Jianwu Xu
email: xujianwu@wanfangdata.com.cn

Zhang Xiumei
email: xiumei@wanfangdata.com.cn

Yuhua Cheng
email: chengyh@wanfangdata.com.cn

Yang Gongliang
email: yanggl@wanfangdata.com.cn

Liu Junli

The Construction of a Clinical Decision Support System Based on Knowledge Base 1

Keywords: Clinical Decision Support System, CDSS, Knowledge Base

Based on a review of domestic and foreign research, application status, classification, composition, and the main problem of a clinical decision support system, this paper proposed a CDSS mode based on a knowledge base. On KB-CDSS mode, this paper discussed the architecture, principle, process, construction of the knowledge base, system design, and application value, then introduced the application WanFang Data Clinical Diagnosis and Treatment Knowledge Base.

Background

Errors made by medical staff in the health care activities have become a social problem of common concern at home and abroad. In 1999, the research report "To err is Human," published by the Institute of Medicine (IOM), noted that the number of medical errors was alarming. Death caused by medical errors has been ranked No. 5 among the top ten causes of human death. Medical errors caused by human factors account for a large proportion of errors, but most of such medical errors can be avoided by the operation of a computer system. Therefore, how to improve medical quality, control medical errors, and enhance patient safety have become urgent tasks for the current health care sector. Accordingly, clinical decision-making research has gradually become an important field in clinical medicine [START_REF] Kohn | To err is human: building a safer health system[END_REF]. Doctors need to have a relevant knowledge of disciplinary expertise, drug, examination, diagnosis and treatment, etc., to make scientific clinical decisions. General practitioners and interdisciplinary doctors are required to have more knowledge.

A high quality design of Clinical Decision Support System (CDSS) can provides guarantees to compensate the limitations of doctors' clinical knowledge, reducing human negligence regarding diagnosis, treatment, examination, and drug use and avoiding repeated treatment and unnecessary medication; however, there are few CDSSs that can be widely applied to clinical treatment at home and abroad. The main reasons include great difficulty in the combination of computer science and clinical work mode, difficulties in the construction of an authoritative knowledge base, rapid updating of medical knowledge, more clinical diagnosis uncertainties, and complex inference mechanisms. Based on this, our team integrated a variety of limitations in the study and practice, proposed the idea of building a CDSS from the perspective of the medical knowledge base, and made attempts to do so [START_REF] Zhao | design concept of OCDSS[END_REF], [START_REF] Lin | Development of a real-time clinical decision support system upon the web mvc-based architecture for prostate cancer treatment[END_REF], [START_REF] Garg | Effects of computerized clinical decision support systems on practitioner performance and patient outcomes[END_REF], [START_REF] Fang | Study of Electronic Medical Record Clinical Decision Support System[END_REF], [START_REF] Yang | design and implementation of CDSS based on clinical guidelines[END_REF], [START_REF] Yang | Study on urology clinical decision support system based on data mining[END_REF], [START_REF] Sun | Intelligent Decision Support System of acute myocardial infarction diagnosis[END_REF].

2

The status of CDSS [START_REF] Lei | Core Value and Clinical Decision Support of Electronic Medical Records[END_REF], Uptodate of Wolters Kluwer [START_REF] Isaac | Use of UpToDate and outcomes in US hospitals[END_REF], [START_REF] Ahmadi | A comparison of answer retrieval through four evidence-based textbooks (ACP PIER, Essential Evidence Plus, First Consult, and UpToDate): A randomized controlled trial[END_REF], [START_REF]Uptodate Homepage[END_REF], Elsevier's MD Consult [START_REF] Wang | MD Consult Introduction to Clinical Medicine Knowledge Base[END_REF], [START_REF]Mdconsult Homepage[END_REF]and so on. China's CDSS was developed late and is mostly still in the theoretical research stage.

There is a large gap compared with foreign countries. The existing CDSS mainly gives priority to single-disease or single-discipline diagnosis and mostly remains in the stage of theoretical studies and laboratory studies, such as the OCDSS of Shanghai University [START_REF] Zhao | design concept of OCDSS[END_REF], the bone tumor aided diagnosis system of the Fourth Military Medical University [START_REF] Liu | Establishment of Clinical Knowledge Base in Computer-Aided Diagnostic Expert System for Osteoma[END_REF], the urology clinical decision support system of Chongqing University [START_REF] Yang | Study on urology clinical decision support system based on data mining[END_REF], the intelligent decision support system of acute myocardial infarction diagnosis of Harbin Institute of Technology [START_REF] Sun | Intelligent Decision Support System of Acute Myocardial Infarction Diagnosis[END_REF], and the neurosurgery clinical decision support system of Fudan University [START_REF] Deng | Neurosurgical Clinical Decision Support System Design Research[END_REF].

Classification and main components of CDSS

In Lei Jianbo's "Core Value and Clinical Decision Support of Electronic Medical Records",CDSSs can be classified according to their internal decision-making mechanisms, system functions, method of recommended, man-machine interaction, communication, and extent of decision support.(table. 1) [START_REF] Lei | Core Value and Clinical Decision Support of Electronic Medical Records[END_REF] The application of CDSS and electronic medical record ( Consultant way, criticism way The degree of decision support Directly (give decision conclusion), indirectly (provide decision-making reference) reports), human-computer interaction and logical reasoning, a user interface, and users(doctors, nurses, and inspectors) (Fig. 1).

Physician

Problems of CDSSs

Although there are many theoretical and system development studies on CDSSs at home and abroad, CDSSs have not yet been widely used on a large scale, the main reasons for which are as follows:

1. CDSSs involve difficult interdisciplinary problems of computers, clinical medicine, psychology, etc. Any CDSS developer who does not have profound clinical knowledge will not be able to meet doctors' demand.

2. CDSSs require a strong and authoritative clinically relevant knowledge base. It is not difficult to build a single-disease or single-discipline knowledge base, but it is very hard to build a knowledge base that can meet all disciplines. 3. Clinical medicine is a rapidly growing discipline. Rapidly updating medical knowledge and conflict among medical views are also factors limiting the usefulness of CDSSs. 4. CDSSs can only achieve their maximum value by closely combining with HIS/EMR systems. Currently, except in large general hospitals, most medium and small hospitals have not established a perfect HIS/EMR system, which also limits CDSSs' ability in the actual docking. Although CDSSs face many problems, more and more clinicians need the support of a CDSS for making clinical decisions on information acquired in the hospital. Currently, theoretical research on CDSSs, computer technology, and Internet technology has developed greatly, which also provides a good environment for the application of CDSSs. A growing number of HIS manufacturers and medical publishers are entering this market.

3

Construction of a CDSS based on a Clinical Knowledge Base

Fig. 2. KB-CDSS Architecture

Based on the current development status of and demand for a CDSS and combined with our rich experience in the construction of large-scale databases, our team proposed Knowledge Base-Clinical Decision Support System (KB-CDSS), which creates different types of clinical databases on the basis of clinical knowledge and vast literature; provides a variety of services for different platforms including organization, search, navigation, interface, and security technology; and offers targeted, timely content according to the user's needs through the interface technology embedded in the electronic medical record system, with the architecture shown in Fig. 2.

Construction principles

The KB-CDSS-based system architecture mainly sticks to the following principles in the construction process:

1. Authoritative content: The knowledge bases supporting KB-CDSS are all written and audited by physicians with extensive clinical experience. Writers and auditors are all served by physicians with vice-senior titles or above and certain academic achievements in their disciplines. 2. Content objectivity: The knowledge sources of the knowledge bases supporting KB-CDSS all refer to openly published information required not to contain personal subjective points of view and that underwent a process of text editing review and expert content review. 3. Modularity: Based on the different types of resources, KB-CDSS is divided into a clinical knowledge base and a clinical document base. The basic clinical knowledge base includes a disease base, a symptoms base, a check base, and a drug base. The clinical document base includes clinical-related academic literature, such as guide specifications, case reports, system evaluations, and metaanalyses. Knowledge bases are maintained and regularly updated by experts in various fields to make it easy for clinicians to gain the latest knowledge. In terms of service, they are divided into literature services, knowledge content services, client services, and interface services. 4. Low coupling: KB-CDSS docks with the EMR system through the system interface. The benefits of using this method are that on the one hand it reduces the cost of the EMR developer so that KB-CDSS data can be called through the interface, while on the other hand it reduces KB-CDSS operation problems, which will not affect the normal operation of the EMR. 5. Immediacy: The clinician in the diagnosis process usually requires immediate decision feedback to facilitate the development of treatment programs. KB-CDSS is able to automatically provide relevant content for instant reference through the internal mapping and retrieval mechanism according to the information in CPOE(computerized physician order entry). 6. Relevance: Clinical treatment involves a variety of disciplines and tasks as well as different use groups. KB-CDSS can be customized for different clients according to different user roles and tasks to provide users with closely related content. 7. Low interference: Doctors' diagnostic process is a highly centralized procedure.

The doctor needs support only when encountering insurmountable problems or when failing to make a determination, so the KB-CDSS only provides support in the form of reminders when doctors need them.

The clinical workflow

Clinical diagnostic work involves many roles, such as doctors, patients, nurses, and Before treatment, patients need to have an understanding of their own symptoms and disease to provide a reference for effective treatment. Doctors conduct inferential analysis according to the patient's description. The main input information at this stage includes patient history data and descriptions of symptoms. Based on this information, the doctor determines the initial disease. KB-CDSS provides relevant descriptive reference information for support.

In the treatment process, the doctors make a determination according to the patient information. If necessary, they arrange for the patient to be tested to provide more patient information to develop and implement disease treatment programs. At this stage, KB-CDSS is divided into active and passive methods of support. The active method is aimed to prevent the serious consequences of improper treatment emerging in the treatment program, such as disease drug contraindications and drug incompatibility. The passive method means that physicians acquire relevant evidence regarding their decisions according to their experience, including basic knowledge and guidelines on diseases, medicines, examinations, system evaluations/meta-analyses, and case reports.

After treatment, Most of the time patient treatment time is short, and there is a lack of relevant health information literacy. KB-CDSS can provide some support for patient education, as shown in Fig. 3.

3.4

Construction of the Clinical Knowledge Base

The clinical knowledge base is the basis of KB-CDSS. The richness and authority of the knowledge base has a direct impact on the application effect of the system. According to the characteristics, the knowledge base is divided into three categories, as shown in Table 2.

Discussion and Cases of the Application's Value

The electronic medical record system is an important part of hospital information. A high-quality electronic medical record system must have CDSS functions, so the CDSS plays an important role in hospital information and should be a necessary part of the hospital information system. A CDSS can significantly improve the quality of medical work, such as by shortening diagnosis time and improving screening accuracy rates. Currently, the most widely used CDSS is the rational drug use system. The CDSS has a positive effect on reducing the incidence of misdiagnosis, preventing drug incompatibility, and handling medication for special populations.

From the perspective of the medical economy, the CDSS improves doctors' work efficiency, thereby decreasing the number of clinics. Accidents caused by medical errors are reduced, thereby reducing damages to the hospital.

The CDSS also has a significant impact on treatment methods. More and more patients pay close attention to the relevant medical knowledge after treatment and before treatment, and know about them due to the Internet and other means before treatment. Currently, the Wanfang Data Clinical Diagnosis and Treatment Knowledge Base developed by Wanfang Data has been formally launched and has dozens of official users and dozens of trial users. Feedback from some hospitals is shown in Table 3.

Fig. 1 .

 1 Fig. 1. Main components of CDSSs

Fig. 3 .

 3 Fig. 3. Clinical workflow

4 .

 4 Platform application: KB-CDSS provides different versions depending on the different application environment. (1) Network version: Doctors generally have the most contact with the Internet. As long as they have access rights, users have access to the necessary knowledge through the network version anytime and anywhere. (2) Mirror version: Most doctors cannot access the Internet at work. The mirror version enables doctors to access knowledge when they cannot access the external network. (3) Client: In order to better support physician workflow and HIS data calls, it can provide more functions that cannot be achieved through the network version. (4) Mobile version: currently, many large hospitals have adopted PDAs or mobile phones as part of their hospital information technology system. The mobile version is quick and easy to use.

Table 1 .

 1 Classification of CDSS Dimension

	Electronic Medical Recor-

Automated alerting (active), active queries (passive) Man-machine interaction Standalone system (can independently exist), integration system (integrate with other systems) Communication way

3.1 KB-CDSS Construction Ideas and Structure

	HIS	EMR			KB-CDSS
	Outpatient doctor workstation		Platf orm layer	Network	Mirror		PDA	Mobile device
		Inter
	Resident doctor	face
	workstation	call
	Nurse workstation	Electronic medical record	Func tiona l layer	IRC retrieval	Content organizat ion	Navigati on display	Data interface	Data Security
	First aid workstation
	Inspection		Data base layer	Disease 、Check、 Drug 、、Symptoms、 Medical technology base	Guideline、Evidence-based literature 、 Medical record report base	...
	workstation
				Clinical knowledge		Medical literature

Table 2 .

 2 Clinical Knowledge Base

	Data type	Examples		Source	Require-	Organization
						ment	method
	Patient		Electronic	medical	HIS/EMR	Authentity	HL7
	data		records			and interi-
						ty
	Scientific	Disease,symptoms,	Textbooks,	Objectivi-	ICD-10,
	knowledg	examina-		authoritative	ty	and	pharmacope-
	e		tion,harmaceuticals,	treatment	authority	ia, examina-
			medical technology	manuals, etc.		tion means
	Experi-	Guideline,	meta-	Openly pub-	Open pub-	Literature
	ence		analysis, system eval-	lished litera-	lishing and	types, content
	knowledg	uation, case reports	ture	source	topics
	e					quality
	3.5	KB-CDSS design
	KB-CDSS design includes four parts: database construction, functional design, inter-
	face design, and platform applications.
	1. Database construction: KB-CDSS is based on Wanfang Data IRC technology,
	which can support the retrieval needs of massive data, multiple fields and multi-
	ple languages. KB-CDSS database is divided into the disease base, check base,
	drug base, guideline base, case report base, evidence-based medicine base, litera-
	ture citations database, and full-text database, which can be used for different
	types of applications.
	2. Functional design: KB-CDSS functions include knowledge content retrieval,
	resource navigation, sorting methods, and related recommendations to provide
	support for different application environments. Knowledge content retrieval pro-
	vides knowledge content points of different particle sizes and supports precise
	and fuzzy searches; resource navigation is organized according to the character-
	istics of content to be easy to read; and sorting is performed according to time,
	relevance, quality, and content. Related recommendations can recommend the
	most relevant content according to the current browsing information.
	3. Interface technology: KB-CDSS interface technology can support major system
	types, such as B/S and C/S, and provide return value according to different input
	parameters, including information on knowledge content, knowledge entry, liter-
	ature, and clustering results. Data are saved in JSON format.

Table 3 .

 3 KB-CDSS Use Situation of Some UsersThrough a study of the theory and application of CDSSs at home and abroad, this paper analyzed the main composition and classification of CDSs and the main problems facing CDSSs, proposed KB-CDSS construction ideas, and described perspectives on KB-CDSS construction ideas, construction principles, clinical workflow analysis, clinical knowledge base construction, and KB-CDSS design. The Wanfang Data Clinical Diagnosis and Treatment Knowledge Base guided by KB-CDSS has been running successfully in some hospitals. KB-CDSS involves a wide range of theoretical research and design development. This study only describes the basic ideas of KB-CDSS and cannot deeply discuss the clinical workflow, knowledge base construction, and system design. In practice, the content and functionality of the Wanfang Data Clinical Diagnosis and Treatment Knowledge Base need to be improved. With the development of computer science, evidence-based medicine and hospital information technology, more CDSSs will be applied to electronic medical record systems in hospitals. Doctors' diagnoses are no longer based on personal experience, but they make clinical decisions with the help of CDSSs. KB-CDSS-based Wanfang Data Clinical Diagnosis and Treatment Knowledge Base aims to achieve the purpose of assisting clinical decision-making through continuous improvement and upgrades.

	User		Version	Advantages	Suggestions
	Beijing Grade-	Network	Simple interface, easy	Extensive knowledge, pa-
	III	General	version	retrieval, rich data	tient-oriented education
	Hospital		types	Recent progress in improv-
				Associated with litera-	ing treatment
				ture
	Shandong	Client	Easy installation, rich	Extensive knowledge, sub-
	Grade-III Hos-		data types, provide	divided according to the type
	pital			expertise and literature	of user, sound reasoning
					mechanism

Found project: National Natural Science Foundation of China, "research on China's information resource industry development policy and management" (ID: 71133006)


Qing Zhang
email: qing.zhang@csiro.au

Ying Su

Ping Yu

Assisting an Elderly with Early Dementia using Wireless Sensors Data in Smarter Safer Home

Keywords: Wireless Sensor Network, Smart home, Activity recognition, Activity of daily living, ADL, Aged carer, Community care, Time series analysis, Information quality 1

The primary aim of this study is to develop a Smart Assistive Living (SAL) platform to enable old people suffering from dementia to stay at home as long as possible. The technology used includes wireless sensor network and broadband network connectivity. The assistive technology aggregates sensor information about environmental, cognitive, physical and physiological factors and integrate them to support the delivery of telehealth and telecare services to older people with mild dementia. The plan for the testing and implementation of the technology and commercial roll out is also briefly outlined.

Introduction

The looming dementia epidemic has plagued all nations around the world, with its social and economic impact widely acknowledged by World Health Organisation, health organizations and governments. For example, about 14 million people in the Asia Pacific Region, the largest continent with more than half of the world population, are plagued by dementia. Alzheimer's Disease International (ADL) estimated that by 2050 the amount of people with dementia will be tripled to 65 millions.

The cost of dementia in 2003 was $60.4 billion for an estimated 12.6 million people with dementia in Asia Pacific region. With an estimated cost of around 1% of GDP, dementia will become the third largest source of health and residential aged care spending in Australia within two decades. The devastating impact of dementia on the social and public health systems is not only due to it being the most disabling of all chronic diseases, but also its enormous economic impact on health system, care services, and productivity losses. Therefore, dementia presents significant challenges to policymakers and public healthcare system.

While there is no cure to dementia, efforts can be made to delay or reduce the number of people suffering from it. The possible preventive and interventive mechanisms include improving social and physical living environment to prevent or slow down the progression of the disease, early interventions (lowering incidence), and improvements in treatment and care to increase survival.

Wellness is about well-being of people. It is indicated by the capability of people in performing their daily activities of living and work. A wellness determination process helps Data related to the wellness indices and behavior recognition can guide the healthcare professionals to identify the variations of people's performance on maintaining or improving health and wellness.

To address the challenge taking the advantage of information and communication technology, we propose a solution called "Smarter and Safer Home" that we hope to enable old people with early dementia (PWED) to remain independently in their homes as long as possible. The second aim of our solution is to enhance quality of life (QoL) for these people, as well as QoL for their family carers. Our strategy is to deploy environmental sensors in their homes, acting as non-intrusive monitoring devices for human behaviour. These sensors are expected to continuously stream data to our central server, where we can then extract and analyse these data to identify the pattern of a person's daily activities. Through the mechanism of machine learning, new activities will be benchmarked against the established patterns to identify those 'abnormal' situations. Once an abnormal signal was detected, an alert will be provided to family carers, such as unattended stove or bathroom flooding. We hope that the 'signal' from the sensors will notify, motivate, and encourage older people and their family carers to take appropriate precaution or intervention. Our proposed technology will lead to new method in assessing the severity of dementia, early detection of abnormal health conditions and development of targeted prevention or early intervention. This will again lead to the reduction of occurrence of behavioural or psychological symptoms and relief burden for family carers to look after their beloved ones. The ultimate goal is to maintain the ADL of people with dementia, improve their QoL and QoL for their family members. This paper will outline the design of our smart home and the plan to implement it.

2

The architecture of the system

We employ the Smarter Safer Home system developed at CSIRO [START_REF] Zhang | Determination of Activities of Daily Living of independent living older people using environmentally placed sensors[END_REF] to collect and analyse sensor data from homes of dementia patients. The system consists of two components: (i) Wireless Sensor Network (WSN) for data transmission and (ii) intelligent home monitoring system to collect sensor data, perform data analysis and present results to end user.

Wireless Sensor Network

Although there are many previous work on monitoring ADL of people with dementia through wearable sensors such as RFID markers and wearable accelerometers detecting falls ([1,2,3]), the innovative aspect of our proposed solution is to place the sensors in the person's living environment, instead attached to their body for nonintrusive monitoring of human behavior. The two advantages of this solution are: First, wearable sensors are not always convenient for users to carry around. This is particularly relevant for people with mild dementia as they easily forget things; second, sensors placed in environment is out of the sight of the users, thus has less interference with their daily lives. Third, the data recorded by sensors are anonymous, containing very little information about personal privacy. Table 1 describes all types of in-house sensors that will be used in our smart home system.

Data collection

This module gathers continuously recorded, daily activity data of a person from the non-intrusive sensors deployed at invisible locations at home. Figure 2 presents the places where these sensors are likely to be located.

Figure 2

Typical places where the sensors will be installed.

Data analyses

This module analyses raw sensor data captured to extract information about a person's routine behaviour and ADL. It will extract activity patterns and measure the person's physical, health and mental functions. Based on statistical data analysis and machine learning, it will provide warning/alert of abnormal situations in real time when such situation happens. By triangulating data from other sources, it is anticipated that the level and type of assistance that a person with early onset of dementia requires can be estimated and be provided to enable him or her to live independently as long as possible. Raw sensor data is initially processed at the in-house local server. The output is converted to semantically meaningful representation of observed actions. The design and implementation of information presentation and service provision will benefit from semiotics, a well-established discipline of signs and human communication in social context. The semiotic framework will guide us in taking account of syntactic, semantic and pragmatic levels of system functions and service provision to the different stakeholders. In our system, sensors collect simple actions such as turn on/off the microwave, move in/out of the bathroom. These actions, along with their temporal features, are then transmitted to the database server for more complex activity extractions. An activity is a more complex motion pattern, typically composed of many actions and with longer durations. For example, turning on a microwave is considered an action, while preparing a meal is an activity. Typical activities of daily living, as a concept that is first established by Katz, include bathing, dressing, toileting, transferring, continence and feeding ( [START_REF] Plan | Katz Activities of Daily Living (ADL)[END_REF]). It is well known that maintaining ADL becomes a major focus for care of people with dementia. Table 2 shows a non-exhaustive list of ADLs that could be automatically extracted from the related sensors in our system.

Wellness determination process through monitoring daily activities

Fig. 2 shows the schematic representation of the determination of wellness of elderly in the proposed Smart Home. The recognition of basic ADLs and determination of wellness of the elderly are described in the following Equations.

P (t|c) = ' ' ' ' 11 ( 1) ' ct ct ct ct t V t V NN N N K       (1)
where N ct is the number of times a particular sensor ID occurs in activity 'c'. V is the set of sensor IDs. K′=|V| is the number of unique sensor IDs. The first function( 1 ) indicates about the non-usage or inactive duration of the appliances, and the second function (

 2
) is about the over-usage of specific household appliances. The following are the details:

12 1 ; 1 (1 ) n T t TT        (2)

Data Presentation

In order to improve awareness and facilitate self monitoring, data will be presented in tablet PC or mobile phone. This will enable family members to gain an insight into the capacity and condition of living of their beloved ones; assist health care providers to get a whole picture of the person's daily lives, routines and health status. The awareness and information will facilitate the timely provision of intervention through telehealth and telecare. The data will be presented to the person for whom home monitoring service is provided, to family care givers and to clinical professionals providing health services to the person. It can be used by the person for the purpose of self-monitoring, by care givers as a means for remote monitoring and care assistance, and by clinicians to support their diagnostic and treatment decision through examining the changes/trends in ambient and activities of daily living, psychological, behavioral and vital signs, respectively, for older people with early dementia, which is particularly useful for those living at home alone. For the later, we will provide a tablet-based application for them to self-monitor their daily activities and conduct physiological assessments regularly.

Implementation studies

The Smart Home system will be developed and implemented in the relevant population to develop and test the system implementation methods. The purpose of the trial is to (1) develop and fine-tune the technology; (2) understand the facilitators and barriers for acceptance and usage of the system; (3) test acceptance, usage and impact of the system on people with mild dementia and their family carers; (4) develop the relevant training and support services to foster adoption and usage; and ( 5) develop the business model for the commercial roll out of the solution to large population. These will be achieved in three stages.

Stage 1. Develop and fine-tune the technology, and develop understanding about facilitators and barriers for system adoption

This trial will be conducted in small population with five to ten people who suffer from mild dementia. The selection of sample will take into account a balance of genda, living environment and life style. Both engineers and system analysts will be involved in the trial. In addition to the data collected by the sensors, human factors for system implementation will also be collected through interview and observation. These data are important in guiding the development of user-friendly interface that will be accepted by the people with dementia and their family carers. The indicators for human factors include the interface design that is acceptable by the end users, the older people's preference for navigating the system and the type of devices with optimal opportunity to be accepted and used. The functions and messages that are useful for the intended population will also be identified.

Stage 2. Pilot trial of the system in small population group

After the initial validation, the system will be further implemented in a small population group of 30 to 50 people with dementia to further test the functionality, user acceptance, usage and effectiveness of the system. Any issues identified will be timely fixed, with system improved. This test and improvement process will be continuously conducted and evolved until enough evidence has been gathered to prove that the system has achieved its objectives.

Stage 3. Large scope implementation to develop the business model for rolling out the system

After the efficacy of the system is validated, the solution will be rolled out in the scope of a city or province to further test its efficacy for large population. The relevant business model for technology roll out will be developed. This include costing model for the solution, implementation strategies, end user support and roles and responsibilities of the relevant stakeholder groups, etc.

Conclusions

This paper briefly outlines a comprehensive Smart Home solution to assist people with mild dementia to live at home. It first presents the technical solution, then the empirical technology development, pilot testing and implementation strategies for rolling out the system to the population. Different from the solutions with wearable devices, the sensors of our Smart Home are placed at various locations in the residency of a person, which will bring in the advantage of no intrusion thus comfort of use. We plan to develop and introduce the system through a rigorous technology development and implementation strategy and practice. The human factors that either facilitate or hinder the adoption of the Smart Home solution will be fully noticed with solution developed. The conduct of the project will contribute to Smart Home technology development and knowledge about effective ICT solutions to assist people with memory loss. It will also contribute to addressing the biggest challenge of population ageing in the current world -dementia, taking advantage of current advancement of ICT.

Figure 1

 1 Figure 1 illustrates the function of the smart home: data collection, analyses and presentation.

Figure 1 :

 1 Figure 1: Smart Home platform architecture

Table 1 :

 1 List of environmentally placed sensors

		Sensor type	Data collected
		Motion sensor	Incidents of movements
		Accelerometer	Mattress movements
		Power sensor	Electrical power draw by appliances
		Acoustic sensor	Water flows in pipes
		Temperature sensor Temperature readings
		Humidity sensor	Humidity readings
		Read switch	Doors open/closed
		Pressure sensor	Sofa/couch being attended
	2.2	Intelligent home monitoring system

Table 2 :

 2 Extracting ADLs from sensors

	Daily activities	Sensor types
	Indoor walking/wandering	Motion sensors
	Sleep	Motion sensors, accelerometer
	Preparing meals	Motion, Power, Acoustic sensors
	Washing cloth	Power, Motion sensors, Reed switch
	Visiting bathroom	Motion, Temperature, Humidity sensors
	House cleaning	Motion, Power, Acoustic sensors
	Postural transfer	Pressure, Motion sensor

Acknowledgements: This work was financially supported by the National Soft Science Planning (2011GXQ4K029), and all sensor data was collected via National Population and Reproductive Health Science Data Center of National Scientific Data Sharing Platform for Population and Health.


Yuan Yao
email: yaoyuan301@sina.cn

Ying Su

Health Outcomes and Cost Benefit of Home e-Health in Helping to Manage Heart Failure

Keywords: Chronic heart failure, Blood pressure control, Lung transplantation, Monitoring system, Pulmonary function, Diabetes control, Self-measurement, Controlled trial, Hypertensive patients, African Americans

This study presents a systematic review of the nature and magnitude of outcomes associated with e-Health of cardiac diseases. Methods: A comprehensive literature search was conducted on Medline and the Cochrane Library to identify relevant articles published between 2000 and 2014 in which the outcome measure used was one or more of health outcome, proxy health outcome, patient compliance or cost. Studies identified were subjected to narrative review. The magnitude and significance of the Home e-Health effects on patients' conditions (e.g., early detection of symptoms, decrease in blood pressure, adequate medication, reduced mortality) still remain inconclusive for cardiac diseases. However, the results of this study suggest that regardless of their nationality, socioeconomic status, or age, patients comply with Home e-Health programs and the use of technologies. Importantly, the Home e-Health effects on clinical effectiveness outcomes (e.g., decrease in the emergency visits, hospital admissions, average hospital length of stay) are more consistent in Heart Failure. Home e-Health of cardiac diseases seems to be a promising patient management approach that produces accurate and reliable data, empowers patients, influences their attitudes and behaviors, and potentially improves their medical conditions. Future studies need to build evidence related to its clinical effects, cost effectiveness, impacts on services utilization, and acceptance by health care providers.

Introduction

It is over a decade since e-Health started to be explored as a tool in the reduction of exposure to risk factors for disease, and in the management of illness. It has taken various forms as technology has evolved, but with the exception of the remote interpretation of images, has failed to become part of mainstream medicine in, for instance, the UK. In previous research, most of intelligent works were centralized at healthcare center and the function of telemedicine terminal device was mainly focused on the acquisition and transmission of physiological data. Heart Failure has features which appear to make it particularly suitable for management involving e-Health: measurement in healthcare settings may be spuriously high ("white coat cardiac diseases"); people with mild to moderate cardiac diseases feel well when off medication but may feel unwell on treatment so may not use it conscientiously; the information to be conveyed between the individual and the healthcare professional is simple; the individual's use of the equipment is unlikely to be comprised by their being acutely anxious or fearful because of the condition. We created a generic workflow model based on interviews and observations at three CR clinics.

Methods

A comprehensive literature search was conducted on Medline and the Cochrane Library to identify relevant articles published between 2003 and 2013. The keywords that were used include telemonitoring, telecare, telemedicine, telematics, telehealth, and telehomecare.. All abstracts were read to identify how many studies were reported in the literature. The inclusion criteria required that the studies: (1) have an experimental design involving direct data collection from patients with any of the four considered chronic diseases, (2) be published in the English language and appear in peer-reviewed journals, and (3) document telemonitoring effects. The abstracts and papers were reviewed by two independent readers. 3 Results

Literature search

Forty three abstracts were found, and led to the identification of 14 relevant RCTs. The 29 abstracts were rejected because they did not report information on health outcome, proxy health outcomes, treatment process, patient compliance and/or cost with particular respect to management of cardiac diseases. Some were excluded as they were trialing mobile phone-based interventions with no e-Health element.

3.2

Health outcome

With the exception of pulmonary diseases that represent a variety of medical conditions, telemonitoring of cardiac diseases was specific to each of these illnesses, and involved adult patients suffering from these medical conditions. Only in few cases, subgroups of the general population (e.g., children, veterans, pregnant women) were considered.

Proxy health outcome

Four RCTs evaluated the efficacy of e-Health in controlling cardiac diseases, with somewhat conflicting results. Kirtava, Z., et al 2013 [START_REF] Kirtava | mHealth for cardiac patients telemonitoring and integrated care[END_REF] randomised 54 patients with main medical results, Quality of Service (QoS), Quality of Experience (QoE), cost-efficiency and remaining challenges -is presented, as well as the outline of its continuation -MTM-2 project, which aims improvement of decision making for emergency cardiac patients and usage of mHealth applications for integrated care provision in remote regions of Georgia. This result was confirmed by two other RCTs. Goroso, D. G et al 2013 [START_REF] Goroso | Monitoring heart rate variability on-line used mobile telephone 3G e-health service oriented[END_REF] provide a mobile tool to prevent early cardiac arrhythmia by means of monitoring online and assessing heart rate variability. Preliminary results proved effective in Sao Paulo for study of heart rate variability. This new service uses mobile phone to record, evaluate and transmit information, which currently is in clinical validation. Foche-Perez et al 2012 [START_REF] Foche-Perez | An open real-time tele-stethoscopy system[END_REF] twelve patients have been auscultated by all the physicians using the tele-stethoscopy system, versus a local auscultation using traditional stethoscope. The system must allow listen the cardiacpatientspatients (systolic and diastolic murmurs, gallop sound, arrhythmias) and respiratory (rhonchi, rales and crepitations, wheeze, diminished and bronchial breath sounds, pleural friction rub) sounds [START_REF] Foche-Perez | An open real-time tele-stethoscopy system[END_REF].

An architectural framework of a system utilising mobile technologies to enable continuous, wireless, electrocardiogram (ECG) monitoring of cardiac patients. The proposed system has the potential to improve patients' quality of life by allowing them to move around freely while undergoing continuous heart monitoring and to reduce healthcare costs associated with prolonged hospitalisation, treatment and monitoring [START_REF] Sneha | A wireless ECG monitoring system for pervasive healthcare[END_REF]. At follow up, 36% of those allocated to 'e-Health' had pressures below 140/90 as did 31% of those receiving usual care. Only those in the third arm -'e-Health' as above plus web delivered pharmacist support -did significantly better than those receiving usual care (56% controlled) [START_REF] Pare | Systematic review of home telemonitoring for chronic diseases: The evidence base[END_REF].

Process of care

Telemonitoring projects of cardiac diseases had the largest samples of patients, which exceeded by far the size of the experimental and the largest average study durations (Table 1). Fanucci et al 2013 [START_REF] Fanucci | Sensing Devices and Sensor Signal Processing for Remote Monitoring of Vital Signs in CHF Patients[END_REF] evaluated a complete and integrated Information and Communication Technology system (CHF patients to daily collect vital signs at home and automatically send them to the Hospital Information System , allowing the physicians to monitor their patients at distance and take timely actions in case of necessity.) against usual care in confirming suspected cardiac diseases in 74 adults. All 74 underwent 24 hour ambulatory monitoring; e-Health appeared superior in detecting true cases (64%) to usual care (26%). E-Health was also more rapid in confirming or refuting the suspicion of cardiac diseases.

Nowadays, chronic heart failure (CHF) affects an ever-growing segment of population, and it is among the major causes of hospitalization for elderly citizens [START_REF] Fanucci | Sensing Devices and Sensor Signal Processing for Remote Monitoring of Vital Signs in CHF Patients[END_REF]. Dennis et al 2013 [START_REF] Dennis | Do people with existing chronic conditions benefit from telephone coaching? A rapid review[END_REF] addressed Telephone coaching for people with chronic conditions can improve health behaviour, self-efficacy and health status: telemedical home blood pressure measurement (5 days, duplicate measurement, four times daily), clinic blood pressure or ambulatory blood pressure monitoring. They confirmed the existence of "white coat cardiac diseases", but showed an increasingly good correlation between telemedical and ambulatory monitoring over the five day periods, with the afternoon readings having the best correlation with the ambulatory value. Cowie et al 2013 [START_REF] Cowie | e-Health innovation: time for engagement with the cardiology community[END_REF] performed an equivalence study to e-Health innovation in detecting uncontrolled cardiac diseases over one year in 62 out-patients of a cardiac diseases clinic. Each patient had e-Health and face-to-face consultations on the same days, the order of the two encounters being randomised. The e-Health system was found to be equivalent to in-person consultation in detecting uncontrolled cardiac diseases, in the physicians' use of additional tests, and in the associated therapeutic decisions. ESC has invested in innovation in education and learning by delivering rich content from its meetings online, by delivering a variety of specialty courses on webinars, and last but not least by delivering clinical guidelines to the personal digital assistants of specialists.. Munoz et al 2011 [START_REF] Munoz | Telemedicine in Pediatric Cardiac Critical Care[END_REF] explored a case series of pediatric patients teleassisted from the Cardiac Intensive Care Unit (CICU) at Children's Hospital of Pittsburgh of University of Pittsburgh Medical Center, Pittsburgh, PA, to the CICU at Hospital Valle del Lili, Cali, Valle, Colombia, between March and December 2010. Seventy-one recommendations were given regarding 53 patients. Median age and weight were 10 months and 7.1 kg, respectively. Ventricular septal defect, transposition of the great vessels, and single ventricle accounted for most cases. The most frequent recommendations were related to surgical conduct, management of arrhythmias, and performance of cardiac catheterization studies. No technical difficulties were experienced during the monitoring of the patients. Satisfaction rates were equally high for technical and medical aspects of telemedicine service.

Duck Hee et al 2012 [START_REF] Duck Hee | A heart monitoring system for a mobile device[END_REF] showed that the fall in blood pressure in their e-Health group was (ECG) signal preprocessing including filtering, power noise canceling, and level shifting adherence of 17.7%.

3.4

Cost of care Kifle, M., et al. [START_REF] Kifle | Interplay of cost and adoption of telemedicine in Sub-Saharan Africa: The case of tele-cardiology in Ethiopia[END_REF] examines the role of Tele-Medicine in the healthcare system and analyzes the costs and benefits of introducing Tele-Cardiology services in Ethiopia (a Sub-Saharan African country). This is a cost comparison study for the treatment of cardiac patients traveling abroad versus patients treated via Tele-Cardiology. Our findings show that Tele-Cardiology is clinically more feasible and more cost effective compared to patients traveling abroad for treatment. Those monitoring themselves made on average 1.2 fewer cardiac diseases related consultations in the year which represented a cost saving despite the expense of the equipment. Martin et al 2013 [START_REF] Cowie | e-Health innovation: time for engagement with the cardiology community[END_REF] need to be involved, and to collaborate with engineers and other key stakeholders at each stage of the process: the technology design and integration, the assessment of the value of e-health innovation (in terms of the impact on patients, the healthcare system, and the costs), the education and support of healthcare professionals and patients, the development of guidelines, and the standardization of systems and models.

Discussions

The introduction of e-Health is a change to the structure of healthcare, so it is appropriate to consider its effect on the processes and outcomes of care. This survey of papers reporting RCTs shows that it is feasible, at least experimentally, to introduce e-Health into the process of identifying and working with individuals with cardiac diseases to reduce their subsequent risk of stroke, ischaemic heart disease and sudden death. It also confirms that this has not been introduced into everyday clinical practice in countries which take an 'evidence based' approach to healthcare, though the literature has developed [START_REF] Hickey | Cardiac e-Learning: Development of a Web-Based Implantable Cardioverter Defibrillator Educational System[END_REF][START_REF] Hansen | The Australian e-Health Research Centre: enabling the health care information and communication technology revolution[END_REF][START_REF] Karunanithi | Care Assessment Platform: An ICT-Enabled Home Care Model for Secondary Prevention of Cardiovascular Diseases[END_REF]from that available to the guideline development groups producing the CSIRO (Commonwealth Scientific and Industrial Research Organisation) and the Queensland Government have jointly established the Australian e-Health Research Centre (AEHRC) Guideline 97 (Risk estimation and prevention of cardiovascular disease February 2011). The former guideline says "Routine use of automated ambulatory blood pressure monitoring or home monitoring devices in primary care is not currently recommended because their value has not be adequately established; appropriate use in primary care remains an issue for further research" and the latter does not mention it at all. There is no definitive evidence that e-Health improves the ultimate health outcomes of the management of cardiac diseases. Our synthesis of the literature indicates that e-Health is likely to be beneficial in controlling cardiac diseases, and thus has the potential to improve health outcomes. Little is known about how this effect is mediated -there is one suggestion that it is through improved compliance. E-Health can also reduce the requirement of hospital care and the number of mortalities. Modern e-health systems can control successfully such diseases as cardiac, diabetic or pulmonary diseases.

The major weakness of this paper is that it is narrative review not a systematic review or a meta-analysis. This is compounded by the fact that the RCTs available are generally small and/or have short follow-up times, so should not be over-interpreted. A more quantitative approach would add value, but, given that there are some relevant trials that have finished recruiting participants but not yet reported (The European Commission has undertaken to support member states in deploying e-health solutions for chronic disease management and in setting quantitative targets such as reduction in hospitalization for heart failure, reduction in healthcare resources by patients with diabetes, and improvement in quality and length of life.), there will be a more optimal opportunity for formal meta-analysis in the near future. We also note that Fayn et al are about to start another trial building an operational e-health infrastructure including pervasive services and remote distributed applications servers in the cardiology domain [START_REF] Fayn | Towards new integrated information and communication infrastructures in e-health. Examples from cardiology[END_REF].

Conclusions

So far, despite the recent history of home e-Health, a significant body of knowledge has been developed and made available to policymakers and clinicians. Based on the results of this review, home e-Health of cardiac diseases seems to be a promising patient management approach that produces accurate and reliable data, empowers patients, influences their attitudes and behaviors, and potentially improves their medical conditions. Nevertheless, some studies have shown that there is an overall reduction in both systolic and diastolic values, and the presumed mechanism is better patient engagement in disease control and compliance. For insurance companies and governments to consider future endorsement of this patient management approach, and subsequent reimbursement for the services provided, it is important to demonstrate its feasibility at the population level. More rigorous research on home e-Health would build stronger evidence that lead to changes in the practice and management of these cardiac illnesses, to acceptance of this patient management approach by payers and providers, and to its future integration in the overall process of care.

Table 1 :

 1 Overview of Research Designs

	Sensor type	Cardiac Diseases
	Total number of studies	16
	Type of design	7
	Adults with congestive heart failure 15
	Size of experimental group	Minimum:10; Maximum 230
	Study duration	Minimum:1 month; Maximum 36 months
	Main types of data being transferred Basic vital signs; Symptoms
	Frequency of data transmission	More than once a day 4, Once a day 8

Acknowledgements: The researchers acknowledge the support of the National Soft Science Planning (2011GXQ4K029), and National Population and Reproductive Health Science Data Center of National Scientific Data Sharing Platform for Population and Health funded by Ministry of Science and Technology, China; the research volunteers and the respondees.


Jeffrey Soar
email: soar@usq.edu.au

Ying Su

Concerns of Ageing and Interest in Assistive Technologies -Convenience Sampling of Attendees at an Aged Care Technology Exhibition in China

Keywords: China, Ageing, Technology

As in many countries, ageing and aged care in China is an important issue. There is a need for more research on the potential for technology to assist older people and their families, particularly given the disappointing levels of adoption in developed countries. Accordingly this paper aims to gain insight into the perceptions of older people and stakeholders in relation to issues of ageing and their interest in adoption of technology. Using convenience sampling, the authors surveyed 277 participants to understand peoples concerns concerning ageing and use of technologies. Results from this study provide a basis for discussion with stakeholders, particularly concerning ageing in China.

Background

This research was conceived as an initial step in a long-term program to gain greater insight into the perceptions of older people and stakeholders in relation to issues of ageing and their interest in adoption of technology. The adoption of home telehealth and intelligent assistive technology has to date been disappointing [START_REF] Soar | A model for regional innovation and information sharing to reduce falls amongst the elderly through intelligent technologies[END_REF] and there is a lack of convincing research evidence of its benefits. The needs and concerns of older adults as computer users may be different from those of younger users as a result of the changes associated with the ageing process [START_REF] Wagner | Computer use by older adults: A multidisciplinary review[END_REF]. There is a need for a greater appreciation of ageing and adoption of assistive technologies from the perspective of older people and their families. The increased use of healthcare associated with ageing is well documented [START_REF] Oliver | Managing risk in older hospital inpatients[END_REF] including the increasing use of medications needed to manage chronic conditions [START_REF] Marek | Patient Safety and Quality: An Evidence-Based Handbook for Nurses[END_REF]. Other challenges of ageing include elder abuse particularly financial abuse [START_REF] Clare | OF ELDER ABUSE IN WESTERN AUSTRALIA: A Qualitative and Quantitative Investigation of Existing Agency Policy, Service Responses and Recorded Data[END_REF]. Associated with increasing use of health and support services is the need to manage documentation and processes for making claims on government or health insurance. It can be a challenge for carers of the frail elderly, likely to be elderly themselves [START_REF] Abs | Older Carers. 4102.0 -Australian Social Trends[END_REF], to navigate the complexity. ICTs offer potential benefits for older people including management of records, personal safety, comfort for families, reminders for medications and other needs, remote access to clinical and other care services, social connections, quality information for self-care, GPS (Global Positioning Systems) tracking and assistance in way-finding, support for people with specific disabilities amongst many others [START_REF] Su | Consumer-Centered Ehealth: Challenges and Opportunities for China[END_REF].

The stoicism of the War Generation may result in a reluctance to seek help or to report instances of breaches of privacy. Anecdotally a commonly-reported comment from older people is they don't want to be a "bother" to people. Entry into the aged care system can occur through a catastrophic event such as a serious fall or from a visit from a relative who observes the older person is no longer able to care for themselves. Better use of ICTs (Information and Communication Technologies) such as Personal Alarms or other sensors and monitors may allow difficulties to be known earlier and for help to be obtained to assist someone to live at home. Trials of Telecare and telehealth have shown these to be well-accepted by consumers and their families.

ICTs are usually designed by young people with good eye-sight, dexterity and familiarity with technologies. Older people often have poorer vision; there are slower connections in the brain. The choice of fonts is rarely undertaken with cognisance of the needs of older users. The ICT hardware and software that older people have may not be updated as frequently as that of other ICT users. They may not understand how to use the automatic updates that software vendors provide leaving them vulnerable to the security gaps these fixes may have addressed.

The cohort of older adults today is very different from previous cohorts of older people, and the next cohort of the elderly, the "baby boomers," is also likely to be different from today's elderly [START_REF] Sand Sharit | The Aging of the Population: Opportunities and Challenges for Human Factors Engineering. The Bridge on Technologies for an Aging Population[END_REF]. Baby boomers can be expected to continue their high use of ICTs into their older years. They will have high expectations of services that can be delivered, of ways they can manage their own care. An issue for them will be maintaining their competencies in the face of the relentless change of technologies; already there is a large gap between teenagers and older people in the social networks and other applications used. The nature of cyber-attacks has changed considerably and baby-boomers may find it a challenge to keep up to date with technology change.

Chinese government policy on ageing, aged-care and technology

Ageing is an area of high priority for governments in China as evidenced by the 12th Five-Year Plan [START_REF]State Council of the people's Republic of China, The planning and construction of social endowment service system[END_REF] and the conclusions of the third plenum session of 18th Party Congress [START_REF]CCP decision on deepening the reform of some major issues[END_REF]. Included in the "CCP (Chinese Communist Party) decision on deepening the reform of some major issues" latter amongst other recommendations for health and aged care services is "Make full use of information technology tools to promote high-quality medical resources longitudinal flow".

Methods

The researchers are involved in organising an annual Aged Care Exhibition in Nanjing, China. This is hosted by the Department of Civil Affairs of Jiangsu, Office of Jiangsu Provincial Committee on Aging, and the China Council for the Promotion of International Trade, Jiangsu Sub-Council. Exhibits include products for mobility, nutrition and dietetics, dietary supplements, mobility devices, training, TCM (Traditional Chinese Medicine) and complementary therapeutics, age-specific real estate, assistive devices, diagnostic devices, "age-friendly" household articles and construction materials, accident prevention products, bathroom products, communication devices, positioning systems and many others. Attendees include government officials, providers of services for the aged, and suppliers; the attendees are largely consumers and the event attracts large numbers of older people. Lectures and presentations are provided by suppliers, researchers, government officials and others covering topics such as analysis of the "silver" market, government policies, the plans of care service organisations and workshops on specific topics such as on ophthalmology and prevention and treatment of cardiovascular diseases. Nanjing was selected as the venue for the annual event; it has an older demographic than most of China, it is easily accessible and it is seen as a desirable city that is a popular venue for conferences.

In 2013 the opportunity was taken to try to survey attendees about concerns of ageing and opinions of assistive technologies. Convenience sampling was undertaken of attendees of the annual Aged Care Technology Expo at Nanjing over three days in November 2013. Approval for a survey of attendees was granted by ISTIC through their processes for research and a survey form developed and tested. This asked for ranking of concerns of ageing and indications of technologies that attendees might be interested in. The options were decided upon following a focus group of aged care policy officials and researchers.

A volunteer assisting at the conference agreed to invite attendees to complete the survey form and a reward was offered in the form of a plastic finger massage device. The volunteer was located at a booth near the main entrance to the Exhibition. Consequently approaches were made only to people who passed near the booth, as the entrance to the exhibition was across several large doors to the Exhibition only a minority of attendees was invited to complete it.

Results

277 attendees completed the survey form which is a very small level of participation given that attendance at the event is around 50,000 people. The numbers of attendees might itself have been a barrier to participation as only a small number of people would have been able to see the volunteer due to the large numbers of people and that entry to the event was through a large open doorway. The volunteer only asked people who passed near her particular booth; there were 190 exhibitors at the event using booths or other displays for their projects and services.

Of the ten options provided on the form for concerns of ageing the responses, in priority order were: health (190), maintaining social activities (140), physical decline (134), accessing public transport (130) Family not taking care of you (113), not having enough money (111), mental decline (99), house not suitable for an older person (76), and family taking your money and assets (63). No respondees selected "other". The responses to the question "Which of the devices people would be happy to purchase" the responses to the options given were: Home telehealth device for online medical consultations (117), Reminder service (appointments, medications etc) (102), Home sensors (87), GPS tracking device in case I get lost (71), Home cameras so my family can see I am OK (69), other products/services (0). No respondees selected "other".

Discussion

Concerns of people about their own ageing are many and varied. There are concerns about a decline in health, increasing chronic disease and disability. Of concern to consumers, funders and care providers is the correlation between the rising number of chronic conditions accumulated with ageing and rising healthcare costs [START_REF] Lehnert | Review: Health Care Utilization and Costs of Elderly Persons With Multiple Chronic Conditions[END_REF]. There are expectations and some evidence that a greater use of technology might assist consumers and their carers to better manage health including remote access to care services. In this sample health and physical were the major concerns of ageing ranked first for health and third for physical decline. There is some evidence of the benefits of maintaining social activities for health and well-being and that was the second major concern of the respondees. Despite China, and especially Nanjing, having a reasonable public transport system in terms of a metro, bus and train networks, accessing public transport was the next concern of respondees. There are indications that transfers are the greatest risk for frail elderly in accessing transport although most Metro and train stations have elevators as well as escalators.

China is a nation influenced by the Confucian tradition which values age and places expectations that your family not taking care of you in older age. The option of "family not taking care of you scored 113 responses suggesting it is a concern of some older people. Nanjing is in the developed east coast strip where greater wealth is evident compared to inner or western Chin yet "not having enough money" scored 111 responses. Lower scores were received for "mental decline" (99) and "house not suitable for an older person" (76). Most Chinese live in apartments and depending on whether they were serviced by elevators might indicate their suitability for frail aged.

Elder abuse is a sad feature of societies and ICTs could offer an additional channel for this to occur, particularly financial abuse [START_REF] Clare | OF ELDER ABUSE IN WESTERN AUSTRALIA: A Qualitative and Quantitative Investigation of Existing Agency Policy, Service Responses and Recorded Data[END_REF]. Older people often use ICTs to manage their retirement savings and investments. They may be less alert to instances of fraud or errors by financial institutions and may be more trusting of institutions such as banks; they may need help to access accounts and manage security including password changes. It may be tempting for people assisting to take advantage of that trust. In this research the concern of "family taking your money and assets scored low (63) but enough to indicate this was a concern of some older people.

6

Technology and new service models

The need for streamlined service models for aged care has been identified [START_REF] O'reilly | Clinical outcomes in residential care : setting benchmarks for quality[END_REF] and technology has potential to help transform the experience of ageing and the delivery of care and support services. While a great deal of work has been done on pilot studies, time-limited trials and telehealth frameworks for health delivery [START_REF] Barrientos | Impact analysis of assessment, consultation and education services to support the adoption of smart home technologies, innovations for chronic disease prevention and solutions for independent living[END_REF] very little research has been done on analysing the critical successes and failures of the delivery models. There is disappointment in governments, providers and remote clients that telehealth has not been adopted at an expeditious rate and the reasons for this warrant investigation [START_REF] Goodwin | The State of Telehealth and Telecare in the UK: Prospects for Integrated Care[END_REF]. This research invited responses to the question "Which of the devices you would be happy to purchase". The highest response was for the option "Home telehealth device for on-line medical consultations" (117 responses). Telehealth has the potential to automatically provide a consultation including taking of vital signs through peripheral devices. A Reminder service (appointments, medications etc) (102) was the second most popular item followed by Home sensors (87), GPS tracking device in case I get lost (71) and Home cameras so my family can see I am OK (69). The form provided space for respondees to indicate other devices but no reponses were received for "other".

Technology along with innovations such as universal housing design [START_REF] Demirbileka | Universal product design involving elderly users: a participatory design model[END_REF] has the potential to meet people's needs at various stages of their lives. These can make our homes safer and reduce the need to move home in the event of illness, frailty or disability. The aged and community care sector is yet to fully embrace the wide range of technology innovations that are increasingly available.

Smart home technologies include Telecare, Telehealth, robotics, wearable devices, and ubiquitous sensors on appliances such as microwave ovens and light switches. The needs of people with dementia that technologies could assist with are great and varied. This includes reminders for ADLs (Activities of Daily Living) and medications. Consumers, families and carers could access care through Telehealth technologies; that is technologies that can provide an automated consultation, a link to a remote clinician when required and information for guided self-care. Similarly these and other devices can facilitate social connections and some residential care facilities already make Skype available for residents. Telecare can help keep people safe through movement detectors, out-of-bed sensors, automated lighting to guide someone to the toilet when they get out of bed in the night, sensor for extreme heat in the kitchen and flooding in the bathroom. Signals can be selectively routed such that an alert about a fall might have a different recipient than an alert about a fire.

As many people are aware the responsibility of caring for a person with dementia can be consuming and allow little time for other responsibilities. Through the technology families can have reassurance that their family member is safe. Sensors can detect if a person opens a door, uses the microwave or other appliances, has a fall, and is taking medications and otherwise following ADLs. The technology can give respite to families so they can live more of their own lives or even to be able to go shopping knowing they will receive an alert in the event of an adverse event such as a fall or in the case of wandering. Technology has the potential to relieve clinicians of much of the non-clinical tasks that clinicians need to deal with, allowing them to focus more on the functions they were trained for.

Sensor networks can be connected to Big Data tools that can analyse massive amounts of data that various sensors can capture. The analytical tools can detect subtle changes in behaviour that might otherwise be missed by busy clinicians. Home visiting care staff members typically spend significant hours driving from client to client. The technology can assist to triage and prioritise visits it can also indicate when the client may not need a personal visit. Clinical staff can reduce unnecessary visits and instead focus on more critical needs for their skills. Overseas these technologies have been demonstrated to reduce admissions, readmissions, and length of stay when a client is admitted. There is also an environmental benefit in reducing client and carer travel to access services.

Despite the long-anticipated benefits the adoption of Smart Home technologies for care has been slow but there are signs that the pace of adoption is starting to accelerate. There have been a small but increasing number of larger-scale roll-outs. There is more available evidence to support the expectations of benefits from Smart Home technologies. The better known studies include the Whole System Demonstrator in the UK [START_REF]Whole system demonstrator programme: Headline findings[END_REF] which involved over 6000 patients in a randomised controlled trial. It found show that Telehealth can deliver a 15% reduction in A&E/ED (Accident & Emergency or Emergency Department) visits, a 20% reduction in emergency admissions, a 14% reduction in elective admissions, a 14% reduction in bed days and an 8% reduction in tariff costs and a 45% reduction in mortality rates. This was not dissimilar from the evaluation of a similar project in the Veterans Administration system in the USA which found 25% reduction in bed days, 19% reduction in hospital admissions and high consumer satisfaction at a relatively modest cost [START_REF] Darkins | Care Coordination/Home Telehealth: The Systematic Implementation of Health Informatics, Home Telehealth, and Disease Management to Support the Care of Veteran Patients with Chronic Conditions Telemedicine and e-Health[END_REF].

There is an expectation that the move of Baby-boomers into the age when they will require aged care services will have significant impacts. This is in terms of their political pressure for improvements including greater access to technology as well as provide markets for "killer aps", that is innovations that perhaps have not yet been invented but which by themselves will drive massive-scale adoption. Another driver may be the ageing cohorts in Asia which already has the countries with the largest numbers of older people (India and China), the regions with the most aged demographics (Hong Kong, Macau, Japan) and the most rapidly ageing countries (Korea and Taiwan).

Smart home technology has matured significantly over the past decade and there is much to learn from the way different technologies are being used successfully in different services and different countries. There is no lack of technology innovations but there is much to be done in learning how to adopt and realise the benefits. It appears many of the Smart Home projects in Australia and overseas are not independently evaluated which can mean that valuable lessons are lost. Care providers are encouraged to partner with some of the many researchers in this field who can assist in finding research grant funds and in distilling the learning to the benefit of all.

7

Limitations of the study

The study had many limitations. It was a convenience study of people attending an aged care event so only people with the capacity and means to attend the event could be included in sampling. The volunteers invited people who came near their booth but had no way of knowing their age, whether they were visitors to the event or participating in another capacity such as an exhibitor, presenter or accompanying family member. The volunteer's booth was near the main entrance so many of the respondees would not have seen the many technologies on display which may account for no-one selecting "other" as technologies they would like to adopt.

Acknowledgements

The researchers acknowledge the support of the National Soft Science Planning (2011GXQ4K029), and National Population and Reproductive Health Science Data Center of National Scientific Data Sharing Platform for Population and Health funded by Ministry of Science and Technology, China; the research volunteers and the participants.


Jin-Peng Qi

Qing Zhang
email: 2qing.zhang@csiro.au

Jie Qi
email: jieqi@dhu.edu.cn

Ying Zhu
email: ying.zhu@hnehealth.nsw.gov.au

A Fast Method for Abrupt Change Detection from Large-Scale Electrocardiogram (ECG) Time Series

Keywords: CP detection, ECG Time series, Large-Scale, Haar Wavelet (HW), Ternary Search Tree (TST)

In previous work, we proposed a promising method, named HWBST, for Change-Point (CP) detection from time series. However, the performance of HWBST is affected partly by the search criteria in terms of Binary Search Tree (BST). In this paper, we propose an improved method for fast CP detection from large-scale ECG time series, based on multi-level Haar Wavelet and Ternary Search Tree (HWTST, for short). In this method, we construct a ternary search tree termed TSTcD from a diagnosed time series by using multi-level HW. Then, we implement fast detection abrupt change from root to leaf nodes in TSTcD, by introducing two search criteria in terms of the data fluctuation in the left, right, and virtual middle branches of TSTcD. Based on the assembled and abnormal ECG samples, we evaluate the proposed HWTST by comparing with HWBST, KS, and T methods. The results show that the proposed HWTST is a faster and more efficient than HWBST, KS and T in terms of the computation time, error, accuracy, and distance of e.c.d.f.

Introduction

Currently, Change-Point (CP) detection has attracted considerable attention in the fields of data mining and statistics. CP detection has been widely studied in many real-world problems, such as atmospheric and financial analysis [START_REF] Bolton | Statistical fraud detection: A review[END_REF], intrusion detection in computer network [START_REF] Yamanishi | On-line unsupervised outlier detection using finite mixtures with discounting learning algorithms[END_REF], signal segmentation in data stream [START_REF] Basseville | Detection of abrupt changes: theory and application[END_REF], as well as fault detection in engineering system [START_REF] Yamanishi | On-line unsupervised outlier detection using finite mixtures with discounting learning algorithms[END_REF][START_REF] Murad | Unsupervised profiling for identifying superimposed fraud[END_REF]. In the past decade, Wavelet Transform (WT), and its revised approaches have emerged as an important mathematical tool for analyzing time series [START_REF] Gustafsson | Adaptive filtering and change detection[END_REF][START_REF] Alarcon-Aquino | Anomaly detection in communication networks using wavelets[END_REF][START_REF] Khalil | Detection and classification of multiple events in piecewise stationary signals: comparison between autoregressive and multiscale approaches[END_REF][START_REF] Kobayashi | Wavelets and their applications in industry[END_REF][START_REF] Percival | Wavelet methods for time series analysis[END_REF][START_REF] Salam | Segmentation of Malay Syllables in connected digit speech using statistical approach[END_REF]. WT is a promising approach for CP detection. It has found applications in anomaly detection, time series prediction, image processing, and noise reduction [START_REF] Alarcon-Aquino | Anomaly detection in communication networks using wavelets[END_REF][START_REF] Salam | Segmentation of Malay Syllables in connected digit speech using statistical approach[END_REF][START_REF] Qi | Kinetic theory approach to modeling of cellular repair mechanisms under genome stress[END_REF][START_REF] Tseng | Segmentation of time series by the clustering and genetic algorithms[END_REF]. WT can represent general functions at different scales and posi-tions in a versatile and sophisticated manner, so the data distribution features can be easily extracted from different time or space scales [START_REF] Tseng | Segmentation of time series by the clustering and genetic algorithms[END_REF][START_REF] Alarcon-Aquino | Change detection in time series using the maximal overlap discrete wavelet transform[END_REF]. As a simple WT, Haar Wavelet (HW), owns some attracting features including fast for implementation and able to analyze the local feature. HW is very useful to find discontinuity and high frequency change in time series, so it is a potential candidate in modern electrical and computer engineering applications, such as signal and image compression, as well as abnormality detection from time series [START_REF] Darkhovski | Nonparametric methods in change-point problems: A general approach and some concrete algorithms[END_REF][START_REF] Walker | A primer on wavelets and their scientific applications[END_REF]. Previously, we proposed a HWBST method for fast CP detection [START_REF] Qi | A Fast Method for Change Point Detection from time series Based on Haar Wavelet and Binary Search Tree (HWBST)[END_REF]. HWBST is a promising method for detecting abrupt change from large-scale time series. However, the performance of HWBST is affected partly by binary search criteria, especially when abrupt change occurs near the middle boundary of BST. To resolve this problem, in this paper, we propose an improved method for fast CP detection from largescale time series, named HWTST, based on multi-level HW and ternary search tree. In the proposed method, a ternary search tree (TST), named TSTcD is built based on a binary search tree, TcD derived from a diagnosed time series, by adding a virtual middle sub-tree; and then abrupt change is detected from TSTcD in terms of two search criteria. To evaluate the proposed method, we apply the HWTST, HWBST, KS, and T to detect abrupt change from both the assembled and the abnormal ECG samples. The detailed HWTST method is implemented as follows.

Method

Definition and assumption [16]

Suppose } ,...,

{ 1 N z z Z  is a diagnosed time series, we observe , ,..., 1 , ) / ( N i X n i f Z    (1)
where

N i i x X ,..., 1 } {  
are discrete and centred i.i.d. random variables, and f is a noisy mean signal with unknown distribution.

Definition 1: We define the data fluctuation between two adjacent segments in Z as,

| 1 1 | sup ) ( 1 , 1          b c R R c a L L N R L mn z n z m c D , (2) where
} , { R L Z Z Z  , } ,..., { c a L z z Z  , } ,..., { 1 b c R z z Z  
, and

a c m   , 1    c b n , and N n m   . If a change point c occurs in Z, there exists a value c satisfies   ) ( D mn c , ] , [ 1 N c z z z 
, and R   .

Hypotheses:

(1) 0

Η : if   ) (c D mn , no abrupt change occurs in Z. (2) 1 Η : if   ) (c D mn , abrupt change occurs in Z.
where R   is a threshold of data fluctuation in a time series Z within an identical distribution. We wish to test 0 Η against 1 Η from observations. Thereafter, we as- sume that the number, the location, and the size of the function f are unknown. However, the upper bound of data fluctuation  is supposed to be known.

Multi-level HW

Generally, as shown in Fig. 1, by using multi-level HW, a discrete time-series signal Z={z 1 , z 2 ,…, z N }, can be decomposed into the k th -level trend cA k , and k level fluctuations, i.e., cD 1 , cD 2 ,..., cD k , k=1, 2, ..,

N 2 log . The k-level HW is the mapping H k defined by [8], ) cD cD ... cD cD cA ( Z 1 2 1    k k k H k , (3)
Fig.

                                        1 , N 0, j k, k,1 N/2 1, 1,1. 0,
M M k                                         1 , N 0, j k, k,1 N/2 1, 1,1. 0,
z z z Z   , N og M k 2 l 0    , and k N j 2 / 1   .

Overview of HWTST method

The scheme of integrated HWTST method (Fig. 2) is composed of three parts. First, a ternary search tree, TSTcD, is constructed from a diagnosed time-series Z by multilevel HW method. Second, abrupt CP is detected from root to leaf nodes in TSTcD, in

cA 2 cA 3 cA k-1 cA k cD 1 cD 3 cD 2 cD k-1 cD k cA 1 … … Z
terms of two search criteria. Last, the proposed method is evaluated by comparing with HWBST, KS, and T methods.

Construction of TSTcD

First, we build a binary tree TcD, in terms of McD. As shown in Fig. 3, we deal the element cD k,j in McD as the root, the other elements as non-leaf left and right child nodes, and the original Z= {z 1 , z 2 ,…, z N } as N leaf nodes, respectively. Then, a virtual middle-child node termed cD k,j;M is added into non-leaf parent node cD k,j in TSTcA.

CP Detection from TSTcD

Definition 2: Suppose the current non-leaf node j k, cD is selected in TSTcD, with its left, virtual middle, and right child non-leaf node, namely

L : j k, cD , M : j k, cD ,
) ( ) 1 ( )2 ( 1 cD 1 L : j k, ; ,          c aM R R aM a L L L j k z z k D , ( 16
)
CP detection from TSTcD in terms of Criterion 2.

Evaluation for HWTST

End CP detection from TSTcD in terms of Criterion 1.

Leaf node? Y

A Diagnosed Z TSTcD Construction Fig. 3. The scheme of TSTcD construction, the virtual non-leaf middle-child node is added.

) ( ) 1 ( )2 ( 1 cD 1 1 R : j k, ; ,           b bM R R bM c L L R j k z z k D , ( 17) ) ( ) 1 ( )2 ( 1 cD 1
M : j k, ; ,          bM c R R c aM L L M j k z z k D , (18) where 1 ) 1
( 2    j a k , j b k   2 , and ) 1 ( 2 ) 1 ( 2 
   k k j c ; 1 2 ) 2 2 ( 2 2 1       k k j aM
, and

2 1 2 ) 1 2 ( 2      k k j bM ; k N j 2 / 1  
, and

N k 2 log 2  
. Thereafter, we can introduce the first search criterion in terms of the data fluctuation defined above.

Criterion 1: Suppose the current non-leaf node j k, cD is selected in TSTcD,

N k 2 log 2   , (a) If ) ) , , (max( ;
, ; , ; , ; , L j k M j k R j k L j k D D D D 
holds true, then the left-child node

L : j k, cD in
TSTcD, is selected to be involved into the current search path;

(b) If ) ) , , (max( ;
, ; , ; , ; , R j k M j k R j k L j k D D D D  holds true, then the right-child node R : j k, cD in
TSTcD, is selected to be involved into the current search path;

(c) If ) ) , , (max( ;
, ; , ; , ; , M j k M j k R j k L j k D D D D 
holds true, then the virtual middle-child node

M : j k, cD
in TSTcD, is selected to be involved into the current search path.

In addition, we introduce another criterion to deal with the last leaf node in TSTcD, and then decide whether the selected leaf node is the potential CP or not. We define the second search criterion in terms of the data fluctuation in the last leaf node level as follows.

Criterion 2: Suppose the current selected non-leaf node is Based on two search criteria above, a fast CP detection is implemented, and then an estimated CP can be detected from root to leaf-nodes in TSTcD.

j k, cD , 1  k ,

Results

To verify the performance of the proposed method further, we apply HWKS, and KS, HW, and T methods, to detect abrupt change from ECG time series provided by Phys-ioBank. In ECG experiments, we design the diagnosed ECG samples from different ECG datasets, including the MIT-BIH Normal Sinus Rhythm Database (NSRDB) [START_REF] Goldberger | Physiobank, physiotoolkit, and physionet components of a new research resource for complex physiologic signals[END_REF], MIT-BIH Noise Stress Test Database (NSTDB) [START_REF] Moody | A noise stress test for arrhythmia detectors[END_REF], and MIT-BIH Malignant Ventricular Arrhythmia Database (MVADB) [START_REF] Sd | Development and analysis of a ventricular fibrillation detector[END_REF] .

CP detection from assembled ECG samples

First, we select a normal ECG dataset, 16265m from NSRDB, and an abnormal ECG dataset, 118e00m from NSTDB. Specifically, we take the normal ECG segment of size m as X m , and the abnormal segment of size n as Y n , respectively, and then assemble the diagnosed ECG sample Z={Xm , Yn}={x In this assembled ECG experiments, the results of CP detection illustrated in Fig. 2, and Table 1 show that, the proposed HWTST can estimate CP position efficiently, and then distinguish the normal and abnormal segments from the assembled ECG samples with faster, smaller error and higher accuracy than HWBST, KS, and T. For HWBST, although faster than KS, and T, it has the biggest error and the lowest accuracy in all four methods. For KS, although slightly bigger error than T, it is faster than T, and has smaller error and higher accuracy than HWBST. For T, it has smaller error and higher accuracy than HWBST, whereas, it needs the longest computation time in all methods. These results indicate the proposed HWTST is more sensitive and efficient than HWBST, for CP detection at the middle boundary. Especially, it has the shortest computation time, the smallest error, and the highest accuracy in all four methods.

CP Detection from abnormal ECG time series

To verify the performance of the proposed method further, we apply HWTST, HWBST, KS, and T to analyze the abnormal ECG time series directly. In this part, we select the abnormal ECG segment from 615m in the MVADB, i.e., Z={Y n }={y 1 ,…, y n }, as a diagnosed ECG sample. To some extent, the distance of e.c.d.f can partly reflect the statistic fluctuation. Therefore, we take this variable as an indicator of the data fluctuation between two adjacent ECG segments divided by the estimated CP (e-CP) position. The selected results of CP detection are plotted in Fig. 2, and the results for all abnormal ECG samples, including the e-CP position, computation time, and the variance of e.c.d.f are summarized in Table 2.

For abnormal ECG samples Z1-Z6 of size N from 2^10 to 2^15, the results show that the proposed HWTST can detect the abrupt change position, and then divide the original ECG sample into two adjacent parts, with the shortest computation time in four methods; and it has bigger distance of e.c.d.f than HWBST, and T methods. For HWBST, although faster than KS, and T, it has the smallest variance of e.c.d.f in all four methods. For KS, it can detect CP with the maximal distance of e.c.d.f, whereas, it needs longer computation time than HWTST, HWBST, especially when ECG sample size is bigger. For T, it needs the longest averaged computation time in all four methods, although it has bigger variance of e.c.d.f than HWBST. These results show that HWTST can capture abrupt change position from the diagnosed ECG samples more quickly and efficiently than HWBST, KS, and T. On the other hand, the detected CP is very useful to find a critical time from the diagnosed ECG time series, where a patient might encounter an important conversion between two different states of health. Therefore, HWTST is very meaningful for inspecting and diagnosing different states of health from diagnosed ECG time series more quickly and efficiently. 1.17 1.17 1.17

Conclusion

In this paper, based on multi-level HW and ternary search tree, an improved method, named HWTST, is proposed for fast CP detection from large-scale ECG time series.

In the proposed HWTST method, a ternary search tree, TSTcD, is built by adding a virtual middle-child sub-tree into TcD, which is derived from a diagnosed time series Z; and two search criteria are defined in terms of the data fluctuation in TSTcD. Then, an abrupt change is detected from root to leaf nodes of TSTcD in terms of two search criteria. Comparing with previous HWBST, KS, and T methods, the results show that the proposed HWTST is more efficient for fast detection CP from large-scale ECG time series, due to the shortest computation time, the smallest error, the highest accuracy in all four methods, and bigger variance of e.c.d.f than HWBST and T. In addition, HWTST has better performance than HWBST, especially when abrupt change occurs near the middle boundary.

Fig. 2 .

 2 Fig. 2. The scheme of the integrated HWTST framework, it includes three parts: TSTcD construction, CP detection from TSTcD in terms of two ternary search criteria, and evaluation for HWTST method.

  and

  measure the data fluctuation in different segments of Z, three statistic variables,

Fig. 1 .

 1 Fig. 1. The results of CP detection from the assembled ECG time series Z1-Z4. (A1)-(A4) the assembled Z1-Z4; (B1)-(B4),(C1)-(C4) ,(D1)-(D4), and (E1)-(E4) the e-CP detected from Z1-Z4, by HWTST, HWBST, KS, and T, respectively; (F1)-(F4) the diagram analysis for the computation time, (G1)-(G4) the error of e-CP, and (H1)-(H4) the accuracy for HWTST, HWBST, KS, and T, respectively. In histograms (F)-(H), '1', '2', '3', and '4' stands for HWTST, HWBST, KS, and T, respectively.

Fig. 2 .

 2 Fig. 2. The results of CP detection from abnormal ECG time series of size for 2^10 to 2^15. (A1)-(A6) the abnormal ECG sample Z1-Z6; (B1)-(B6), (C1)-(C6), (D1)-(D6), (E1)-(E6) the e.c.d.f derived from two adjacent ECG segments in Z1-Z6, by HWTST, HWBST, KS, and T, respectively; (F1)-(F6) the diagram analysis of the distance of e.c.d.f, and (G1)-(G6) the computation time of HWKS, KS, HW, and T in Z1-Z6, respectively. In histograms (F)-(H), '1', '2', '3', and '4' stands for HWTST, HWBST, KS, and T, respectively.

Table 1 .

 1 The results of CP detection from the assembled ECG samples.

	Z	Size, N	2^7	2^8	2^9	2^10	2^11	2^12	2^13	2^14
	M	CP, k	2^6	2^7	2^8	2^9	2^10	2^11	2^12	2^13	Mean
		HWTST	.0050	.0060	.0060	.0060	.0060	.0060	.0070	.0090	.0063
	Time	HWBST	.0060	.0060	.0070	.0080	.0080	.0100	.0140	.0240	.0103
		KS	.0100	.0130	.0200	.0440	.0119	.3910	1.420	5.431	.9176
		T	.0300	.0450	.0740	.1390	.2870	.6750	1.653	4.461	.9205
		HWTST	9	8	8	8	31	8	8	8	11
	Error	T	63	63	15	1	1	1	1	1	18
		KS	15	15	15	15	15	90	52	70	36
		HWBST	62	4	70	198	988	1194	388	8074	1372
		HWTST	.9297	.9688	.9844	.9922	.9849	.9980	.9990	.9995	.9821
	Accuracy	KS	.8828	.9414	.9707	.9854	.9927	.9780	.9937	.9957	.9675
		T	.5078	.7539	.9707	.9990	.9995	.9998	.9999	.9999	.9038
		HWBST	.5156	.9844	.8633	.8066	.5176	.7085	.9526	.5072	.7320

Table 2 .

 2 The results of CP detection from the abnormal ECG samples.

	Z	Size, N	2^10	2^11	2^12	2^13	2^14	2^15	Mean
	M
		HWTST	630	1478	3448	1520	9503	22640	NA
	e-CP	HWBST	614	1437	3804	1863	16167	27054	NA
		KS	813	1153	3237	2164	8610	22361	NA
		T	66	65	4036	8190	1	1	NA
		HWTST	.0060	.0060	.0070	.0060	.0090	.0140	.0080
	Time	HWBST	.0080	.0090	.0100	.0140	.0200	.0350	.0160
		KS	.0430	.1320	.4100	1.409	5.294	20.46	4.625
		T	.1450	.3170	.7440	1.855	4.685	13.02	3.461
		KS	.6260	.4919	.4991	.3456	.1909	.1632	.3861
	Variance	HWTST	.1944	.3750	.2916	.1941	.2475	.1297	.2387
	of e.c.d.f	T	.6770	.5811	.0079	0	0	0	.2110
		HWBST	.0983	.3249	.1786	.1616	.0496	.0162	.1382

Acknowledgment: I would like to thank my supervisor Prof. Qing. Zhang and Prof. Mohan Karunanithi in the Australia E-Health Research Centre for their assistances, supports and advices for this paper. This paper is supported by National Natural Science Foundation of China (No.61104154), and the Fundamental Research Funds for the Central Universities.