Coralie Amadou
email: coralie.amadou@gmail.com

Aurélie Carlier
email: aurelie.carlier@aphp.fr

Chloe Amouyal
email: chloe.amouyal@gmail.com

Olivier Bourron
email: olivier.bourron@aphp.fr

Carole Aubert
email: caroleelodie.aubert@insel.ch

Thibault Couture
email: thibault.couture@aphp.fr

Eric Fourniols
email: eric.fourniols@aphp.fr

Georges Ha Van
email: georges.havan@aphp.fr

Stéphanie Rouanet
email: stephanie.rouanet@statethic.fr

Agnes Hartemann
email: agnes.hartemann@aphp.fr

Agnès Hartemann

Five-year mortality in people with diabetic foot ulcer in the years 2009-2010 is lower than expected

Keywords: Diabetes. Foot. Ulcer. Mortality ABI Ankle brachial index CLI Critical limb ischemia DFU Diabetic foot ulcer PAOD Peripheral artery occlusive disease PEDIS Perfusion, Extent, Depth, Infection, Sensation

Aim

Mortality rate is decreasing in people with diabetes but if this observation also concerns patients with diabetic foot ulcer (DFU) needs additional data. This study evaluated the mortality rate at 5 years in patients with a DFU occurring in the years 2009-2010 and identified risk factors associated with mortality.

Methods

Patients who successively attended for a new foot ulcer between in 2009-2010 were followed until healing and at one year. Data on mortality were collected at year 5. Multivariate Cox proportional Hazard model was used to identify mortality risk factors.

Results

Three hundred and forty-seven patients were included: mean age was 65±12 y, diabetes duration was 16 [10; 27] years; 13 % were on dialysis and 7 % had an organ graft. At 5 years, 49 patients (14%) were considered lost to follow up. The total mortality rate at 5 years was 35 %, and 16% in patients with neuropathy. In multivariate analysis, mortality was positively associated with age (HR 1.05 [1.03-1.07], p < 0.0001); duration of diabetes (HR 1.02 [1.001-1.03], p = 0.03); PEDIS perfusion grade 2 vs 1 ], p = 0,006); PEDIS perfusion grade 3 vs 1 (HR: 3.14 [1.58-6.24], p=0.001), and with the duration of ulcer during the first year ], p=0.0009).

Conclusion

Mortality rate was not as high as expected despite a high number of co-morbidities, suggesting that progress has been made in health care of these patients. Particularly, patients with neuropathic foot ulcer had a survival rate at 5 years of 84%.

Introduction

Diabetic foot ulcer (DFU) is an economic burden for many countries and induces a dramatic decrease in physical, emotional, and social functioning for patients [START_REF] Reiber | The burden of diabetic foot ulcers[END_REF][START_REF] Boulton | The global burden of diabetic foot disease[END_REF]. It is associated with advanced micro and cardiovascular complications, resulting in high morbidity and a greater risk of premature death [START_REF] Boyko | Increased mortality associated with diabetic foot ulcer[END_REF]. The major cause of death in DFU is ischemic heart disease [START_REF] Iversen | History of Foot Ulcer Increases Mortality Among Individuals With Diabetes[END_REF][START_REF] Young | Improved survival of diabetic foot ulcer patients 1995-2008: possible impact of aggressive cardiovascular risk management[END_REF].

Studies regarding long term survival in patients with DFU are scare, but data coming from cohorts formed before the 2000s, reported mortality rates around 45% at five years [START_REF] Iversen | History of Foot Ulcer Increases Mortality Among Individuals With Diabetes[END_REF][START_REF] Young | Improved survival of diabetic foot ulcer patients 1995-2008: possible impact of aggressive cardiovascular risk management[END_REF][START_REF] Moulik | Amputation and mortality in new-onset diabetic foot ulcers stratified by etiology[END_REF]. However life expectancy has improved for the last years in people with diabetes [START_REF] Dale | Secular decline in mortality from coronary heart disease in adults with diabetes mellitus: cohort study[END_REF][START_REF] Rawshani | Mortality and Cardiovascular Disease in Type 1 and Type 2 Diabetes[END_REF], and therapeutic options for DFU have made progresses and are now the topic of robust international guidelines [START_REF] Bus | IWGDF guidance on footwear and offloading interventions to prevent and heal foot ulcers in patients with diabetes[END_REF]. A single study in 2008 [START_REF] Young | Improved survival of diabetic foot ulcer patients 1995-2008: possible impact of aggressive cardiovascular risk management[END_REF] suggested that survival in people with DFU before and after the 2000s could have increased, but these optimistic results were not confirmed in another study published in 2012 [START_REF] Morbach | Long-term prognosis of diabetic foot patients and their limbs: amputation and death over the course of a decade[END_REF].

The main aim of our study was thus to determine the years 2010 life expectancy in patients with DFU. Identifying patients with DFU who are at high risk of premature death is important to choose the best therapeutic project with each patient. Thus secondary objective was to identify the years 2010 predictive factors for five-year mortality in patients with DFU.

Methods

Population

Between March 2009 and December 2010, all patients with diabetes and a new foot ulcer who attended a multidisciplinary diabetic foot center in a University Hospital (Paris, France), were successively included in this cohort. Patients gave oral consent for participation and agreed to be contacted (them or their family relatives) to obtain information on their outcomes. The study was in accordance with ethical legislation in France.

ClinicalTrials.gov registration no. NCT03782129

Wound healing date was recorded until 12 months after inclusion. Five years after inclusion, patients or their family relatives or their family physician were contacted by phone to know if they were still alive. If necessary we consulted clinical files or the registry office of the patient's birth town hall. If there was no mention of death on birth certificate, the patient was considered to be still alive. If the patient was not born in France, and the information could not be obtained, the patient was considered lost to follow-up.

Foot ulcer management

All patients with DFU were treated according to the most recent guidelines from the International Working Group on the Diabetic Foot (IWGDF), particularly for Peripheral Artery Occlusive disease (PAOD), and the French Society of Infectious Diseases. Hospitalization was required in case of wound complications.

Database

At inclusion data were collected for the following variables: age, sex, diabetes type and diabetes duration, insulin therapy, BMI, dialysis, kidney or pancreas-kidney transplant, active smoking, presence of a relative at home or not, date of ulcer occurrence, history of previous DFU or amputation. Severity of ulcer was graded according to the University of Texas Diabetic Wound Classification System [START_REF] Armstrong | Validation of a diabetic wound classification system. The contribution of depth, infection, and ischemia to risk of amputation[END_REF] and to the PEDIS (Perfusion, Extent, Depth, Infection, Sensation) classification system [START_REF] Chuan | Reliability and validity of the perfusion, extent, depth, infection and sensation (PEDIS) classification system and score in patients with diabetic foot ulcer[END_REF].

In the PEDIS classification peripheral arterial occlusive disease (PAOD) is grade 2 if presence of symptoms or signs of PAOD but not of critical limb ischemia (CLI): presence of intermittent claudication or Ankle Brachial Index (ABI) <0.9 (but with systolic ankle pressure >50 mmHg) or Toe brachial Index <0.6 (but with systolic toe blood pressure >30 mmHg) or Transcutaneous Pression of O2 (TcPO2) is 30-60mmHg or other abnormalities on noninvasive testing, compatible with peripheral arterial disease but not with critical limb ischemia. Peripheral arterial disease is grade 3 (critical limb ischemia) if systolic ankle blood pressure is < 50 mmHg or systolic toe blood pressure is < 30 mmHg or TcPo2 < 30 mmHg.

The PEDIS classification for sensation is as follow: grade 1= a normal sensation, grade 2 = a loss of sensitivity to the monofilament, and grade 3= presence of a chronic Charcot foot.

Objective and outcome

The objective of our study was to determine mortality rate at 5 years. The secondary objective was to identify the independent predictors of five-year mortality in patients with diabetic foot ulcer.

Statistical analysis

Continuous variables are reported as mean ± standard deviation (sd) or median [Q1; Q3] and are compared using Wilcoxon rank sum test. Categorical variables are reported as number and percentage (percentages were calculated excluding missing data) and are compared by Chi-2 lcertest or Fisher's exact test, as appropriate. Missing data had not been imputed. Time to death after inclusion was analyzed using Kaplan Meier method. Estimate rate at 1, 3 and 5 years and their 95% confidence interval (CI) are presented. Patients who were known to be alive at five-year or lost-to follow up were censored at five years or at the last contact date. For some patients, information on death was known, but the date of death could not be recovered. In order to take these patients into consideration, 2 analyses were performed: these patients were considered as deceased at the latest available date of follow-up plus 1 day (primary analysis) and censored at the latest available date of follow-up (sensitivity analysis).

Risk factors of death were looked for among patients' and disease' characteristics (age, sex, ulcer duration, body mass index (BMI), lifestyle, type 2 diabetes, insulin treatment, diabetes duration, hemodialysis, active smoking, PEDIS perfusion, PEDIS sensation, University of Texas Diabetic Wound Classification System, acute hospitalization and ulcerduration during the first year of follow up (as time-dependent covariate) using Cox proportional Hazard model. Univariate analysis (p<0.15) were first performed to select potential explanatory variables that were subsequently tested in multivariate model (stepwise method). The results were interpreted in terms of adjusted hazard ratios (aHR) with their associated 95% CI.

A p-value <0.05 was considered significant. All statistical analyses involved the use of SAS release 9.4 (SAS Institute Inc, Cary, NC) statistical software package.

Results

Three hundred and forty-seven (347) patients were included. Five years after inclusion 49 (14%) patients were lost to follow up (Figure 1).

The main characteristics of the patients at inclusion are given in Table 1. Sixty eight % were male and mean age was 65 +/-12 years. Most patients were retired (62 %) and did not live alone (77 %). Eighty nine % had type 2 diabetes, 71 % were treated with insulin and duration of diabetes was 16 [10; 27] years. Fourteen % of patients were active smokers, 13% were on dialysis and 7 % had a organ transplant (4% a kidney and 3% a kidney-pancreas transplant).

Seventy % of patients had peripheral arterial disease (PAOD) and 17 % had grade 3 PAOD according to PEDIS classification (e.g. supplemental Table S1). Nine % of patients had grade 3 neuropathy (chronic Charcot foot) according to PEDIS sensation classification. 50% of patients were admitted to hospital at baseline for wound management.

Median wound duration at inclusion was 49 [19; 120] days. The distribution of ulcer gradation according to PEDIS classification and University of Texas Diabetic Wound Classification System is given in supplemental Tables S1 andS2.

Compared with patients not lost to follow-up (N=298), patients lost to follow up (N=49) had a longer ulcer duration at inclusion (66 [30; 155] versus 46 [18; 114] days; p=0.04), a more frequent grade 4 infection (6% versus 0.3%; p=0.018) and they required more frequently to be admitted (68 versus 48%; p =0.02). But they were not different for age, diabetes duration, severe comorbidity like dialysis or organ graft, and pedis perfusion classification.

According to Kaplan

Mortality rate

The five-year mortality rate was 35% [30; 41] (primary analysis). Mortality rate was 10% at year 1 and 25% at year 3. (Figure 2a).

Independent predictors of five-year mortality

Mortality at year 5 was associated with age, diabetes duration, dialysis, PEDIS perfusion grade, PEDIS sensation grade, wound University of Texas classification stages C,D and ulcer duration during the first year of follow up (Table 2). Independent predictors of five-years mortality were higher age, higher diabetes duration, PEDIS perfusion grade 2 or 3, and ulcer duration during the first year of follow up (Table 3). These results were consistent in the sensitivity analyze (data not shown).

Mortality rate according to PEDIS perfusion grade is shown in supplemental table S3 and survival curves in Figure 2b. Patients with grade 1 PEDIS perfusion (no peripheral arterial disease, neuropathic foot ulcer) had a survival rate of 100, 91 and 84% at respectively 1, 3 and 5 years.

Discussion

The 5-year mortality rate of patients presenting a new diabetic foot ulcer in the years 2009-2010 was 35%. The most appropriate study to make a comparison with our data is the one of Morbach and col [START_REF] Morbach | Long-term prognosis of diabetic foot patients and their limbs: amputation and death over the course of a decade[END_REF] on patients presenting with DFU in 1998-1999, because patients seems to be nearly comparable. Despite a bit higher rate of severe comorbidities in our cohort compared with Morbach's one (respectively 13% of patients on dialysis versus 4%, 70% of patients with peripheral arterial disease versus 55%) we found a lower mortality rate: 35% compared with 46%. Importantly in patients without peripheral arterial disease (isolated neuropathy) the mortality rate in our cohort is much smaller (16%) and twice as lower than in the Morbach's cohort (30%). The difference is smaller for patients with peripheral arterial disease, but presents: 43% compared with 59%. The mortality rate in our cohort is also lower than in others cohorts followed before the years 2010 [START_REF] Moulik | Amputation and mortality in new-onset diabetic foot ulcers stratified by etiology[END_REF][START_REF] Ghanassia | Long-Term Outcome and Disability of Diabetic Patients Hospitalized for Diabetic Foot Ulcers[END_REF]. These results suggest that life expectancy has improved in patients with diabetic foot ulcer.

Young and col in 2008 [START_REF] Young | Improved survival of diabetic foot ulcer patients 1995-2008: possible impact of aggressive cardiovascular risk management[END_REF] already suggested this increase in life survival in patients with diabetic foot ulcer. They even reported a low 27% mortality rate, but patients in their cohort were younger than in our (62 years old versus 65) with a shorter duration of diabetes (14 years) and a less frequent peripheral arterial disease (50%), all these factors influencing mortality.

Interestingly in a recent national observational study including patients with an active diabetic foot ulcer in the 2008-2011 years, identified from a diabetes register, the percentage of people who died during a 2 year follow up period was 16% [START_REF] Vadiveloo | Amputation-free survival in 17,353 people at high risk for foot ulceration in diabetes: a national observational study[END_REF], so next to the one observed in our study (see fig 2).

An improvement in life expectancy has been recently described in people with diabetes (type 1 and type 2) [START_REF] Rawshani | Mortality and Cardiovascular Disease in Type 1 and Type 2 Diabetes[END_REF]. This is probably explained by a combination of advances [START_REF] Tricco | Effectiveness of quality improvement strategies on the management of diabetes: a systematic review and meta-analysis[END_REF] among which a better management of cardiovascular risk factors. The first cause of mortality in patients with diabetic foot ulcer is a cardiovascular event which explains 50% to 75% of deaths [START_REF] Iversen | History of Foot Ulcer Increases Mortality Among Individuals With Diabetes[END_REF][START_REF] Young | Improved survival of diabetic foot ulcer patients 1995-2008: possible impact of aggressive cardiovascular risk management[END_REF][START_REF] Chammas | Increased Mortality in Diabetic Foot Ulcer Patients: the Significance of Ulcer Type[END_REF], and we can suppose that the better management of cardiovascular risk factors also regard these patients. Another explanation could be the improvement of foot ulcer management observed in the last years, with a lower rate of major amputation when patients are referred to diabetic foot ulcer centers, like in the current cohort where the major amputation rate was 10% at year 1 (data not shown). This may improve health related quality of life and decrease depression, two components that are predictive of mortality [START_REF] Williams | Depression and incident diabetic foot ulcers: a prospective cohort study[END_REF][START_REF] Winkley | Five-year follow-up of a cohort of people with their first diabetic foot ulcer: the persistent effect of depression on mortality[END_REF] in this population.

In our cohort, the strongest independent predictive factor of mortality at year 5 was severe peripheral arterial disease (grade 3 of the PEDIS classification), which is an expected risk factor for mortality [START_REF] Young | Improved survival of diabetic foot ulcer patients 1995-2008: possible impact of aggressive cardiovascular risk management[END_REF][START_REF] Morbach | Long-term prognosis of diabetic foot patients and their limbs: amputation and death over the course of a decade[END_REF]. It is assumed that the severity of peripheral arterial disease is a strong reflection of the general health and cardio-vascular patient's condition. Interestingly the wound duration during the first year was another important independent factor associated with 5-year mortality (HR: 2.09). To our knowledge, no previous studies have already tested the association with this variable. The persistence of a non-healed foot ulcer exposes to infection, but this is not a frequent cause of mortality, and PEDIS infection was not associated with mortality in our study (data not shown). It is more likely that a prolonged non healed ulcer reflects the presence of several factors that may increase the risk of death, like undernutrition, depression, carelessness and poor adherence to treatments. In the Eurodial study [START_REF] Siersma | Health-related quality of life predicts major amputation and death, but not healing, in people with diabetes presenting with foot ulcers: the Eurodiale study[END_REF] a low health-related quality of life (HRQoL) especially in the physical domain, was associated with death in people with DFU after adjustment for possible confounders. Authors suggested that strategies that improve mobility, reduce pain, and enable patient to better perform daily activities might have beneficial effects on the outcome, in addition to biomedical interventions focused on wound treatment. Depression which can reduce self-care is also associated with mortality at five years in people with diabetic foot ulcer [START_REF] Winkley | Five-year follow-up of a cohort of people with their first diabetic foot ulcer: the persistent effect of depression on mortality[END_REF].

The strengths of our study are the high number of patients, the prospective design and the low rate of lost to follow up. Weaknesses of our study are the monocentric recruitment, the absence of a comparative group, and the absence of data on drug therapies and causes of death.

Conclusions

In the years 2009-2010, mortality rate at year 5 of patients presenting with a new diabetic foot ulcer is not as high as observed before the 2000s, suggesting that these patients benefit of a better health care like all people with diabetes. This result emphasizes that diabetic foot ulcer should not be considered as a terminal illness, and that clinicians need to address risk factors for mortality aggressively in these patients to improve chances of survival. Particularly in patients with neuropathic foot ulcer, the chance to be still alive after five years is high: it concerns 84% of patients. Importantly, patients with a long duration non-healed ulcer are at high risk of mortality at five year independently of peripheral arterial disease and age. These patients could probably have benefit of a better global care, taking into account nutrition, psychological health and daily well-being, but this remains to be tested in future studies.

A.H. is the guarantor of this work and, has full access to all the data, and takes responsibility for the integrity of the data.

  Meier method, the non-healing rate at one year of follow up was 32.8% [27.4; 38.3].

Figure 1 :Figure 2 :

 12 Figure 1: Study Flow Chart Figure 2 : Kaplan Meier curve of survival, overall (a) and according to PEDIS Perfusion (b). Estimate rate [95% CI]

Figure 1 ! 2

 12 Figure 1

Table 1 . Baseline characteristics of patients (n=347

 1

	Data are expressed as mean +/-SD, median [Q1; Q3] or N (%)
	* Kaplan-Meier estimate [95% CI]

Table 2 :

 2 Predictors of five-year mortality

	Factors	Univariate analysis	Multivariate analysis*
		HR [95% CI]	aHR [95% CI]	p-
		p-value	value
	Age	1.06 [1.04; 1.08]	1.05 [1.03; 1.07]
	(per additional year)	<0.001	<0.001
	Sex (female vs. male)	1.16 [0.78; 1.72] 0.469
	Ulcer duration at baseline	0.999 [0.998; 1.00]
	(per additional day)	0.037
	BMI (kg/m²)	0.97 [0.93; 1.00]
	(per additional unit)	0.071
	Do not live alone	1.17 [0.73; 1.87]
	(vs. live alone)	0.515
	Type 2 diabetes	1.24 [0.67; 2.32] 0.496
	Insulin treatment	1.29 [0.84; 1.995] 0.251
	Duration of diabetes	1.02 [1.003; 1.03]	1.02 [1.001; 1.03]
	(per additional year)	0.021	0.032
	Hemodialysis	1.75 [1.05; 2.90] 0.031
	Active smoker	0.79 [0.43; 1.44] 0.433
	PEDIS Perfusion 1 3 2	<0.001 1.00 5.47 [2.89; 10.35] <0.001 3.02 [1.70; 5.38]	0.004 1.00 2.
		<0.001

35 [1.28; 4.29] 0.006 3.14 [1.58; 6.24] 0.001

	Acute hospitalization at baseline	1.03 [0.69; 1.55] 0.878
	Ulcer duration during the first year of follow up**	2.04 [1.37; 3.0.] <0.001	2.09 [1.35; 3.22] <0.001
	* N=319
	** time-dependent covariate
	aHR : adjusted Hazard Ratio
	PEDIS Sensation 1 2 3	0.030 1.00 1.30 [0.78; 2.19] 0.319 0.30 [0.09; 1.01]
		0.525
		<0.001
	TEXAS Classification	1.00
	A	0.81 [0.33; 2.01]
	B	0.649
	C	3.20 [1.75; 5.85]
	D	<0.001
		2.75 [1.51; 5.01]
		0.001

Acknowledgments

We thank Eli Lilly Company for having supported this work.

Funding

This work was supported by Eli Lilly Company.

Contribution statement

C.A. researched data and wrote the manuscript. A.C. researched data and wrote the manuscript. C.A. contributed to the discussion. O.B. reviewed the manuscript. C.A. researched data. T.C. researched data. E.F. researched data. G.H.V. helped design the study and researched data. SR carried out all statistical analysis and reviewed the manuscript. A.H. designed the study, wrote the manuscript and contributed to the discussion.


Gowrishankar Ganesh

Alejandro Melendez-Calderon

Masahiko Haruno

Mitsuo Kawato

Etienne Burdet

Transition between reciprocal activation and co-contraction during wrist posture control

come

Introduction

Our central nervous system (CNS) achieves mechanical interaction with the environment by controlling the force [START_REF] Shadmehr | Adaptive representation of dynamics during learning of a motor task[END_REF] and impedance [START_REF] Akazawa | Modulation of reflex EMG and stiffness in response to stretch of human finger muscle[END_REF][START_REF] Burdet | The central nervous system stabilizes unstable dynamics by learning optimal impedance[END_REF]) at the contact points of the limb. Roughly speaking, at a joint, torque is exerted by differential or reciprocal activation of the muscles spanning this joint, while impedance can be regulated by co-contracting antagonist muscle pairs. Therefore, the control of muscle reciprocal activation and co-contraction is central to motor control theories such as the equilibrium-point hypothesis [START_REF] Feldman | Functional tuning of the nervous system with control of movement or maintenance of a steady posture. III. Mechanographic analysis of execution by man of the simplest motor tasks[END_REF][START_REF] Bizzi | Posture control and trajectory formation during arm movement[END_REF][START_REF] Levin | Reciprocal and coactivation commands for fast wrist movements[END_REF][START_REF] Ostry | A critical evaluation of the force control hypothesis in motor control[END_REF]) and the internal model theory of simultaneous force and impedance control (Franklin et al. 2008).

Torque provides power to perform a task while mechanical impedance, the resistance to positional perturbations, helps stabilizing the system against disturbances. Therefore in usual movement tasks there are clear distinctions in the role of the reciprocal activation and cocontraction. However, the distinction becomes ambiguous in postural control tasks where both may be utilized to maintain posture against disturbances. While intuitively we may expect that co-contraction is used to attenuate unpredictable or 'high-frequency' disturbances and reciprocal activation for 'low frequency' disturbances, it is unclear when and how transition occurs between the two strategies.

To investigate this question we examined the electromyography (EMG) activity of wrist muscles in a posture control task where subjects experienced sinusoidal perturbations of different frequencies applied by a computer controlled manipulandum while they tried to maintain their wrist position. We compared the position, force and EMG subjects produce in this task with the activity they produce while performing the same movement by choice. The results show that even though subjects are able to control active reciprocal activations over a frequency of 3 Hz, they prefer to slowly shift from reciprocal activation to co-contraction while resisting external disturbance and as the disturbance frequency increases.

Methods and Materials

Subjects and Task

Five males right-handed subject aged between 23-29 years, without known pathology, participated in the study. The experiments were conducted according to the principles in the Declaration of Helsinki. The experiments were approved by the ethics committee at Imperial College and the subjects gave informed consent prior to performing them.

The subjects stood in an upright posture and had their forearm fixed firmly with straps to a wrist manipulandum constraining the movement along the flexion/extension axis (Fig. 1A). The subjects performed six 250-seconds long sessions: three resistive and three active sessions.

In the resistive sessions the subjects were given visual feedback of the wrist flexion/extension angle (blue cursor in Fig. 1B) and a target angle (±3 degrees, area enclosed by the two green polygons in Fig. 1B). They were instructed to "maintain the wrist angular position within and near the boundaries of the target" while the manipulandum imposed sinusoidal torque perturbations in the flexion-extension direction of three torque magnitudes {T1,T2,T3} corresponding to 0.2, 0.35 and 0.5 of maximum voluntary co-activation (MVCA), respectively.

The frequency of perturbation in each session varied from 0.4Hz to 3.5Hz. The order of frequencies were presented to the subject in a pseudo-random series {0.6, 1.9, 1.0, 2.8, 3.5, 0.4, 1.5, 1.2, 2.3, 0.8, 1.0, 3.5, 2.3, 0.6, 1.2, 0.4, 0.8, 1.9, 1.5, 2.8} Hz with each frequency presented twice in each session. Frequencies lower than 1Hz were presented for 10 cycles, while frequencies greater than 1Hz were presented for 10 seconds each.

The three active sessions served as control and were designed to compare the reciprocal activation and co-activation values when the actuations of similar load and frequency were made voluntarily by the subjects. In these sessions, the subjects were provided visual feedback not of their hand position, but of their wrist torque as a cursor (Fig. 1B). The subjects actively performed isometric wrist flexions-extensions such that the torque cursor amplitude touched the boundaries of the same target as the resistive sessions. The cursor position was determined by multiplying the instantaneous subject torque by 3/T1, 3/T2 and 3/T3 degree/Nm respectively so as to equalize the load to the resistive sessions. The frequency of the movement was regulated using a metronome with frequencies (and order) similar to the resistive sessions.

A rest period of few minutes was provided between sessions in order to avoid fatigue related effects. All subjects performed consecutive resistive and active sessions, though two performed the active sessions first and the rest performed the resistive session first.

Electromyography (EMG)

Surface EMG was measured from four wrist muscles: flexor carpi radialis (FCR), flexor carpi ulnaris (FCU), extensor carpi radialis bravis (ECRB) and extensor carpi ulnaris (ECU) which are the major contributors to wrist flexion and extension in a midway position [START_REF] Hoffman | Step-tracking movements of the wrist. IV. Muscle activity associated with movements in different directions[END_REF]Kakei et al. 1999;[START_REF] Haruno | Optimal control of redundant muscles in step-tracking wrist movements[END_REF]. After electrode position was determined for each muscle using functional movements, the area was cleansed with alcohol and abrasive gel (Nuprep, DO Weaver), and disposable pre-gelled adhesive electrodes were fixed to the subject's skin (inter-electrode distance ~1cm) (Fig. 1C). A ground electrode was fixed to the ankle of the subject. The EMG signals were pre-amplified using active clip connectors (g.GAMMAclip+g.GAMMABox, g.Tec) and amplified using a medically certified g.BSamp amplifier (g.Tec) before being fed into the manipulandum computer through a National Instruments data acquisition card (NI 6221) at 1 KHz and high-pass filtered at 20Hz. The filtered EMG was rectified and low pass filtered using a 2 nd order Butterworth filter with a 5Hz cut-off frequency to obtain EMG fcr , EMGf cu , EMG ecr and EMG ecu .

Subject specific load calculation and normalization

Each subject started the experiment by four repetitive calibration sessions separated by rest periods of 120 seconds. Each calibration session consisting of four parts: i) Relaxation -subjects were asked to not move and relax their forearms as much as possible.

The average muscle activity during this part was added up for the flexor and extensor muscles to obtain the rest period activations for the flexor (FLEX rest ) and extensor (EXT rest ) muscles.

ii-iii) Flexion-Extension -subjects were instructed to either flex or extend their wrist and keep a constant level of wrist torque while the device was blocked at 0 o . The torque level required from the subjects varied from 1-4Nm (i.e. 1Nm in session 1, 2Nm in session 2, and so on). A cursor was programmed to respond to individual torque measurements (scaling: 1Nm of applied torque moved the cursor of 4°), which provided subjects with visual feedback of the applied torque level. Subjects were asked to apply the force necessary to keep the cursor inside a target. iv) Co-activation -subjects were asked to co-activate maximally.

Each part of the calibration lasted for 4s, with 30s of rest time between parts. The last 2s of each recording were used to calculate the parameters for the normalization of flexors and extensor muscle groups. Relaxation, flexion and extension tasks were used to compute a linear relationship between torque and EMG activation levels. Next, the mean of the co-activation parts through the four calibration sessions was used to determine the maxima of voluntary co- activation decreases with increase of frequency. We quantify these differences in the following sections of the article.

Data analysis

Task performance

The subject performance, measured as the cursor position (representing manipulandum position and subject torque in resistive and active sessions respectively), was low pass filtered using a zero-lag second order Butterworth filter with 5 Hz cut-off frequency and rectified. As each disturbance period lasted for at least 10 cycles, at least 20 peaks are expected in the rectified cursor position profiles. Of these, the 10 peak values were collected from latter part of each disturbance period and the mean was calculated for each subject, session and for every frequency. The mean and standard error of the subject means was plotted as in Figs. 2 and3.

Note that the latter part of the disturbance period was considered in order to avoid any transition effects from the previous disturbance.

Reciprocal activation and co-contraction

We start the EMG analysis by the definition of these two terms. Note that in the last section we The RA and CC data from above were processed similar to the cursor position data. The mean of the peak 10 values from the latter part of each disturbance period were collected for each disturbance period and the average was calculated for each subject and for every frequency.

The mean and standard error of the subject averages were then plotted as in Fig. 3.

To compare the torque sensor readings with the reciprocal activation, we looked at the correlation between the two signals. To remove the delay between the muscle activity and the torque sensor signal, at each frequency, the correlation was repeatedly calculated by time shifting the torque signal between 0-100 ms. The maximum correlation during this process was noted for every frequency and subject. The subject average the standard error of the maximum correlation was plotted for the resistive and active sessions in Fig. 4A. The corresponding subject average of the time -shifts (delay between RA and torque signal) are plotted in Fig. 4B.

Results

Subjects' performance

Figure 2 shows the accuracy of subject performance in the resistive and active sessions. All subjects succeeded in performing the task in both the resistive (A) and active (B) sessions.

Irrespective of the task load (different colors) the subject cursor, representing wrist movement in the resistive and wrist torque in the active sessions, remained within the target area (brown dashed trace). In both the resistive and active sessions, while the cursor movement was not different across frequencies (resistive: p=0.95, active: p=0.86; 2 way ANOVA across all subject sessions and frequency), its amplitude was consistently larger at higher loads (resistive: p<0.017, act: p< 0.01; 2 way ANOVA across all subject sessions and loads). However, across the resistive the active sessions, there was no significant difference in cursor movement at each load (0.2 MVCA: p=0.93, 0.35 MVCA: p=0.77, 0.5 MVCA: p=0.16; 2 way ANOVA across subject sessions of similar load and frequency).

Reciprocal activation and co-contraction

In the resistive sessions (Fig. 3A) the reciprocal activation (upper panel) increased with increase in load (different color traces) and decreased with increasing frequency of disturbance (p<0.002 and p<0.001 respectively, 2-way ANOVAs across subject sessions and loads and frequencies).

On the other hand, while co-contraction similarly increases with load (p<0.001, 2-way ANOVAs across subject sessions and loads), it also increases with increase of frequency (p<0.001, 2-way ANOVAs across subject sessions and frequencies).

In the active sessions, the reciprocal activation (Fig. 3B, upper panel) increased with load (p<0.001, 2-way ANOVAs across subject sessions and loads) and frequency (p<0.006, 2-way ANOVAs across subject sessions and frequencies), while co-contraction (Fig. 3B, lower panel) increased with frequency (p<0.001, 2-way ANOVAs across subject sessions and frequencies); no significant difference was seen with increase of load (p=0.95, 2-way ANOVAs across subject sessions and loads).

Co-contraction was found to be consistently higher in the resistive sessions in comparison to the active sessions (0.2MVCA: p<0.001; 0.35 MVCA: p<0.001; 0.5 MVCA: p<0.001; 2 way ANOVA across subject sessions of similar load and frequency). We note that the trends of the total muscle activation, given by the summation of the flexor and extensor EMGs and corresponding roughly to mechanical impedance, were similar to that observed with co-contraction.

While reciprocal activation indicated the active torque applied by the subjects, we also had a torque sensor which measured the applied torque on the manipulandum handle. The correlation between recorded torque and reciprocal activation (Fig. 4A) indicated that, while in the case of the active sessions the correlation remained high through the frequencies, the correlation steadily decreased with frequency in the case of resistive sessions, indicating again the fading role of reciprocal activation in the perturbation compensation. The delay between the reciprocal activation and torque sensor increased with frequency in both the active and resistive sessions (Fig. 4B), which is consistent with previous studies on muscle physiology [START_REF] Patridge | Modifications of neural output signals by muscles: a frequency response study[END_REF].

Discussion

Our result showed that during posture control against random disturbances, the strategy changes with increasing frequency from that of reciprocal activation at low frequencies to cocontraction at higher frequencies. This gradual transition is not due to an impossibility to produce reciprocal activation at higher frequency. The active sessions clearly show that the subjects can perform reciprocal activation at higher frequencies. Interestingly, even in this case, the co-contraction increases with the frequency even when not directly required by the task.

This differential choice of the co-contraction and reciprocal activation can explain the trend of correlation between the torque sensor readings and reciprocal activation (Fig. 4A). The reading on the torque sensor provides us the external wrist torque measured. In the resistive sessions, this torque is produced by both the reciprocal activation and the stiffness of the wrist, which is related to the co-contraction produced by the subject. With increase of frequency, as the reciprocal activation decreases, the correlation with torque decreases. In contrast, cocontraction does not contribute to the task in the active sessions, correspondingly the torque signal is well correlated to reciprocal activation at all frequencies.

While the strategy employed by subjects differed with sessions, the subjects' performance (Fig.

2) were equally good in the active and resistive sessions. However, the cursor amplitude was consistently larger at larger loads. This observation may be explained by the fact that motor output variability increases with EMG magnitude, as motor noise generally increases with muscle activity [START_REF] Slifkin | Noise, information transmission, and force variability[END_REF].

It is interesting to observe co-contraction in the active isometric experiment when, as only reciprocal activation was required to perform this task. Co-contraction was observed (Fig. 3B)

to increase with the frequency. Control of reciprocal activation at higher magnitudes and frequencies requires co-contraction due to the physiology of muscle force development. The CNS controls muscle force by modulating the frequency of the action potentials in the motor units. Both build-up and fall off of force (at the onset/conclusion of neural) activity is slow [START_REF] Burke | Physiological types and histochemical profiles in motor units of the cat gastrocnemius[END_REF] and therefore, muscle force cannot follow rapid variations. To compensate for this, when rapid changes are required (like in the active isometric experiment), the CNS commands a higher burst of activity on the agonist muscles; this initial burst of activity would eventually lead to an overshoot in the force production unless it is compensated by a burst of activity in the antagonistic muscle (Kandel et al., 2000), giving rise to co-contraction.

In the resistive sessions, several additional factors could have also contributed to the increase of co-contraction. First, when performing a posture control task, the CNS responds to perturbations with reflexes whose gains can vary according to the task and change in the environment. Delay on the reflex response varies depending on its origin, e.g. 30ms for the monosynaptic reflexes, 50-80ms for the long-loop reflexes [START_REF] Evarts | Motor Cortex Reflexes Associated with Learned Movement[END_REF][START_REF] Hammond | The influence of prior instruction to the subject on an apparently involuntary neuro-muscular response[END_REF] or 110-150ms for visual reflexes [START_REF] Franklin | Specificity of reflex adaptation for task-relevant variability[END_REF]. As the nature of the task was to maintain the wrist at a given posture, the CNS may have modified reflex gains and utilized mechanisms of inhibition to the Ia inhibitory interneurons in order to build (or help building) cocontraction automatically [START_REF] Nielsen | The regulation of presynaptic inhibition during cocontraction of antagonistic muscles in man[END_REF]. In addition, the burst of activity produced by these reflexes on one muscle could start overlapping with the activity on the antagonist muscle when the perturbation changes direction, thus building up co-contraction.

Second, experiments in primates have shown that firing-rate modulation of both slow and fast twitching units depends on the frequency of the perturbation [START_REF] Humphrey | Separate cortical systems for control of joint movement and joint stiffness: reciprocal activation and coactivation of antagonist muscles[END_REF]. For slow perturbations, slow-twitch units begin to fire, but as the frequency increases, fast-twitch units start to interact and tonic co-activation drive on both flexors and extensors is increased.

Further, it is well known that motor noise increases with muscle activation [START_REF] Hamilton | The scaling of motor noise with muscle size and motor unit number[END_REF]). However, an increase of co-contraction has been shown to reduce motion variability [START_REF] Burdet | The central nervous system stabilizes unstable dynamics by learning optimal impedance[END_REF]) probably due to the faster increase of the muscle impedance than motor noise [START_REF] Selen | Can co-activation reduce kinematic variability? A simulation study[END_REF][START_REF] Kp Tee | Concurrent adaptation of force and impedance in the redundant muscle system[END_REF]). In addition, co-contraction is also known to increase the reflex response to perturbation in the stretched [START_REF] Akazawa | Modulation of reflex EMG and stiffness in response to stretch of human finger muscle[END_REF][START_REF] Carter | Nonlinear stretch reflex interaction during cocontraction[END_REF]).

Increase of co-contraction may thus also be a strategy utilized by the CNS to aid the control of the reciprocal activation to move the wrist.

Finally, the decrease in reciprocal activation at higher frequencies in the resistive sessions can be explained as follows. With the change of disturbance frequency the increase of cocontraction, due to all the above reasons, also leads to a fast increase of muscle impedance [START_REF] Selen | Can co-activation reduce kinematic variability? A simulation study[END_REF][START_REF] Kp Tee | Concurrent adaptation of force and impedance in the redundant muscle system[END_REF]). The increased impedance, in turn, 'takes over' the posture control task and enables the CNS to reduce reciprocal activation, which lack in efficiency at higher frequencies due to the muscle dynamics which have a cut off of 1.8Hz (Patridge 1966).

  Fig.1D,E show the normalized flexor and extensor EMG from one of the subject with the

  have normalized each muscle EMG by the external torque the muscle produces. Reciprocal activation may be thus defined as the differential antagonist muscle activation which leads to an active external wrist torque. Co-contraction is defined as the common antagonist muscle activation that does not lead to an external torque. Note that the definitions includes the voluntary activity produced by the subject and the involuntary reflexes in the muscles produced during perturbations.Reciprocal activation (RA) and co-contraction (CC) are thus calculated as:where EMG RA,fr and EMG CC, fr represent the reciprocal muscle activation and co-contraction at frequency fr. EMG flex and EMG ext represent the normalized flexor (Eq.1) and extensor EMG (Eq.2). filter(x,a), represents a Butterworth third order high pass filter of x with a cut-of frequency of a and min() takes the minimum of the two elements at any time instance. The high pass filter helped remove the co-contraction component from the EMG, while changing the cut-off frequency corresponding to the disturbance frequency helps to reduce any frequency dependent bias from the filter.

Fig. 1 :

 1 Fig. 1: Experimental setup. Subjects stood in an upright position with their forearm fixed to the

Fig 2 :

 2 Fig 2: Task performance. The target cursor amplitude across subjects, which corresponds to the

Fig. 3 :

 3 Fig. 3: Active and resistive behaviors. The mean (lines) and standard error (error bars) of

Fig4

  Fig4: A) Correlation between torque sensor signal and reciprocal activation EMG (EMG RA ) was