Patricia Mesa-Gresa

Jose A Lozano
email: jlozano@labhuman.i3bh.es

Roberto Llórens
email: rllorens@labhuman.i3bh.es

María Mariano Alcañiz
email: malcaniz@labhuman.i3bh.es

Dolores Navarro

Enrique Noé

María Dolores Navarro

Clinical Validation of a Virtual Environment Test for Safe Street Crossing in the Assessment of Acquired Brain Injury Patients with and without Neglect

Keywords: Acquired brain injury, unilateral spatial neglect, pencil-and-paper tests, cognitive assessment, virtual reality, rehabilitation

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

The term 'Acquired Brain Injury' (ABI) refers to a normally developed brain that is damaged afterward. The causes can be diverse, including brain trauma, ischemic or hemorrhagic stroke, brain tumors, anoxia, etc. [START_REF] Ríos-Lago | Neurophychology of Acquired Brain Injury[END_REF] [START_REF] Rose | Virtual Reality in Brain Damage Rehabilitation: Review[END_REF]. The main consequences of ABI involve the loss of brain functions that are related to the motor and cognitive systems as well as the loss of communication skills and emotional and behavioral regulation. There is also an important number of patients that currently have a long-term or lifelong need for help to perform activities of daily living (ADL) [START_REF] Ríos-Lago | Neurophychology of Acquired Brain Injury[END_REF] [START_REF] Rose | Virtual Reality in Brain Damage Rehabilitation: Review[END_REF]. Brain injured patients may suffer cognitive difficulties such as problems with attention, memory, concentration, and executive functions (planning, judging, reasoning, etc.). Taking this heterogeneity of symptoms into account is essential to be able to carry out a proper assessment of the disease in order to ensure the success of the treatment.

Unilateral Spatial Neglect (USN) is a frequent disorder that is detected after brain damage [START_REF] Ríos-Lago | Neurophychology of Acquired Brain Injury[END_REF]. The main feature of USN is the inability of patients to pay attention to stimuli located on the contralateral side of injury, and these symptoms are not related to sensorial or motor deficits [3][4]. This alteration may have important functional consequences for patients in their daily lives that make recovery more arduous. Patients who suffer symptoms usually fail to attend to their left/right side thereby disturbing their personal space (for example, shaving only half of their face), peripersonal space (reading one side of the two pages of a newspaper), and extrapersonal space (bumping into objects when walking) [START_REF] Ting | Visual Neglect Following Stroke: Current Concepts and Future Focus[END_REF]. The complexity and heterogeneity of the symptoms of USN cause a lack of consensus on suitable tools for evaluation and treatment [START_REF] Tsirlin | Uses of Virtual Reality for Diagnosis, Rehabilitation and Study of Unilateral Spatial Neglect: Review and Analysis[END_REF]. Although many cases of USN can be detected by observation, certain specific diagnoses require a specific evaluation to measure the severity of symptoms and possible progression. Traditional tools for assessment are based on pencil-and-paper tests as well as behavioral batteries [START_REF] Ting | Visual Neglect Following Stroke: Current Concepts and Future Focus[END_REF] [START_REF]Neurophychological Tests[END_REF]. The effectiveness of evaluation tests of this kind have been proved, although there are some limitations that must be taken into account such as the difficulty of interpreting the results, the extrapolation of results to daily life tasks, the difficulty of differentiating between sensory deficits, the lack of attention that is typical of USN, and the absence of assessment of changes in personal space [START_REF] Tsirlin | Uses of Virtual Reality for Diagnosis, Rehabilitation and Study of Unilateral Spatial Neglect: Review and Analysis[END_REF] [START_REF] Ting | Visual Neglect Following Stroke: Current Concepts and Future Focus[END_REF].

In the last few decades, new procedures using virtual reality (VR) technologies have emerged. VR is a new technology based on computerized-generated stimulation that immerses the user in a realistic 3D world with multisensory stimuli and that offers the possibility to interact with the elements and receive feedback [START_REF] Tsirlin | Uses of Virtual Reality for Diagnosis, Rehabilitation and Study of Unilateral Spatial Neglect: Review and Analysis[END_REF] [7][8]. This technology, which has demonstrated its validity in the area of neuropsychology [START_REF] Rose | Virtual Reality in Brain Damage Rehabilitation: Review[END_REF], can overcome some of the limitations of traditional evaluation methods. The main advantages of using VR are that it permits the evaluation and treatment in a realistic environment that is related to daily life and that is safer and has intrinsic ecological validity [START_REF] Ting | Visual Neglect Following Stroke: Current Concepts and Future Focus[END_REF] [START_REF] Katz | Interactive Virtual Environment Training for Safe Street Crossing of Right Hemisphere Stroke Patients with Unilateral Spatial Neglect[END_REF]. VR can generate different environments that allow more interaction and sense of presence and that improve the motivation of the users while enabling a precise control of each session to be maintained [START_REF] Peñasco-Martín | Application of Virtual Reality in the Motor Aspects of Neurorehabilitation[END_REF]. In the same way, the performance of the subjects can be recorded from different measuring procedures, which allows for individualized and adapted sessions in accordance with the limitations of the subject and/or the previous results obtained by the VR system [START_REF] Katz | Interactive Virtual Environment Training for Safe Street Crossing of Right Hemisphere Stroke Patients with Unilateral Spatial Neglect[END_REF] [START_REF] Peñasco-Martín | Application of Virtual Reality in the Motor Aspects of Neurorehabilitation[END_REF]. In the case of the assessment of USN, the use of visual trackers by VR systems enables the eye movements of patients and their visual search pattern to be evaluated, which is important in learning more about the characteristics of this disease [START_REF] Ting | Visual Neglect Following Stroke: Current Concepts and Future Focus[END_REF].

In recent years, several studies have initiated the application of VR systems as an evaluation tool for neuropsychological disorders. Some studies have carried out virtual versions of the classic pencil-and-paper tests. Fordell et al. [START_REF] Fordell | A Virtual Reality Test Battery for Assessment and Screenig of Spatial Neglect[END_REF] designed the VR-DiSTRO system which consists of a VR-test battery based on conventional tests for USN evaluation. The main results obtained in this study showed a high sensitivity of the VR system in detecting cases of neglect and a high level of agreement between measures of conventional tests and those obtained by the VR-DiSTRO. In another study [START_REF] Broeren | Neglect Assessment as an Aplication of Virtual Reality[END_REF], a semi-immersive work bench with stereoscopic glasses and a haptic device were used with a virtual version of the cancellation test. In this study, the results revealed that negligent and recovered patients showed irregular exploration performance in the VR task, with the VR system being more instructive than the conventional test. However, other VR systems include innovative diagnostic tasks. Dvorkin and colleagues [START_REF] Dvorkin | Assessment and Monitoring of Recovery of Spatial Neglect within a Virtual Environment[END_REF] designed a Virtual Environment for Spatial Neglect Assessment application consisted of a 3D room-shape where patients had to respond when they detected a target (balls). The results indicated the sensitivity of the VR system for differentiating between negligent patients and control subjects, even though the similarity between the results of the VR system and a traditional test was less conclusive. More recently, Kim et al. [START_REF] Kim | Assessment of Post-stroke Extrapersonal Neglect Using a Three-Dimensional Immersive Virtual Street Crossing Program[END_REF] examined the efficiency of a 3D immersive virtual street crossing program for the assessment of post-stroke patients [START_REF] Katz | Interactive Virtual Environment Training for Safe Street Crossing of Right Hemisphere Stroke Patients with Unilateral Spatial Neglect[END_REF][13]. The VR system consisted in a real street crossing that could evaluate extrapersonal space in patients and showed significant differences between negligent and non-negligent patients.

A previous study by Navarro et al. [START_REF] Navarro | Preliminary Validation of Ecotrain-Cognitive: A Virtual Environment Task for Safe Street Crossing in Acquired Brain Injury Patients with and without Unilateral Spatial Neglect[END_REF] has demonstrated that our VR Street Crossing Test (VRSCT) is perceived by the patients as being a usable and satisfactory system in the rehabilitation of ABI and USN. Therefore, the main objective of our study is to evaluate the validity of the VRSCT system in terms of cognitive assessment. More specifically, the study compares the scores obtained from patients with ABI (with and without neglect) between different pencil-and-paper tests of attention and the measures found in the VRSCT system. Finally, we have tried to verify the sensitivity of our VR system as a complementary tool in neuropsychological assessment of attentional deficits in patients with ABI and with the diagnosis of USN.

Materials and Methods

Subjects. The participants of this study included twenty-five patients, 14 men and 11 women, aged 51.2 ± 12.62 years (mean ± standard deviation or SD), with a mean chronicity of 505.42 days (SD: 335.11) and a mean of 11.84 years of education (SD:4.22). All the participants had sustained either a right or a left hemispheric brain lesion due to an ABI (hemorrhagic stroke: n=12, ischemic stroke: n=10, brain tumor: n=3). The participants in this study were selected based on their scores on the Mini-Mental State Examination test (MMSE), which is a brief assessment of cognitive abilities, and an adapted version of the Mississipi Aphasia Screening Test (MAST), which evaluates comprehension of orders. All the subjects had a score greater than or equal to 24 on the MMSE and greater than or equal to 45 on the MAST. Therefore, participants had a cognitive level and proper comprehension to be able to handle the software.

VRSCT system. The VRSCT system simulates a typical city with its buildings, streets, cars, crosswalks, traffic lights, etc. In this environment, the objective of the patient is to go to a specific place in order to confront these adverse elements. This virtual environment is programmed to offer the therapist the possibility to configure it according to the difficulty level that is most appropriate for the patient. In order to offer the patient the virtual experience in an immersive way, we decided to use a conventional panoramic 47" LCD monitor, and a conventional 5.1 surround sound system. In order to interact with the virtual environment in an easy, intuitive and noninvasive way, we offered the patient two wireless devices: a conventional joystick for navigation and interaction, and an optical tracking system (TRACKIR, a product of NaturalPoint Company) to be able to track the patient's head movements. This last aspect is very important in the rehabilitation of neglect patients because they must get used to moving their heads to the neglect side of the space. The patient uses a cap that has three reflecting marks. The position and orientation of these marks are captured by a USB infrared camera that is placed in a panoramic LCD monitor. The device allows the patient to link his/her head movements in 3D space to the movement of the point of reference in the virtual environment. The device also allows these movements to be configured, for instance, linking small head-movements of the patient in 3D space to magnify the point of reference of movements in the virtual environment; this creates a panoramic view of the virtual environment of up to 180º.

In the experiment, the patients were placed in a quiet room where they sat at a table in front of a widescreen monitor. A therapist trained in the virtual system was in the same room with the patient to give specific instructions about the assessment task and the software and to control the process. First, the patients received instructions on the use of the program. Then, the head tracking system was adjusted for each patient and a training session was administered to practice with the software and the hardware. For this training session, the patient had to navigate through the virtual streets and complete a single route without traffic or any other distractor. Once the patient had undergone the training session successfully, the assessment session began. The main goal of this session was to cross two-way roads in order to arrive at a destination point, a supermarket, and then return to the start point as quickly and as safely as possible. When an accident occurred, the patient received emotionally-intense audiovisual feedback (for example, sound of a car horn) and new instructions from the therapist. In this case, the program was automatically restarted from the initial point, without discounting the time already consumed. Taking into account previous studies, the session was considered completed when the patient performed two complete routes (each included arriving to the supermarket and getting back to the starting point) without more than four accidents. Therefore, when the patient did less than two complete routes or had more than four accidents, the patient was considered to have failed the task. The measures evaluated during the assessment session were the following: the number of times the participant looked to the left and to the right, the total time needed to finalized the task, the total number of accidents, and the completion/non-completion of the task (See Figure 1). Instruments. The pencil-and-paper tests used in the study are described below. The Behavioral Inattention Test (BIT) is a behavioral test battery that is designed to evaluate USN. It is composed of 15 subtests, 9 of which evaluate aspects of daily life and 6 of which are traditional tasks that assess neglect. The subtests of daily living are assessed by tasks like tracing line drawings, dialing, reading a menu, reading an article, telling and setting the time, choosing currencies, copying statements and addresses, map orientation and choosing cards. The evaluation of neglect on these tests consists of letter cancellation, star cancellation, a copying figures and shapes, line bisection and representative drawing [START_REF]Neurophychological Tests[END_REF]. To determine the presence of USN, the BIT scores were used taking the score of 129 as the cut-off. Based on the scores obtained by the participants and the normative scales of the test, the subjects were classified as "Negligent subjects" if the score was less than or equal to 129, and "Non-negligent subjects" if the score was greater than 129. The second test used was the Color Trail Making Test (CTT). This is a behavioral test that is based on the evaluation of sustained visual attention, mental flexibility, sequencing, visual tracking, and graphomotor ability. The CTT is a color version of the Trail Making Test. This test has two different parts: 1) Part A: the subject must connect the 25 numbers that are randomly distributed on a sheet with consecutive lines; and 2) Part B: There are 25 duplicate numbers within circles of different colors in which the subject must connect consecutive numbers with lines while at the same time alternating colors. The variable evaluated in this test is time (seconds) to perform each of the parts. Finally, the Conners' Continuous Performance Test-II (CPT-II) is a computerized test that evaluates the sustained attention of the subject and the ability to inhibit inappropriate responses. In this test, the subjects must press a key when they detect letters other than the letter 'X'. The assessment contains 6 blocks that vary in the rate of submission of the letters. After testing, the program generates an automated report that includes data on various variables such as the number of omissions (letters that the subject did not mark), number of commissions (times that subject marked 'X'), reaction time (HIT Rt), and the capacity to adapt to the temporary demands of the task (HIT Rt ISI).

Procedure. All the patients were classified and selected based on their scores on the MMSE and the MAST. Once the 25 patients who participated in the study were selected, a cognitive evaluation was performed prior to using the VRSCT system. The cognitive assessment, which consisted of BIT, CTT, and CPT-II, was conducted during the same week as the virtual training. Then, evaluation and training with the VRSCT were initiated. The virtual test consisted of a preliminary training session and an evaluation session based on the task explained above. The training session took approximately 10 minutes and the evaluation session lasted until the patient finished the task and/or the patient was considered to have failed the task.

Data analyses.

All statistical analyses were performed by SPSS 17.0 for Windows. The Pearson parametric correlation was used to analyse the BIT scores that classified patients as negligent or non-negligent in relation to the total time for the completion of the task in the assessment session of the virtual program and the number of accidents. The Pearson parametric correlation for continuous variables was used to measure the numerical scores obtained on tests of attention assessment (CTT and CPT-II) by non-negligent subjects that were related to the variables obtained by the VRSCT (total time to finalize the task and the number of accidents). The measures evaluated during the assessment session on the VRSCT were compared between negligent and non-negligent patients using the Mann-Whitney U-test. All the data are presented as mean±SD. In all cases, the significance levels were set at p<0.05.

Results

Correlation between the BIT and the VRSCT system with negligent and nonnegligent patients. According to the BIT scores, five of the twenty-five patients were classified as negligent subjects. The results obtained for non-negligent subjects (n=20) showed a negative correlation that is statistically significant between the score obtained on the BIT and the total time needed to finalize the VRSCT (r 2 = -0.507, p<0.05) and the total number of accidents (r 2 = -0.515, p<0.05) (See Table 1 and Figure 2 a). None of the VRSCT measures were significantly correlated with the BIT score in negligent subjects.

Correlation between the conventional test for assessing attention (CTT and CPT-II) and the VRSCT system with non-negligent patients. On the CTT, scores obtained by non-negligent patients in part A (r 2 = 0.802, p<0.001) and part B (r 2 = 0.506, p<0.05) correlated significantly with the total time needed to finalize the VRSCT (See Figure 2 b). On the CPT-II test, only the significant correlation was between the HIT Rt ISI variable of the test and the total time needed to complete the task of the VRSCT (r 2 = 0.613, p<0.01). Other measures obtained with the CPT-II test (omissions, commissions, and HIT Rt) did not reach a significant correlation with the variables of the VRSCT. Comparison of negligent and non-negligent patients' performances on the VRSCT. The total number of accidents registered in the VRSCT was significantly higher in negligent patients than in non-negligent patients (U=17.000, p<0.05). Non-negligent patients showed a lower number of accidents (3.00±1.41) than the negligent patients (1.15±1.27). However, the total time needed to finalize the task in the VRSCT did not reach statistical significance between negligent and non-negligent patients (p=0.734).

Discussion

In this study, we evaluated the validity of VRSCT for the assessment of both negligent and non-negligent ABI patients. The results of the study showed that the VRSCT system was effective in terms of cognitive assessment. The measures obtained by the VRSCT system correlated with BIT score for non-negligent patients. More specifically, subjects that showed a lower score on the BIT spent more time completing the VRSCT task and had a higher number of accidents. However, with regard to the negligent patients, the results showed no significant correlation with the BIT data. Despite these result, the relationship between the scores of the BIT test and the VRSCT system in non-negligent patients may indicate that the virtual system measurements could be sensitive to the subject's attentional capacities. Future studies could make a more accurate comparison between the two types of diagnoses (i.e., traditional vs. VRSCT), by taking into account the subtasks of the BIT and expanding the measures assessed by the virtual system such as reaction time or time required for specific task performance.

The results also show that the VRSCT system has a positive correlation in nonnegligent patients with other traditional tests used to assess attention. More precisely, patients who took less time to solve the CTT and presented higher capacity to adapt to the temporary demands of the tasks of CPT-II had fewer accidents and spent less time completing the task in the VRSCT.

With respect to differences in the implementation of the VRSCT between negligent and non-negligent patients, the VRSCT showed significant differences in the measure of total number of accidents. The results show that the negligent patients had a higher number of accidents than non-negligent patients. Moreover, the system requirements to complete the task can evaluate the capacity of the patient to have an appropriate emotional response to the dangerous stimuli in daily life as well as the capacity of the patient to have an adequate reaction time. These pilot results indicate that the VRSCT can be used as a complementary tool for the diagnosis of patients with ABI affected by USN. We hope that this study is a first step in the construction of a complete platform for diagnosis and rehabilitation of ABI. Indeed, future studies and the implementation of improvements would allow the VRCST system to respond to the needs of both patients and therapists.

Figure 1 .

 1 Figure 1. Overview of the VRSCT and description of traking system.

Figure 2 .

 2 Figure 2. (a) Correlation between the BIT scores and the total time needed to finalize the VRSCT in non-negligent patients. (b) Correlation between CTT-A scores and the total time needed to finalize the VRSCT in non-negligent patients.

Table 1 .

 1 Correlation between the pencil-and-paper tests (BIT, CTT and CPT-II) and the variables of VRSCT for negligent and non-negligent subjects.

			BIT	CTT-A	CTT-B	CPT HIT Rt ISI
		Negligent	Non-negligent	Non-negligent	Non-negligent	Non-negligent
	VR System	subjects	subjects	subjects	subjects	subjects
	Total time (sec)	0.704	-0.507*	0.802**	0.506*	0.613**
	Number of accidents	-0.231	-0.515*	0.243	0.429	0.151
	*p<0.05; **p<0.01

Acknowledgments. This study was funded by Ministerio de Educación y Ciencia Spain, Project Game Teen (TIN2010-20187) projects Consolider-C (SEJ2006-14301/PSIC), "CIBER of Physiopathology of Obesity and Nutrition, an initiative of ISCIII" and Excellence Research Program PROMETEO (Generalitat Valenciana. Conselleria de Educación, 2008-157).


Topi Kaaresoja
email: topi.kaaresoja@nokia.com

Eve Hoggan
email: eve.hoggan@helsinki.fi

Emilia Anttila
email: emilia.anttila@nokia.com

Playing with Tactile Feedback Latency in Touchscreen Interaction: Two Approaches

Keywords: Touchscreen, latency, tactile feedback, weight

A great deal of research has investigated the potential parameters of tactile feedback for virtual buttons. However, these studies do not take the possible effects of feedback latencies into account. Therefore, this research investigates the impact of tactile feedback delays on touchscreen keyboard usage. The first experiment investigated four tactile feedback delay conditions during a number entry task. The results showed that keypads with a constant delay (18 ms) and the smallest feedback delay variation were faster to use and produced less errors compared to conditions with wider delay variability. The experiment also produced an unexpected finding -users seemed to perceive buttons with longer delays as heavier, with a need for greater force when pressing. Therefore another experiment was conducted to investigate this phenomenon. Seven delay conditions were tested using a magnitude estimation method. The results indicate that using different latencies can be used to represent tactile weight in touchscreen interaction.

Introduction

Nowadays, many devices in different product domains support multimodal interaction. For example, touchscreen mobile phones now provide not only visual feedback but also auditory and haptic responses to user input. Despite the fact the microprocessors are becoming increasingly fast, operating systems and applications are more complex thus placing higher demands on the processors. This can lead to latency and latency variation in interaction. The research described in this paper focuses on different aspects of tactile latency in touchscreen interaction.

In the area of HCI research, latency is traditionally viewed as being harmful to interaction due to its potentially disruptive effect on usability and the user experience [START_REF] Wright | Audio and Gesture Latency Measurements on Linux and OSX[END_REF][START_REF] He | Video-Based Measurement of System Latency[END_REF][START_REF] Mine | Characterization of End-to-End Delays in Head-Mounted Display Systems[END_REF]. However, previous psychophysical latency research indicates that stimuli from different modalities must appear asynchronously to be perceived as simultaneous [START_REF] Zampini | Audiotactile temporal order judgements[END_REF][START_REF] Zampini | Audiovisual temporal order judgements[END_REF][START_REF] Lee | Spatiotemporal Visuotactile Interaction[END_REF]. Therefore, in some cases, latency must be intentionally introduced into feedback. Our previous work introduce these latency issues more in detail [START_REF] Kaaresoja | Feedback is… Late: Measuring Multimodal Delays in Mobile Device Touchscreen Interaction[END_REF][START_REF] Kaaresoja | The Effect of Tactile Feedback Latency in Touchscreen Interaction[END_REF]. This paper will address the following questions: How do constant and variable tactile feedback latencies affect performance and perceived pleasantness? How does audio feedback inherently part of the tactile feedback affect the perception of tactile feedback latencies? It must also be noted that certain perceptual consequences, such as illusions, may occur when latency is introduced to tactile feedback. Therefore, our final research question asks whether illusions created through latency can be used as a design parameter for an interface when carefully selected and controlled.

This paper reports the results of two experiments focusing on tactile latency. The first experiment investigated four different tactile feedback delay variation conditions during a number entry task on a touchscreen keypad. The second experiment was conducted to test seven different delay conditions for virtual buttons using a magnitude estimation method. This experiment was used to determine whether using different latencies can be an effective way in which to represent tactile weight as a parameter in touchscreen interaction.

Background Work

The following section will briefly describe some of the existing research in the areas of tactile feedback for touchscreens and latency tolerance in relation to this work.

Touchscreens with Tactile Feedback

Recent research has mainly focused on the technology used to provide the tactile feedback from touchscreens on mobile devices and also on the advantages of augmenting visual displays with an additional modality through which information can be transmitted.

Poupyrev et al. [START_REF] Poupyrev | Ambient Touch: Designing Tactile Interfaces for Handheld Devices[END_REF] introduce tactile feedback for ,mobile touchscreen devices. They embedded TouchEngine, a thin, miniature low-power tactile actuator in a PDA. The actuator was designed specifically for use in mobile interfaces, and it is a piezoelectric actuator that bends when a signal is applied. In this case, Poupyrev et al. used the tactile feedback as an ambient background channel of information for several applications. They conducted a formal user study into the use of tactile feedback with tilting devices, for example. Participants were required to scroll through a text list using gestures. The results of the study showed that, on average, participants could complete the tasks 22% faster when provided with tactile feedback.

Nashel and Razzaque [START_REF] Nashel | Tactile Virtual Buttons for Mobile Devices[END_REF] added tactile cues simulating real buttons to virtual buttons displayed on mobile devices with touch screens. As the user"s finger moves over a virtual button: a "pop" is presented as the finger enters a button region; a low amplitude vibration is presented when the finger pushes the button; a short pulse is presented as the finger leaves the button area and no feedback when the finger is between buttons. The experiments conducted found that all participants were able to differentiate between vibration (finger over a button) and no vibration (finger not over any button). Kaaresoja et al. [START_REF] Kaaresoja | Snap-Crackle-Pop: Tactile Feedback for Mobile Touch Screens[END_REF] presented a touchscreen mobile device augmented with piezo-electric tactile feedback. The actuators are positioned under a resistive touchscreen, and can provide tactile feedback to a stylus or finger. The authors suggest four applications for the touchscreen tactile feedback: numerical keypad, text selection, scrolling, and drag and drop. Lastly, Hoggan et al. [START_REF] Hoggan | Investigating the Effectiveness of Tactile Feedback for Mobile Touchscreens[END_REF] presented a study investigating the use of tactile feedback for touchscreen keyboards on PDAs. The tactile feedback added to the standard touchscreen buttons was made up of simple tactons, that are abstract structured vibrotactile icons that can be used to encode multiple dimensions of information [START_REF] Brown | Multidimensional Tactons for Non-Visual Infomation Display in Mobile Devices[END_REF].

The research mentioned above shows that tactile feedback can be an effective addition to touchscreen interaction in terms of performance and user satisfaction. However, even though most tactile hardware involves at least a small amount of latency, the majority of this research does not take this into account. The promising results of the studies discussed above may be drastically reduced if users are not tolerant to latencies.

Latency

Adelstein et al. [START_REF] Adelstein | Sensitivity to haptic-audio asynchrony[END_REF] experimented with the threshold for detecting a difference between two different latency conditions between audio and tactile stimuli. The participants tapped a brick with the rubber tip of a hammer twice, and were asked to judge if there was difference in the lag of two stimuli pairs. The results suggest that the just noticeable difference is 24 ms, which as unaffected by the length of the audio stimulus.

Mäki-Patola and Hämäläinen [START_REF] Mäki-Patola | Latency Tolerance for Gesture Controlled Continuous Sound Instrument Without Tactile Feedback[END_REF] studied the tolerance of a human performer for latency in gesture controlled musical instruments. The threshold for latency perception was between 20 and 30 ms. They also found out that the playing style affected the detection of latency: if slow passages of music with vibrato were played, high latencies were tolerated. Also younger participants detected the latency more easily.

MacKenzie and Ware [START_REF] Mackenzie | Lag as a Determinant of Human Performance In Interactive Systems[END_REF] reported a study on the effect of latency in a target acquisition task using the Fitts" law paradigm. They introduced four latency conditions, 8.3, 25, 75 and 225 ms. The task was to move a small rectangle to a target with a mouse on a computer screen. They modified the target width and the distance from the target. The results showed that the maximum latency 225 ms significantly slowed down the task by 64% from the reference 8.3 ms, error rate being 214% higher (3.6% to 11.6%).

In our previous work [START_REF] Kaaresoja | The Effect of Tactile Feedback Latency in Touchscreen Interaction[END_REF] we investigated the effect of constant tactile feedback latency in touchscreen keypad interaction. We experimented with latency between the virtual button press and the tactile feedback from 18 ms to 118 ms.. The task was to enter numbers in a number keypad and short sentences in a QWERTY keypad. The latency was unchanged during a test block of number or character entry tasks. The results showed that the users tolerate the tactile feedback latency well. The performance did not drop significantly. However, an effect was found in subjective satisfaction: the satisfaction drops as the delay gets longer.

Although a small amount of research has been conducted in the area of tactile feedback latency for touchscreens, there has been no investigation of variable latencies or of the potential design opportunities provided by such latencies.

Experiment 1: Variable Delay

The first experiment in this research investigated the effect of tactile feedback latency variation on user performance in touchscreen interaction. The aim of the study was to compare the efficiency, accuracy and subjective perceived pleasantness of the touchscreen use between different tactile feedback latency variation conditions.

Participants

A within subjects design was used with 12 participants. Six of them were female and six were male. The age varied from 18 years to 47, average age being 28 years. All the participants were employees of Nokia Research Center. They were all righthanded. Ten of the participants had used a mobile phone for over five years and two of them for about 3-5 years. All participants claimed they write an average of three text messages per day. Four participants said they use a touchscreen device daily. Five participants said that they use touchscreen devices once in a while, and the last three participants had never used a touchscreen device.

Equipment and Stimuli

Experiment 1 was conducted on a Nokia 770 Internet Tablet (Fig. 1) augmented with tactile feedback [START_REF] Laitinen | Enabling mobile haptic design: Piezoelectric actuator technology properties in hand held devices[END_REF]. The 4-inch (90 x 54 mm) touchscreen displayed a virtual numeric keypad (Fig. 2). The experiment application was written in Python. Tactile feedback was generated with two piezo discs which were placed under the display module [START_REF] Laitinen | Enabling mobile haptic design: Piezoelectric actuator technology properties in hand held devices[END_REF]. We decided to study button-down feedback as opposed to button-down and button-up to keep the number of experiment conditions low enough and because an experiment with button-up feedback was conducted separately [START_REF] Kaaresoja | The Effect of Tactile Feedback Latency in Touchscreen Interaction[END_REF]. Button-up feedback on touchscreens can be complicated because the user"s finger tends to have been removed from the display before the feedback is presented meaning that tactile feedback can often go unnoticed at least when the latency is higher.

The tactile pulse used in the Experiment 1 is shown in Fig. 3. The rise time of the pulse was 1 ms and the fall time 4 ms, displacement of the display module being about 6 µm. When the user pressed a key, this pulse was given after a delay described below. Four different tactile feedback latency variation conditions were selected. The first condition was the reference 18 ms (minimum latency achieved with the hardware used) with no variation. The second condition was latency variation between 18 and 36 ms (randomized equal amount of latencies 18 and 36 ms), the third being between 18 and 72 (randomized equal amount of latencies 18, 36 and 72 ms), and the fourth between 18 and 144 ms (randomized equal amount of latencies 18, 36, 72 and 144). As we can see, the maximum latency was doubled for every condition. The latency variation conditions were named as 18, 18-36, 18-72 and 18-144. The delay was validated with a microphone and an oscilloscope.

Procedure

The piezo technology inherently produces audio feedback in addition to tactile feedback. In order to find out if the audio feedback has an effect, we decided to run the experiment both with and without headphones. In the first condition, typical street noise was played in the headphones to mask the audio feedback from the device. These two environmental conditions were named as Tactile (with headphones) and Tactile&Audio.

The task was to key in the three numbers, which appeared on the display at once and press lastly the OK button using the virtual keypad (Fig. 2). If the participants made an error, they could correct it with the C-button. There were altogether 55 tasks in one block. The block was repeated in all four conditions. There were 440 tasks in Experiment (55 tasks, 4 latency conditions and 2 environmental conditions) altogether. All the blocks and conditions were counterbalanced. The experiment application measured the time from the first keypress to the keypress of OK button and it also wrote the numbers, the test user keyed in, into a results file.

Before starting the actual experiment, the participants were able to try to key in few three digit number series. The participants were instructed to hold the device with both hands and press the virtual buttons on the touchscreen with their right thumb (Fig. 4). Fig. 4. The participants were instructed to hold the device with their both hands and press the virtual buttons with their right hand"s thumb.

There was a questionnaire concerning the subjective satisfaction after each block. The participants were asked to rate their degree of agreement with the following statements using a 1-7 rating scale, where 1 meant totally disagree and 7 totally agree:

 This keypad is pleasant to use.  I felt myself comfortable when using this keypad.  Pressing the keypad buttons felt just like pressing physical ("real") buttons.  I always knew that the device received my keypress.  I would like to buy a device with this kind of keypad.

There also was a interview containing the following questions after the completion of all the test blocks:

1. Did you notice any difference in the feedback? 2. Did you notice that some of the feedback came after a delay? 3. What did you think about the feedback delay? Was it distracting? Did the feedback delay have some effect on your performance? It took approximately 30 minutes to complete the whole experiment.

Results

Fig. 5 shows the average task time with 95%CI in all the latency variation conditions for both Tactile and Tactile&Audio conditions. A two-way repeated measures ANOVA showed there is a significant difference in the latency variation condition Fig. 6 shows the average error rate with 95%CI in all the latency variation conditions for both Tactile and Tactile&Audio conditions. A two-way repeated measures ANOVA showed there is no significant difference in the latency variation condition [F [START_REF] Mine | Characterization of End-to-End Delays in Head-Mounted Display Systems[END_REF]33)

Average error rate

Tactile&Audio Tactile Fig. 6. The average error rate with 95%CI in with and without headphones.

Fig. 7 and Fig. 8 show the mean values and standard deviations for degree of agreement with the satisfaction questionnaire statements on a 1 to 7 (totally disagreetotally agree) scale in Tactile and Tactile&Audio conditions. In both conditions the results show that the keypad with largest delay variation was clearly rated lowest in all five statements. Therefore we can conclude that it is less pleasant to use compared to other keypads with less delay variation.

In the interview, the users commented that, without the audio feedback (with the headphones on), the significance of the tactile feedback was quite obvious. They noticed differences in the keypad"s sensitivity and accuracy. Participants stated that keypad with the largest delay variation required more force to press the buttons and felt somewhat unreliable. Only a couple of users noticed the delay in some of the feedback and the others did not notice that at all (10 out of 12 participants). The keypad with the shortest delay was said to be the most pleasant to use; it was fast and felt natural.

Users without the headphones (Tactile&Audio condition) commented that they noticed differences in the keypad"s accuracy and reliability. The keypad with the shortest delay was said to be more sensitive and reliable and it did not require so much force to press the buttons compared to other keypads. Only two of the test users said that they noticed that some feedback came after a delay but the rest did not notice that at all. However, almost all users commented that there was something seriously wrong with the keypad with the largest delay variation and it was horrible to use but they could not figure out the reason behind this. Users commented that they needed to press the buttons very hard before the keypad received their key-press.

Discussion

This study clarified the effect of tactile feedback delay variation on the user performance in the use of the touchscreen device. The study compared the efficiency, accuracy and subjective perceived pleasantness of touchscreen use between different tactile feedback delay variation conditions. The experiment also investigated whether audio feedback biases the effect of tactile feedback delay variation on user performance and the evaluation of the pleasantness of the tactile feedback. It was found that the keypad with a feedback delay variation of 18-144 ms was slowest to use. However, there was no significant increase in the error rate. The results also showed that in the satisfaction questionnaire the keypad with the largest delay variation 18-144 ms received clearly the lowest score in all five statements compared to other delay conditions.

Therefore it is suggested that users can tolerate a tactile feedback delay varying from 0ms to 36ms and even 76 ms when using touchscreen buttons. However, wider feedback delay variations impact user performance, with reduced accuracy and increased task times, and are thereby unacceptable. The same conclusion can be drawn from the pleasantness evaluations where users strongly disliked the keypad with the biggest delay variation.

The pairwise comparisons between the Tactile&Audio and Tactile conditions showed no statistical differences. These results indicate that inherent audio feedback does not have an effect on user performance or the perceived pleasantness of touchscreen buttons incorporating tactile feedback variations.

From Performance Measurements to Illusions

The experiment described next takes the issue of tactile latency one step further by examining the perceptual illusions. In the areas of HCI and UI design, delays in feedback for a user"s actions are often considered as negative issues and are to be avoided at all costs. However, the results of the experiment detailed above have shown that latency in tactile feedback is varying between 0 ms to 36 ms in touchscreen virtual button use cases is acceptable. In fact, in Experiment 1, most users (10 out of 12) were not aware of the delay. Interestingly when participants were asked in post-study questionnaires about their experience during the experiments, several participants mentioned aspects related to the size and weight of the buttons. For example, in Experiment 1, one participant stated, "especially the last one (18-144 ms) required much more force to press the buttons" and "I needed to press the buttons very hard". A previous study [START_REF] Kaaresoja | The Effect of Tactile Feedback Latency in Touchscreen Interaction[END_REF] on constant feedback latencies produced similar findings where participants felt that they needed to apply more force to the touchscreen buttons when the delay was longer, even though the activation threshold of the touchscreen was not altered in any way. It appears as though the introduction of different delays to tactile feedback does not affect latency perception but in fact affects the perception of the size/weight of the button.

Experiment 2: Perceived Weight Study

Finding design parameters for tactile feedback to encode information is a difficult task as the set of parameters that can be manipulated is much smaller than in sound for example, and this reduces the number of stimuli that can be created. Researchers are trying to find effective new parameters that can be used for the design of distinguishable tactile feedback. Previous studies have investigated parameters such as rhythm, spatial location and texture [START_REF] Brown | Multidimensional Tactons for Non-Visual Infomation Display in Mobile Devices[END_REF][START_REF] Hoggan | New Parameters for Tacton Design[END_REF][START_REF] Ternes | Designing Large Sets of Haptic Icons with Rhythm[END_REF]. The post-study questionnaire results in Experiment 1 suggest that latency may be a potential new parameter for use in the design of tactile feedback. Introducing latency may be sufficient to create a fullstrength illusion of weight or depth.

In an effort to establish weight (created using latency) as a tactile feedback design parameter, this section presents the results from an experiment investigating whether users perceive buttons with a bigger delay as being heavier or larger. We present practical implementation details and guidelines based on the results focusing on the design of heavy/light touchscreen buttons and more specifically, on the most effective parameter design. Drawing on the results, we argue that weight can be used as an additional parameter when designing tactile feedback for touchscreens.

Related Work

Traditionally most research into the perception of weight has concluded that the visual sense has dominance over the other senses. In particular, the most famous area of study is the size weight illusion [START_REF] Murray | Charpentier (1891) on The Size-Weight Illusion[END_REF][START_REF] Ross | Weight Illusions and Weight Discrimination -A Revised Hypothesis[END_REF][START_REF] Van Mensvoort | What you see is what you feel: exploiting the dominance of the visual over the haptic domain to simulate force-feedback with cursor displacements[END_REF] where when lifting two objects of different volume but equal weight, people judge the smaller object to be heavier.

However, more recently it has been shown that the sense of touch can also affect the perception of weight. Ellis and Lederman [START_REF] Ellis | The Role of Haptic Versus Visual Cues in The Size-Weight Illusion[END_REF] showed that the size-weight illusion is a primarily haptic phenomenon where haptic volume cues can create the same size-weight illusion as well as visual volume cues if not better. Amazeen [START_REF] Amazeen | Perceptual Independence of Size and Weight by Dynamic Touch[END_REF] also showed that a dependence of perceived heaviness relies on a dependence on perceived volume (perceptual independence). This volume can be perceived through the sense of touch by allowing users to grasp virtual objects using force feedback devices for example.

These results would suggest that it might be beneficial to investigate the use of haptic volume cues in touchscreen interaction too. Although the objects cannot be physically grasped, it may be possible to create a similar illusion of weight or volume without using visual cues.

Equipment and Stimuli

The equipment was identical to Experiment 1. The tactile pulse used in the Experiment 2 is shown in Fig. 9. The rise time of the pulse was 5 ms and the fall time 4 ms, displacement of the display module being about 25 µm, leading a feeling of soft tactile click. When the user pressed a key, this pulse was given after a delay. The delays used were 18, 38, 58, 78, 98, 118, 138 and 158 ms. Given the results of Experiment 1, participants did not wear headphones to block out the audio feedback from the actuators, as this had no statistical effect on the accuracy of the number entry tasks.

Methodology

The aim of this experiment was to investigate whether users perceive buttons with a bigger delay as being heavier. A magnitude estimation method was used where participants assigned an arbitrary number of their own choice to the weight of a baseline stimulus presented. Participants were then presented with a series of further stimuli (buttons plus delay) and asked to assign a weight number reflecting its perceived weight relative to the baseline. Overall there were 28 tasks in the experiment using a random baseline stimulus (chosen from the 7 clicks with different delays). For example, a participant could be presented with the 18 ms delay stimulus as the baseline and asked to assign a weight value to the 158 ms delay stimulus in comparison to the baseline (Fig. 10). The experiment took approximately 30 minutes to complete. Overall, fourteen participants took part in the experiment: 8 male and 6 female, all employees of Nokia Research Center. In general terms, the experiment involved a within subjects design where teach participant completed all magnitude estimation tasks for all seven delay categories. All tasks were counterbalanced.

Hypothesis

The hypothesis for this experiment was as follows:

1. Longer delays in tactile feedback will result in the perception of heavier buttons.

Results

During the experiment, the experimental software recorded data on the participants" magnitude estimations of each stimulus as shown in Fig. 11. Given that participants could assign any weight rating they wished, all data were normalized prior to analysis. From the average weight estimates for each tactile feedback delay we found a significant correlation of 0.81 (r = 0.532, p = 0.05) showing a positive relationship between weight and latency. This correlation suggests that higher feedback delays result in the perception of heavier buttons.

Analysis of the weight estimates for each tactile feedback delay using an ANOVA showed a significant difference (F=13.69, df=6, p<0.05). As summarised in Table 1, Post hoc Tukey tests with Bonferroni corrected significance levels showed that buttons with delays of 78 to 158 ms are perceived as significantly heavier than those using an 18 ms delay (p = 0.05). Buttons with delays ranging from 98 to 158 ms are perceived as significantly heavier than those with a 38 ms delay (p = 0.05). Buttons with delays of between 118 and 158 ms are also perceived as significantly heavier than 58 to 78 ms delays (p = 0.05) and a 158 ms delay is also perceived as significantly heavier than a 98 ms delay (p = 0.05). Lastly, there were no significant differences in the perceived weight of touchscreen buttons with delays ranging between 18 and 58ms or between 118 and 158 ms. These results indicate that it is possible for users to interpret delays as having an effect on the perceived "weight" of touchscreen buttons. Button presses with tactile feedback delayed by 18 ms, 78 ms, and 118 to 158 ms respectively are perceived as being significantly heavier.

Post-Study Questionnaire Results

At the end of the experiment, participants were given the opportunity to try all buttons with all delays again and asked which button they thought was the heaviest and which was the lightest. The results are shown in Fig. 12. Participants did not rate any of the buttons with short delays as "heavy". 158 ms was voted as the heaviest 57% of the time and 118 ms 43% of the time. This suggests that the weight difference between 118 and 158 ms is negligible.

As opposed to the votes for the heaviest button, no long delays were chosen to be the lightest buttons. The shortest delays of 18 and 38 ms were voted as the lightest buttons (with 1 vote for 78 ms, which is surprising. Further investigation with a larger number of participants is required.)

In the post-study questionnaire, participants were also asked to rate levels of pleasantness, comfort, realism and confidence on a scale of 0 to 7. As can be seen in Fig. 13, all buttons with all delays were rated fairly highly for all measures. Fig. 13. Average rating for each delay (out of 7) with standard deviations Analysis of the questionnaire results showed no significant differences except for confidence levels. A Kruskal-Wallis test (H = 12.87, df = 6, p = 0.05) followed by post hoc Dunn"s Tests (p = 0.05) confirmed that participants experienced significantly lower confidence levels when using buttons with 158ms feedback delays compared to those with 18 and 38 ms. Some participants stated: "it (158 ms) seems unresponsive" and "sticky (118 ms and 158 ms)" which helps to explain such low confidence levels.

Discussion

Overall, when using this range of delays, 3 significantly different weights can be produced using: 18, 78 and 118 or 158 ms. One participant mentioned, "only C (158 ms) is unpleasant to use". Fortunately, given that feedback delays of 118 ms are also perceived as significantly heavier than 78 ms and 18 ms, there is no need to use a delay of 158 ms when aiming for three distinctive weights.

In the future, tactile latency could be incorporated into touchscreen widgets such as soft keyboards. For example, buttons with important or crucial functions such as "delete" or "send" could use a longer feedback delay to create the illusion of weight.

Overall Discussion and Conclusions

This paper reported the results of two experiments investigating tactile feedback latencies in touchscreen interaction. Both experiments approached latency from a different perspective. The first experiment took a traditional stance with an aim to establish the levels at which variable tactile feedback latencies become detrimental to performance and perceived pleasantness of touchscreen keypads. The second experiment focused on the potential benefits of latency as a design parameter.

The first experiment produced some interesting findings. Firstly, tactile feedback latencies with small variations between 18 and 72 ms were found to be acceptable to most users. The results show that the keypad with a feedback delay variation of 18-144 ms was slowest to use. However, there was no significant increase in the error rate. The majority of participants indicated in the satisfaction survey that high levels of variation (18 to 144 ms) were not pleasant or preferred.

In real world systems, it is more likely for users to encounter variable feedback delays than constant delays so it is important for designers to take this into account and ensure that such variations do not exceed 72 ms.

Unexpectedly, the results of the first experiment also indicate that audio feedback does not have an extra effect of the performance and perceived pleasantness of tactile feedback with variable latencies. This is a very positive finding given that most devices produce some intrinsic audio feedback when the tactile actuators vibrate. It is reassuring to know that this extra feedback does not affect performance. However, it must be noted that the additional audio feedback could perhaps cause annoyance to users, especially in discreet situations and environments such as libraries.

Experiment 2 was conducted to establish whether users perceive buttons with a bigger tactile feedback delay as being heavier. The results show that adding tactile feedback latencies to button presses does indeed create the illusion of added button weight. More specifically, to create a set of three different buttons with different perceived weights, the tactile feedback latencies should be set to 18 ms, 78 ms and 118 ms+.

It may seem unusual to encourage the introduction of feedback delays but in this case our research has successfully shown that tactile feedback delays often go unnoticed by users and that, instead, these delays create the illusion of weight. This may explain the high tolerance of users to the tactile feedback latencies in the first experiment discussed in this paper and in our previous work on constant feedback latencies [START_REF] Kaaresoja | The Effect of Tactile Feedback Latency in Touchscreen Interaction[END_REF].

In order for this new design parameter to be used effectively, it will be necessary to combine it with other tactile parameters to see if there are any negative effects when used in combination. Furthermore, future studies will investigate similar touchscreen widget weight illusions with other combinations of modalities such as audio and visual. The thresholds of this parameter will also be investigated to establish the maximum and minimum delays that can be introduced to create the illusion of weight without disturbing performance. Given the relatively low number of design parameters in the tactile modality, compared to audio for example, the addition of a weight/latency parameter can greatly increase the amount of distinguishable tactile feedback that can be created. This new parameter may be used to enhance many different types of interface widgets and also to represent the weight of 3D objects.

Fig. 1 .Fig. 2 .

 12 Fig. 1. Nokia 770 Internet Tablet enhanced with tactile feedback

Fig. 3 .

 3 Fig. 3. The tactile feedback pulse used in Experiment 1. The figure shows the displacement of the display module.

Fig. 5 .

 5 Fig. 5. The average task time with 95%CI in with and without headphones.

Fig. 7 .

 7 Fig. 7. Mean values and standard deviations of subjective ratings in Tactile condition.

Fig. 8 .

 8 Fig. 8. Mean values and standard deviations of subjective ratings in Tactile&Audio condition.

Fig. 9 .

 9 Fig. 9. The tactile feedback pulse used in Experiment 2. The figure shows the displacement of the display module.

Fig. 10 .

 10 Fig. 10. Screenshot of interface in Experiment 2

Fig. 11 .

 11 Fig. 11. Average weight estimate for each tactile feedback delay (with standard deviations)

Fig. 12 .

 12 Fig. 12. Total number of votes for the heaviest and lightest button based on delay

  =2.43, p=0.07], or the between Tactile and Tactile&Audio conditions [F(1,11)=1.39, p=0.24].

		3%
	(%)	2%
	rate
	Error	1%
		0%
		18	18-36	18-72	18-144

Delay condition (ms)

Table 1 :

 1 Summary of tactile latencies (in milliseconds) perceived to create heavier buttons

	18	38	58	78	98	118	138	158
	18			*	*	*	*	*
	38				*	*	*	*
	58					*	*	*
	78					*	*	*
	98							*
	118
	138
	158


Maja Wrzesien

María-José Rupérez

Mariano Alcañiz Raya

Input Devices in Mental Health Applications: Steering Performance in a Virtual Reality Paths with WiiMote

Keywords: Mental health, virtual reality, steering law

Recent studies present Virtual Reality (VR) as potentially effective technology in the Mental Health (MH) field. The objective of this paper is to evaluate two interaction techniques (traditional vs novel) using a popular and low-cost input device (WiiMote) within a theoretical framework of the Steering Law. The results show that the WiiMote responds to the requirements for the MH technologies, and that the law of Steering continues to be valid on all of three paths. This opens up a new range of possible research studies for the design and evaluation of interaction techniques in MH field.

Introduction

Even though the use of 3D input device is increasing, the development of input device for particular domain such as MH applications evolves slowly [START_REF] Frohlich | On 3D Input Devices[END_REF]. Indeed, there has been few studies performed regarding VR technology within the medical context [START_REF] Jin | Improving the visual realism of virtual surgery[END_REF], nor much information regarding the choices of the optimal for this specific context input/output device has been proposed [START_REF] Zudilova-Seinstra | Evaluation of 2D and 3D glove input applied to medical image analysis[END_REF]. Moreover, to the authors' knowledge, no studies regarding input devices in mental health VR applications have been performed.

The purpose of this paper is to choose the input device that might correspond to the requirements of VR mental health technologies and evaluate it in the context of a basic task (i.e., traveling task) used in VR mental health applications. More specifically, our aim is to extend the application of a formal predictive model (Steering Law) to a more complex and more close to a real-use path, a maze path. In our opinion, circular or straight paths do not reflect the paths that are habitually used in VR mental health applications, such as those that might be used for virtual cognitive rehabilitation tasks, virtual reality exposure therapies, or therapeutic virtual games. This has motivated us to study the validity of the Steering Law in a maze path.

Virtual Reality has a great potential in different MH applications, and has been effectively used in differ MH disorders [START_REF] Botella | Virtual Reality and Psychotherapy[END_REF] such as anxiety disorders; eating disorders; and sexual disorders. Many potential techniques have been proposed to interact with VR environments [START_REF] Zhai | User Performance in Relation to 3D Input Device Design[END_REF], from standard techniques such as mouse, joystick, touchscreen, to specialist techniques such as spacemouse, trackballs, wands, gloves. Some general requirements regarding the input device design for the VR environments have been proposed [START_REF] Bowman | 3D User Interfaces, Theory and practice[END_REF]. However, the input devices used in mental health VR applications should take into account some additional design recommendations, closely related to general guidelines for MH technologies [START_REF] Doherty | Design and evaluation guidelines for mental health technologies[END_REF]. First, the input device should be attractive and engaging. Since engagement is one of the critical factors in creating client-therapist relationship, attractive and fun input device might be a first step in engaging clients in the interaction with technology that in turn might help them getting engage in the treatment and relationship with the therapist. Second, the input device should be intuitive and easy to use. Indeed, since the clients have different social and cultural backgrounds, the input device should be easy to use and to learn. Moreover, according to Doherty et al. [START_REF] Doherty | Design and evaluation guidelines for mental health technologies[END_REF], it seems to be beneficial for the clients to use familiar for them and easily available technologies, since technology is rarely used in day-to-day client work or in therapist training. Third, the input device should be affordable. In fact, interacting in a VR environment often involves the use of devices intentionally made for that purpose. However, these devices are generally expensive and often not available for the average consumer. Finally, the input device should be flexible, allowing the designers to program it in different ways. Indeed, an important requirement for the MH technology to be of practical use corresponds to the necessity for the system to be adapted to the brand range of MH disorders [START_REF] Coyle | PlayWrite: End-User Adaptable Games to Support Adolescent Mental Health[END_REF]. Thus, the flexibility of the input device would allow the designers to adapt it according to the needs of a specific application.

Evaluation

The Steering Law [START_REF] Accot | Beyond Fitts' Law: Models for Trajectory-Based HCI Tasks[END_REF] is a model of human movement that predicts the speed and total time spent by a user who steers with a pointing device through a tunnel or along a path presented on a screen. It describes a linear relationship between the mean time of steering along the path and the index of difficulty of the path, which is the ratio between the length and width of the path. In other words, the longer the path and the smaller the width, the greater the mean steering time. This predictive model was chosen as a framework for this evaluation for the following reasons. First, it brings consistency to empirical evaluations of input devices by using rigorous methodology. Second, it gives researchers the opportunity to compare their results in a cross-study comparison. Finally, it allows to extend its application in a 3D straight and circular paths [START_REF] Zhai | Human Movement Performance in relation to path Constraint-The Law of Steering in Locomotion[END_REF] to a path that is more representative in the MH applications (a maze path).

The WiiMote input device [START_REF] Lee | Hacking the Nintendo WiiRemote[END_REF] was chosen for this study for the following reasons. First, this type of device is a low-cost and currently used 3D input device. Thus, its use seems interesting in terms of a low financial impact and quite high popularity which corresponds to the affordability, familiarity and attractiveness requirements. Second, the WiiMote presents many different possibilities in terms of interactions techniques (for 2D and 3D tasks). Finally, the WiiMote presents a wide range of possible functionalities to be programmed, which corresponds to the flexibility requirement. More specifically, in the case study presented in the following sections the WiiMote input device was programmed according to Bowman et al. classification [START_REF] Bowman | 3D User Interfaces, Theory and practice[END_REF]: input device with (a) both discrete components (buttons) for direction/target selection task, and continuous components (gesture-based movement, i.e. wrist movements) for velocity/acceleration selection, which we can call a traditional interaction technique; (b) continuous components (gesture-based movement, i.e. wrist movements) for both direction/target selection task and velocity/acceleration selection, which can be called a novel interaction technique.

The traveling task in a maze path was chosen as the task used in these empirical study for the following reasons. First, traveling, which is a motor component of navigation [START_REF] Bowman | 3D User Interfaces, Theory and practice[END_REF], supports a cognitive component of the navigational process, as well as other interaction-related and therapy-related processes. Second, traveling is a basic task in many VR mental health applications in order to move from a current location to another target location, and support other type of tasks. Finally, travel in a maze path seems better reflect the characteristics of MH applications than the previously basic shapes used in this theoretical framework (straight and circular). The travel task in a maze path such as a supermarket environment or a city center can be applied in the MH applications such as cognitive rehabilitation, preventive systems for dementia, or VR post traumatic stress disorder treatment.

Methodology

A fully-crossed, within-subject factorial design with repeated measures was used. The independent variables were the following: (a) the path shape with three modalities (P=straight, circular and maze); (b) the interaction technique (IT=novel vs traditional); and (c) the index of difficulty defined by different path widths and the same path length, with six modalities (ID=122, 144, 168, 190, and 212 cm). The steering time and error rates were the dependant variables. Moreover, users' short post-experience semi-directive interview data were collected. In order to avoid the learning process between trials, the order of use of the input device, index of difficulty, as well as the path shape presentation was balanced according to a Latin square pattern. Also, the entrance sides to the maze path and the turning direction for the circular path were changed between the two input devices. Touching the walls of the paths resulted in an error being recorded. According to Zhai and Woltjer [START_REF] Zhai | Human Movement Performance in relation to path Constraint-The Law of Steering in Locomotion[END_REF], only the trials without errors were taken into account in the data analysis. The error rates were analyzed separately.

Eighteen people (seven men and eleven women; 19-36 years old (MD=25,50, SD=5,15)) participated in this study. The participants were selected by previously fixed exclusion criteria (left handed people, significant experience in tridimensional and in basic computer games, significant experience in 3D graphics, and significant experience in use of the WiiMote). According to recommendations of Doherty et al. 11 the evaluation was performed with non-clinical population; however the sample aimed at reflecting the clinical population characteristics (i.e., diversity in social and cultural background; diversity in age; and small experience with innovative technologies).

Three different path shapes were used in the experiment: a straight path, a circular path (see Figure 1 (a) and (b)), and a maze path (see Figure 1 (c)). Six different widths of the path were set for each path shape at 100, 122, 144, 168, 190, and 212 cm simulating paths in which a human could move. The width of the avatar used to navigate in the virtual environment was 45 cm simulating a human body. The avatar was placed equidistant from the two walls of the paths. The virtual environment for the experiment was developed under 3dGamestudio, version 7.77. The image of the paths was projected on a 180x240 cm screen with 1024 by 768 resolution. The output device was chosen as the most often used device for the VR mental health in our research center. The task consisted of traveling through a virtual environment toward the clearly marked finishing point. No time pressure or constraints were imposed during the trials; however, the participants were asked to perform the task as fast as possible without touching the walls, restriction needed to validate the Steering Law.

Two different set-ups of the WiiMote were tested: a novel interaction technique involving no use of any buttons (only wrist movements; see Figure 2

Results

Figure 3 (a,b,c,d,e,f) show the regression results between the index of difficulty and the mean completion time for both interaction techniques and for all paths. The index of difficulty was calculated by dividing the path length by six different path widths. As Figures 3(a) and 3(b) show, there was a strong linear relationship between the mean time and index of difficulty for the straight path with the traditional interaction technique (r 2 =0.996), and with the novel interaction technique (r 2 =0.985).

Figures 3 (c) and 3(d) show a slightly different but still strong linear relationship between the mean time and index of difficulty for the circular path (r 2 =0.915 for traditional interaction technique, and r 2 =0.988 for the novel interaction technique). Finally, Figures 3(e) and 3(f) show a strong linear relationship between the mean time and the index of difficulty for the maze path with the traditional interaction technique (r 2 =0.991) and with the novel interaction technique (r 2 =0.962). The highest performance related to the traditional interaction technique in term of slope (less time increase per unit of ID, corresponding to 1/b in steering law equation) was for the straight path (IP=1/0.162), followed by the maze path (IP=1/0.335), and the lowest performance was for the circular path (IP=1/0.507). The performance related to the novel interaction technique in term of slope was highest for the circular path (IP=1/0.107), followed by the straight path (IP=1/0.117), and then the maze path (IP=1/0.833).

Due to the differences in the programming set-up of the direction selection (input device set-ups with mixed components, with arrow buttons and wrist movements vs input device set-ups with continuous components, with only wrist movements), the input device set-ups cannot be compared using the slope and the intercept that are derived from the Steering Law equation. However, the two interaction techniques can be compares in terms of error rates. The results show (see Figure 4(a)) that the error rate depends on the path width (F 5,85 =53,362, p<.000) with significantly more errors for the narrowest path than for the other paths (post hoc multiple comparison with Bonferroni correction, p<.0001). In addition, as the results in Figure 4(b) show, the error rate depends on the different interaction technique (novel vs traditional) (F 5,85 =5,923, p<.026) with significantly more errors for the novel interaction technique (where only wrist was involved). More specifically, the error rates were significantly higher in the maze path than in the other two (post hoc multiple comparison with Bonferroni correction, p<.026). Finally, there was a significant interaction (F 10,170 =3,501, p<.000) between the path condition (straight, circular, maze) and the path width in both interaction techniques (see Figure 5 The informal interview revealed that the participants preferred the novel interaction technique slightly more than the traditional interaction technique (57% vs 43%). The majority of participants considered the novel interaction technique fun and intuitive (-I liked this technique because it was new and entertaining"; -It was fun to navigate like this‖). Some of the participants that had difficulties in using the novel interaction technique considered that once they used to it, it was not so difficult (-Well, in the beginning it was hard, but once you get used to it it's quite fun‖). On the other hand, the participants that chose the traditional interaction technique considered it easy to use and familiar (-I liked it because it was the same thing as playing computer games on the keyboard"; "I preferred this technique because it's like using the remote control"). In general, participants enjoyed traveling with both interaction techniques ("It was so fun to walk in virtual environments"; "Call me for the next study").

Discussion and conclusions

The objective of the study was to evaluate an adapted to MH applications input device in a case study of traveling task. The results show that the WiiMote responds very well to all requirements. First, according to the informal interviews, the traveling task with different WiiMote set-ups was enjoyed and perceived as fun by all participants. Since positive emotional response such as enjoyment is an integral part of engagement [START_REF] Shernoff | Student engagement in high school classrooms from the perspective of flow theory[END_REF], we can therefore consider that the WiiMote input-device can engage users. Second, the WiiMote set-ups were intuitive to use and easy to learn. Although, both interaction techniques were appreciate equally by the participants, the results show that there were significantly more errors for novel interaction technique (involving wrist movements) than for traditional interaction technique (involving use of arrow-buttons and wrist movements). On the other hand, the error rates obtained with the traditional interaction technique were significantly greater for the narrowest circular path (see Figure 5a). Therefore, we can conclude that the choice between these two interaction techniques and its usefulness depends on the path shape in a particular application. Finally, WiiMote responds to the flexibility requirement. In this study we evaluate two WiiMote set-ups; however, WiiMote can be programmed in many ways. For instance, a different interaction technique with a more controlled bimanual interaction (according to Guiard's model) can be proposed (see Figure 6). Moreover, our objective was to extend the theoretical framework to a maze path. The study confirmed that the Steering Law established for the circular and straight paths in 3D environments is also valid for a maze path. The correlations in this experiment are slightly smaller than those obtained by Zhai and Woltjer [START_REF] Zhai | Human Movement Performance in relation to path Constraint-The Law of Steering in Locomotion[END_REF]. These differences might be due to the inexperienced with new technologies population used in this study.

Fig 1 .

 1 Fig 1. The three paths used in the experiment: straight (a), circular (b), and maze (c).

  (a)), and a traditional interaction technique involving use of buttons (see Figure 2 (b)).

Fig 2 .

 2 Two WiiMote set-ups (novel (a) vs traditional (b)). The bold blue arrows in Figure (a) indicate user motion while navigating and accelerating with the device involving no use of any buttons, only wrist movements, the bold blue arrows in Figure (b) indicate user motion while accelerating, and the thin blue arrows indicate directions of the arrow buttons used for traveling.

Fig 3 .

 3 Fig 3. Index of Difficulty vs trial completion time in the straight path with traditional (a) and novel technique (b); in the circular path with traditional (c), and novel interaction technique (d); and in the maze path with traditional (e), and novel interaction technique (f).

Fig 4 .Fig 5 .

 45 Fig 5. The error rates for traditional (a), and for novel interaction technique (b), regarding different path shapes and different indexes of difficulties.

  (a) and (b)).

Fig 6 .

 6 Fig 6. Bimanual interaction technique. The bold blue arrows indicate user motion while accelerating and the thin blue arrows indicate user motion while navigating.

We can consider this study as a first step forward to better know the requirements for the input devices used in specific domain such as VR mental health technologies. We hope that this will motivate more researchers to carefully chose and design the input devices for their specific MH applications, which in turn will allow to create a more systematic typology of input devices for MH technologies.

Acknowledgements

We would like to express special gratitude to Jean-Marie Burkhardt and José David Martín-Guerrero. This study was funded by Ministerio de Educación y Ciencia Spain, Project Game Teen (TIN2010-20187) and partially by projects Consolider-C (SEJ2006-14301/PSIC), -CIBER of Physiopathology of Obesity and Nutrition, an initiative of ISCIII‖ and Excellence Research Program PROMETEO (Generalitat Valenciana. Conselleria de Educación, 2008-157).