Frederic Anselme
email: frederic.anselme@chu-rouen.fr.

PhD Pierre Bordachar
email: bordacharp@hotmail.comjl-pasquie@chu-montpellier.fr

PhD Jean Luc Pasquié

PhD Didier Klug
email: didier.klug@chru-lille.fr

PhD Christophe Leclercq
email: christophe.leclercq@chu-rennes.fr

PhD Antoine Milhem
email: antoine.milhem@ch-larochelle.fr

MD Christine Alonso
email: christine.alonso@wanadoo.fr

MD Jean Claude Deharo
email: jeanclaude.deharo@ap-hm.fr

PhD Daniel Gras
email: dangras@aol.com

MD Vincent Probst
email: vincent.probst@chu-nantes.fro.piot@ccncardio.com

PhD Olivier Piot

MD Arnaud Savouré
email: arnaud.savoure@chu-rouen.fr

Frédéric Anselme
email: frederic.anselme@chu-rouen.fr

Safety, Feasibility and outcome results of Cardiac Resynchronization with Triple Site Ventricular Stimulation as compared to Conventional Cardiac Resynchronization

Keywords: cardiac resynchronization therapy, multisite pacing, congestive heart failure

Background:

The non-responders rate to cardiac resynchronization therapy (CRT) may be due to incomplete resynchronization as dyssynchrony can persist in about 30% of patients. We hypothesized that CRT with triple site ventricular stimulation (TRIV) may improve resynchronization and its outcomes.

Objective:

We assessed the feasibility and safety of TRIV and collected data on clinical outcomes to dimension future studies.

Methods: Our pilot randomized trial was designed to assess the safety and feasibility of TRIV with 2 right and 1 left ventricular leads as compared with conventional CRT. The primary endpoint was the rate of severe adverse events (SAE) at 6 months. Secondary endpoints included functional improvement parameters, quality of life (QOL) score, and changes of echocardiographic indices at 6 and at 12 months in a subset of patients.

Results: 76 patients were enrolled at 11 centers and randomized to control or TRIV arm. All implant procedures were successful but one. At 6 month, there was no statistical difference between proportions of patients with at least one SAE in both groups (34.1% vs. 25.7%, p=0.425). There was also no difference between functional improvement parameters, 6-minutes walking distances (p= 0.40), QOL scores (p = 0.27) and echographic indices. At 12 months, proportion of patients with a LVEF gain of more than 5%, 10 %, 15 % was significantly superior with TRIV.

Conclusion:

TriV pacing is an effective and safe technique and may provide a greater benefit on ventricular remodeling than conventional CRT. Further studies are needed to assess its long term benefit (NCT00887237).

Introduction

Cardiac resynchronization therapy (CRT) is a recommended treatment for selected patients with symptomatic heart failure (HF). Although most treated patients show a benefit from CRT, a lack of response is observed for about 25-30% of them [START_REF] Chung | Results of the Predictors of Response to CRT (PROSPECT) Trial[END_REF] whatever the response criteria used either based on the clinical status (NYHA class, clinical composite score) or on ventricular remodeling parameters assessed by echography (Left ventricle end of systole volume). This rate has remained remarkably stable since the therapy started and has motivated many studies to better understand the underlying physiopathology and the CRT action mechanisms.

Among the various research axes, increasing the number of pacing sites in an attempt to better homogenize the cardiac mechanical activity has been evaluated. A configuration with two RV leads and one LV lead was tested acutely in three studies [START_REF] Moubarak | First experience of intraoperative echocardiography-guided optimization of cardiac resynchronization therapy delivery[END_REF][START_REF] Yoshida | Effect of triangle ventricular pacing on haemodynamics and dyssynchrony in patients with advanced heart failure: a comparison study with conventional bi-ventricular pacing therapy[END_REF][START_REF] Anselme | Increase of responder rate at one year with triple site ventricular stimulation as compared to conventional cardiac resynchronization[END_REF] . In all cases, it demonstrated a significant improvement of cardiac performance whether assessed by echographic parameters or LV dP/dt measurements. First results with triple-site ventricular stimulation are encouraging and this approach might become a treatment option for CRT candidates provided its feasibility, safety and efficacy is demonstrated at larger scale. In the present study, we focused on the safety of this pacing configuration and collected data on clinical outcomes to dimension future studies.

Methods

This was a pilot, multicenter, prospective, parallel, randomized, controlled trial conducted in 11 French centers. All patients were informed and granted their written informed consent as approved by ethics committee. Patients were enrolled in the study if they were candidate to a de novo CRT-P or CRT-D. Criteria for inclusion into the study included LV dysfunction due to either ischemic or non-ischemic cardiomyopathy with an LV ejection fraction (LVEF) < 35%, New York Heart Association (NYHA) class II, III or IV functional status, and optimal medical therapy. Patients had to be in sinus rhythm with QRS duration > 120 milliseconds for NYHA class III and IV patients and > 150 milliseconds for NYHA class II patients [START_REF] Vardas | Guidelines for cardiac pacing and cardiac resynchronization therapy: the task force for cardiac pacing and cardiac resynchronization therapy of the European Society of Cardiology. Developed in collaboration with the European Heart Rhythm Association[END_REF][START_REF] Dickstein | Focused Update of ESC Guidelines on device therapy in heart failure: an update of the 2008 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure and the 2007 ESC guidelines for cardiac and resynchronization therapy[END_REF] . Patients with complete AV block were excluded. Enrolled patients were randomly assigned in a 1:1 fashion to receive either a standard CRT system with a bipolar LV lead and a RV lead positioned at the RV apex (Control group) or a TRIV system (test group) with two RV leads: one positioned at the apex, the other in a high septal position, at the level of the His bundle or above. Randomization occurred in blocks within centers. The septal RV and the bipolar LV leads were connected to the LV port using parallel Y-adaptor (Medtronic model 2872). This configuration was chosen to avoid any oversensing on the RV channel. Patients were blinded for the allocated intervention. At predischarge, patients underwent A-V delay optimization under echocardiographic guidance to maximize diastolic filling. VV delay was set to zero millisecond for all patients in both groups. Device programming was left to investigators discretion with the exception of the LV capture management feature that was left off.

Data collection

Patients underwent the following evaluations at baseline: NYHA functional class; 6-minute walking test; QOL evaluation using the Minnesota Living with Heart Failure Questionnaire (MLWHF); Echocardiography exam, which included measurement of LVEF, LV diastolic and systolic dimensions, end diastolic and systolic volumes (during all the study, echography exams were performed in a blinded fashion); and QRS width on 12-lead ECG. Duration of the procedure and acute electrical parameters values -pacing threshold and impedance, sensed signal amplitude -were collected. At each follow-up (FU) visit, pre-discharge and 6 months, the CRT system proper functioning was assessed. Threshold test in the TRIV group were performed using 12-lead ECG to better identify QRS morphology changes. Baseline variables were reevaluated three, and six months after randomization. Clinical composite score (CCS) [START_REF] Packer | Proposal for a new clinical end point to evaluate the efficacy of drugs and devices in the treatment of chronic heart failure[END_REF] was evaluated at 6 month FU. The echocardiography exam and electrical parameters measurements were repeated at 12 month for all patients included in Rouen. All adverse events (AE) were reported and adjudicated by an independent AE committee that reviewed events type, severity and system-relatedness. AE were defined according to ISO14155-2003.

Study endpoints

The primary objective of the study was to evaluate the safety of the TRIV configuration compared to standard CRT.

Primary end point was the rate of severe adverse events (SAE). Secondary end points included type, rate, severity and timing of adverse events (AE), survival and proportion of patients with continuous CRT delivery, clinical composite score, NYHA class distribution in both groups, 6 minute walking distance, QOL scores, changes of echocardiographic indices of LV remodeling at 6 months. For the subset of patients followed-up at 12 months, they were considered as responders to CRT if they were alive, gained one NYHA class and had an absolute LVEF increase of more than 5 %, 10%, 15%.

Statistics

Data were analyzed on an intention-to-treat basis. All p values reported are nominal, and all statistical tests are 2-sided. P value < 0.05 was considered statistically significant. Data were expressed as mean ± SD, if continuous, and as absolute and relative frequency, if categorical. Comparisons between continuous distributions were performed by means of 2-sample Student t test or Wilcoxon test when distributions were not normal. Categorical distributions were compared by using the 2 test or the Fisher exact test for small samples. Multinomial logistic regression was used to estimate whether CCS and NYHA distributions were influenced by the tested treatment. Survival, time to first AE, time to first SAE and time to first device-related AE curves were determined by the Kaplan-Meier method. Time 0 was the date of enrolment and patients not experiencing an event were censored at 6 months FU visit date. Comparison of the 2 study groups was done using the log-rank test.

Results

First patient was enrolled in June 2009, and last patient FU was completed in January 2013; 76 patients were randomized (TRIV = 35, control = 41). There were no significant baseline differences between groups (Table I). The mean LVEF was 28.7 ± 6.3 % and the mean LV end-diastolic volume was 208 ± 74 ml. The mean intrinsic QRS and PR interval duration were 162 ± 21 and 194 ± 42 ms respectively (31% of patients with a PR interval > 200 ms). CRT-Ds were implanted in two third of the patients population (65.8 %). Implant was attempted for all but one patient assigned to standard CRT group who died before implant. A prophylactic antibiotic therapy was administered prior implant to 87.8% and 94.3% of the patients in the control and Triv Group. All of the patients were implanted successfully but one for which a second attempt with LV epicardial lead placement was required. Mean procedure duration was slightly longer in the TRIV group (118 ± 50 versus 98 ± 37 minutes in the control group, p=0,066). Mean X-ray exposure durations were similar: 17.0 ± 12.7 versus 18.4 ± 11.9 minutes (p=0,504). Lead electrical parameters measured individually were also comparable with the exception of the LV pacing threshold that was slightly lower in the TRIV group (1.48 ± 0.85 V vs 1.12 ± 0.75 V at 0.5 ms). Loss of biventricular capture on the LV and septal RV leads connected with the Y-adaptor occurred at 1.47 ± 0.56 V at 0.5 ms (0.5 -2.75 V). This latter value remained stable at pre-discharge: 1.47 ± 0.88 V.

QRS durations decreased in both groups versus baseline : 144 ± 26.5 versus 136 ± 19.4 in control and TRIV group respectively (p=0.16). Of the 41 patients assigned to the control group, 3 did not complete six months FU -2 died, and six months of FU. No patient was lost to FU for the analysis of SAE. All patients continued to receive the assigned treatment for the intended duration of the study. Pacing thresholds remained acceptable throughout the entire study duration for most of the patients. TRIV pacing could be achieved for all of the patients with this pacing configuration however threshold was superior to 4.5 V / 0.4 ms for four of them.

Primary end point

At 6 month FU, there was no statistically significant difference between proportions of patients with at least one SAE in the control and TRIV groups (respectively 34.1% vs. 25.7%, p=0.425). Time to first SAE is presented in Figure 1. The probability of first SAE occurrence was similar in both groups (log rank test, p=0.52). In particular, device related infection rates were similar, with one infection in each group.

Secondary end points:

As for SAE, proportions of patients with at least one AE were similar in both groups (56.1 % in control versus 42.9% in TRIV group, p=0.25). This was also true for mortality (4.9% versus 5.7%). None of the reported deaths were procedurerelated; all were due to terminal heart failure. Time to first AE, to first system-related AE and to death were similar for both groups (log rank test, p=0.46, p=0.79, p=0.88 respectively).

A majority of patients (81.6%) were free of any interruption of CRT delivery or occurrence of side effects. Proportion of patients with at least one system-related AE was equivalent in Control and TRIV group (19.5% and 17.1% respectively, p=0.79).

Six-month CCS distributions were similar between control and TRIV group (p= 0.90) with a quite large proportion of responders to the therapy. Same observation was done for NYHA class distributions (p= 0.86) as well as for 6-minutes walking distance (p= 0.40) and QOL score (p = 0.2; Table II). At 6 month FU, there was no significant difference between the indices of LV remodeling observed in both groups: LVEF and LV dimensions improved in similar proportion (Table III).

In the subset of patient followed-up at 12 months, there was no difference regarding proportion of patients with SAE (60% for controls versus 50% for TRIV patients). Compared to baseline, the improvement of the 6 minutes walking distance was not significant and was similar in both groups. QOL score improved significantly only in the TRIV group (p=0.03). LVEF and changes of LVEF was significantly superior in the TRIV group compared to the control group. Also the proportion of responders' patients with LVEF gain of more than 5 %, 10 %, and 15 % was significantly superior in the TRIV group (Table IV). Finally there was a trend towards a greater proportion of patients with LVESV decrease of more than 15% and 25% in the TRIV group as compared to controls (85% versus 66%; 69% versus 47% respectively).

Discussion

This is the first chronic prospective randomized study comparing conventional biventricular and TRIV pacing with the use of two RV leads.

Feasibility:

We demonstrated that implanting an additional RV lead for CRT is feasible and safe, and does not interfere with the proper device functioning including tachyarrhythmia management. Conversely to other multi -site pacing approaches using two LV leads, where procedure feasibility may be limited by the ability to successfully implant the second LV lead in a stable and appropriate position, our implant success rate was of 100%. Noteworthy, this was achieved without significantly prolonging procedure duration, highlighting the easiness of the implant technique. This was expected as the main driver for procedure duration is most of the time related to LV lead implantation. In published series on dual LV pacing, the implant success rate ranged from 85 to 100% [START_REF] Leclercq | A Randomized Comparison of Triple-Site Versus Dual-Site Ventricular Stimulation in Patients With Congestive Heart Failure[END_REF][START_REF] Lenarczyk | Triple-site biventricular pacing in patients undergoing cardiac resynchronization therapy: a feasibility study[END_REF][START_REF] Lenarczyk | Implantation Feasibility, Procedure-Related Adverse Events and Lead Performance During 1-Year Follow-Up in Patients Undergoing Triple-Site Cardiac Resynchronization Therapy: A Substudy of TRUST CRT Randomized Trial[END_REF] . In study by Lenarczyk et al., implantation of a second LV lead resulted in a 30 min prolongation of procedure duration associated with a significant increase in X-ray exposure [START_REF] Lenarczyk | Implantation Feasibility, Procedure-Related Adverse Events and Lead Performance During 1-Year Follow-Up in Patients Undergoing Triple-Site Cardiac Resynchronization Therapy: A Substudy of TRUST CRT Randomized Trial[END_REF] .

In addition, TRIV was appropriately delivered throughout the entire FU duration. Although the Y connector enlarged the pocket size and limited the choice of LV lead pacing vectors, we did not observe a significant increase in device related AE. Of importance, as already mentioned by Lenarczyk, device related infection rate was low: only one was reported in each group. However, we cannot strongly conclude on this point as the design of our study did not allow capturing longterm potential system-related infections. There is compelling evidence from long-term FU in large populations showing that infection risk increases with the number of leads and the number of re-operations. High ventricular thresholds were observed in only four patients in the TRIV group. This is likely related to the dissipation of part of the delivered pacing energy through the Y connector. A dedicated 4-channels device would definitely overcome these problems. In any case, the use of an additional pacing site will necessarily result in an increase of energy consumption which consequently will alter battery longevity.

Increasing the number of implanted leads could promote vein thrombosis. Even though this was not systematically assessed, no clinical symptoms related to such an event were reported.

Clinical impact:

At 6 month FU, QoL, 6 min walking test and CCS evaluation significantly improved in both study groups. Conversely to what has been observed in TRIP HF study, we did not observe any additional clinical benefit provided by the TRIV pacing configuration at the time of FU. However, we did observe a significant improvement of LVEF and a trend towards a greater proportion of patients with LVESV decrease in the subset of patients followed up at 12 months. Proportion of responders was significantly higher in the TRIV group whatever the defined threshold value for LVEF changes (5%, 10%, 15%). This reflects the fact that not only the long term response rate to CRT is higher but also the amplitude of response (super-responder rate) is much greater in the TRIV group as compared to the conventional group. It appears that the additional benefit of TRIV configuration requires time to be detected as if the effect of TRIV lasted much longer than BIV on ventricular remodeling. This would explain by itself both the greater response rate and the greater LVEF improvement associated with TRIV. Some authors tested dual RV pacing alone. It appears to produce a beneficial clinical response in CRT candidates on an acute and long-term basis 11 . However, the remodeling effect of bifocal RV pacing is generally inferior to that of conventional biventricular pacing [START_REF] Barold | Is bifocal right ventricular pacing a viable form of cardiac resynchronization?[END_REF] . Several studies have been performed on the positioning of RV and LV pacing leads and their influence on the quality of resynchronization. Some authors compared septal versus apical positioning of the RV lead without demonstrating any difference in terms of clinical outcomes [START_REF] Kristiansen | A randomized study of haemodynamic effects and left ventricular dyssynchrony in right ventricular apical vs. high posterior septal pacing in cardiac resynchronization therapy[END_REF] . Others proposed to optimize RV lead positioning based on the echographic measurement of the aortic pre-ejection delay 2 while others positioned the LV lead at the site of the latest mechanical activation [START_REF] Saba | Echocardiography guided left ventricular lead placement for cardiac resynchronization therapy: results of the Speckle Tracking Assisted Resynchronization Therapy for Electrode Region trial[END_REF][START_REF] Khan | Targeted left ventricular lead placement to guide cardiac resynchronization therapy: the TARGET study: a randomized, controlled trial[END_REF][START_REF] Zanon | Determination of the longest intrapatient left ventricular electrical delay may predict acute hemodynamic improvement in patients after cardiac resynchronization therapy[END_REF][START_REF] Adelstein | Effect of echocardiographyguided left ventricular lead placement for cardiac resynchronization therapy on mortality and risk of defibrillator therapy for ventricular arrhythmias in heart failure patients (from the Speckle Tracking Assisted Resynchronization Therapy for Electrode Region [STARTER] trial)[END_REF] . Benefit of these approaches could be demonstrated through single centers studies. However, their implementation can be limited by constraints of the cardiac venous anatomy and may not be easy to reproduce at larger scale on a practical standpoint. Advanced echo measurements to detect sites of latest mechanical activation may be technically challenging [START_REF] Saba | Echocardiography guided left ventricular lead placement for cardiac resynchronization therapy: results of the Speckle Tracking Assisted Resynchronization Therapy for Electrode Region trial[END_REF] . 17. In addition their reproducibility remains arguable [START_REF] Chung | Results of the Predictors of Response to CRT (PROSPECT) trial[END_REF] . LV endocardial pacing looks promising [START_REF] Auricchio | Feasibility, safety, and short-term outcome of leadless ultrasound-based endocardial left ventricular resynchronization in heart failure patients: results of the Wireless Stimulation Endocardially for CRT (WiSE-CRT) study[END_REF] even though it requires lifelong anti-coagulation treatment. A larger scale evaluation is now required to ensure procedure and long-term safety and evaluate more precisely clinical outcomes.

It has been also proposed to reduce the number of pacing leads seeking for LV fusion. This pacing configuration, mainly dedicated to patients with LBBB, normal AV and RV conduction, could be an attractive option but its interest is not yet strongly demonstrated [START_REF] Martin | Investigation of a novel algorithm for synchronized left-ventricular pacing and ambulatory optimization of cardiac resynchronization therapy: results of the adaptive CRT trial[END_REF] .

Last, several authors proposed to increase the number of pacing sites in order to improve CRT effectiveness. One of the reasons for the lack of response to conventional CRT may be the presence of functional or fixed lines of conduction block within the left ventricle and slow ventricular activation. This latter could be due to slow electrical interventricular conduction or abnormal electro-mechanical coupling. Multiplying the pacing points could potentially overcome all of these patho-physiological abnormalities and significantly shorten the global LV activation time. With the advent of quadripolar LV leads, initially proposed as a mean to avoid phrenic nerve stimulation, some preliminary data suggest that they could also provide hemodynamic benefit [START_REF] Osca | The Use of Quadripolar Left Ventricular Leads Improves the Hemodynamic Response to Cardiac Resynchronization Therapy[END_REF] . The latter could be related to the ability to pace from the basal or mid-LV region without compromising lead stability. Although the four poles are close together, it may also be related to the ability to simultaneously pace from all electrodes [START_REF] Zanon | Multipoint Pacing by a Left Ventricular Quadripolar Lead Improves the[END_REF] . The impact on CRT efficiency remains to be proven chronically on large scale (MORE CRT MPP study; NCT02006069). A better mechanical resynchronization may be obtained using a third ventricular lead remotely positioned from the others. Several pacing configurations have been tested including either an additional LV or RV lead. A configuration with two LV leads was evaluated in two studies performed on de novo patients [START_REF] Leclercq | A Randomized Comparison of Triple-Site Versus Dual-Site Ventricular Stimulation in Patients With Congestive Heart Failure[END_REF][START_REF] Lenarczyk | Triple-site biventricular pacing in patients undergoing cardiac resynchronization therapy: a feasibility study[END_REF] with promising results on the echographic and clinical parameters. We believe that the 2RV+1LV approach is not so different than the 1RV+2LV approach in terms of resynchronization effect. Provided that the pacing leads are positioned far enough one from each other, the paced areas would be close: a high septal RV lead would be near to a LV lead positioned in the great cardiac vein, while an apical RV lead would be near to a LV lead positioned in a posterior/postero-lateral vein. According to electrical and anatomical characteristics, one approach rather than the other might suit better to a given patient.

Study limitations

The size of the population precludes drawing any definite conclusion on the clinical relevance of this technique. This was a pilot study designed to validate feasibility and build hypothesis for future studies. The pre-specified efficacy endpoints demonstrated no significant difference at 6 months while we observed a significant impact of TRIV pacing on a smaller sample at 12 months. Although it is possible that this technique may only convey modest incremental benefits, we still believe it is worth to perform a larger and longer term study to demonstrate its superiority. Echocardiographic evaluation was not performed in a core lab. All of the exams were done in a blinded fashion even though the sonographer may have visualized the leads. Most of the patients were enrolled in Rouen. However a potential center effect in the study results was ruled out. Also, only patients enrolled in Rouen were followed-up at one year. This implied lack of patient selection bias and only limited variations in echo measurements method in this subset of patients.

Conclusion

Our study supports TriV pacing as an effective and safe tool to improve patient clinical status. Larger studies are needed to assess the long term clinical benefit of this new pacing modality.

Acute Hemodynamic

Clinical perspectives

This is the first chronic prospective randomized study comparing conventional biventricular and triple site ventricular pacing with the use of two RV leads (TRIV). Our study supports TRIV as an effective and safe tool to improve patient clinical status. Development of new device technology is required to limit the drawbacks induced by the addition of a third lead and its impact on battery longevity (multi-port can). Although at mid-term follow-up, there was no significant difference between groups regarding clinical status, we observed an encouraging trend towards a better LV remodeling at 1-year in the TRIV group. The additional benefit of TRIV configuration may require time to be detected as if the effect of TRIV pacing lasted much longer than BIV on ventricular remodeling. This would explain both the greater response rate and the greater LVEF improvement associated with TRIV we found in our study. A larger and longer term study is needed to demonstrate the potential superiority of this pacing technique over conventional CRT in order to be translated into daily clinical practice.

All

1

 1 Response to CRT Compared with Conventional Biventricular Pacing at any Site. Heart Rhythm. 2015 May;12(5):975-81. : Proportion of patients free from severe adverse event Title figure Kaplan-Meier estimates of the time to first severe adverse event

Table I :

 I Population characteristics at baseline ± 16.2 35 37.2 ± 18.1 0.73 36 29.6 ± 23.2 33 22.2 ± 16.1 0.27

						Control		TRIV		p
	n			76		41			35
	Age (year)			69.4 ± 10.7	69.9 ± 10.5		68.9 ± 11.2	0.71
	% male			71.1%		61%		82.9%		0.04
	Ischemic heart disease (%)			43.4%		43.9%		42.9%		0.93
	Paroxysmal AF (%)			26.3%		26.8%		25.7%		0.91
	QRS duration (ms)			162 ± 21		160 ± 21		164 ± 21		0.20
	CRT-D proportion (%)			65.8%		63.4%		68.6%		0.64
	NYHA class % II % IV % III			6.6% 7.9% 85.5%		12.2% 7.3% 80.5%		0% 8.6% 91.4%		0.09
	LVEF (%)			28.7 ± 6.3%	29.6 ± 6.3 %	27.7 ± 6.4 %	0.12
	LV end of diastole volume (ml)			202 ± 70.7		208 ± 73.8		195 ± 67.5		0.55
	LV end of systole volume (ml)			145 ± 58.9		147 ± 61.8		144 ± 56.4		0.96
	LV end of diastole diameter (mm)		66.7 ± 9.76	66.9 ± 10,5		66.5 ± 8.99	0.86
	LV end of systole diameter (mm)		57.4 ± 11.5	58.6 ± 11.6		55.9 ± 11.4	0.31
	6 minute walking distance (m) / n	309 ± 111 / 66	304 ± 98 / 36	315 ± 125 / 30	0.68
	QOL score			37.2 ± 18.1	36.5 ± 19.8		38.0 ± 16.2	0.73
				Baseline				6 month FU
		n	Control	n	TRIV	p	n	Control	n	TRIV	p
	Clinical composite score: % Improved % Worsened % Unchanged						38	81.6% 5.2% 13.2%	33	78.8% 3.0% 18.2%	0.90
	NYHA class:
	% I		0%		0%			21.1%		18.2%
	% II	41	12.2%	35	0%	0.09 38	55.3%	33	63.6%	0.86
	% III		80.5%	91.4%			23.7%		18.2%
	% IV		7.3%		8.6%			0%		0%
	6 min. walking distance (m)	36	304 ± 98	30 315 ± 125	0.68 33	377 ± 97	32 355 ± 117 0.40
	QOL Score	41 38.0

Table II :

 II Functional status at baseline and 6 month FU

Acknowledgements

This study was sponsored by Medtronic.


Philippe Rauffet
email: philippe.rauffet@univ-ubs.fr

Christine Chauvin
email: christine.chauvin@univ-ubs.fr

Gael Morel
email: gael.morel@univ-ubs.fr

Pascal Berruet
email: pascal.berruet@univ-ubs.fr

Designing sociotechnical systems: a CWA-based method for dynamic function allocation

Keywords: Cognitive Work Analysis, Design method and tools, Social Organization and Cooperation Analysis, Dynamic Function Allocation. ACM Classification H.1.2 User/Machine Systems (Human factors). I.5.2 Design Methodology

Dynamic function allocation (between human agents or between human and technical agents) is a crucial issue in complex sociotechnical systems, particularly in changing or demanding situations. This issue has not yet been explicitly addressed in the Cognitive Work Analysis framework. This paper presents a conceptual and methodological proposal for designers that supplements the existing CWA tools. The new tool is integrated into the Social Organization and Cooperation Analysis (SOCA) stage. It formalizes different kinds of associations between work functions and elementary work situations and between resources and work functions. It enables the identification of conflicts (impossible allocations) when examining a complex situation resulting from the conjunction of several elementary situations. When conflicts are resolved, it is possible to choose the best configuration among a set of possible associations between resources and work functions. This proposal is illustrated with the case study of an electric pedal-assist bike.

INTRODUCTION

Socio-Technical Systems Engineering (STSE) focuses on the design of complex systems with interconnected human, technical, and organizational components [START_REF] Baxter | Socio-technical systems: From design methods to systems engineering[END_REF]. In particular, this approach raises the issue of the role of operators faced with increasingly autonomous technical systems in dynamic, risky, and sometimes unforeseen situations.

The distribution of activities between humans and machines is a central process in Socio-Technical System (STS) design and operation [START_REF] Challenger | Function allocation in complex systems: reframing an old problem[END_REF]. Function allocation and, more precisely, dynamic function allocation (DFA), can help a system maintain a satisfying performance in complex situations. This issue must be taken into account as early as the preliminary design phase of a project [START_REF] Mod | Defence Standard 00-25[END_REF][START_REF] Goom | Function allocation and MANPRINT[END_REF].

Several methods have been proposed to design sociotechnical systems. Among them, Cognitive Work Analysis (CWA), proposed by [START_REF] Rasmussen | Information Processing and Human-machine Interaction[END_REF], [START_REF] Rasmussen | Cognitive Systems engineering[END_REF] and further developed and codified by [START_REF] Vicente | Cognitive work analysis: Toward safe, productive, and healthy computer-based work[END_REF], appears as one of the most comprehensive. It combines the contributions of engineering and human factors to provide designers with a powerful framework for STS design. As depicted on table 1, it is a formative constraint-based approach, consisting of five successive stages: a) Work Domain Analysis (WDA), b) Control Task Analysis (ConTA), c) Strategies Analysis (StrA), d) Social Organization and Cooperation Analysis (SOCA), and e) Worker Competencies Analysis (WCA).

The issue of function allocation is addressed at the fourth stage, namely SOCA. This issue is a crucial one, but the exploration of the social and organisation phase has received less attention than the application of the WDA or ConTA [START_REF] Jenkins | Using cognitive work analysis to explore activity allocation within military domains[END_REF].

SOCA does not deal explicitly with the dynamic distribution of functions between humans and machines [START_REF] Chauvin | Integration of Ergonomics in the Design of Human-Machine Systems[END_REF]. No modelling tools existed for this stage before the recent proposals made by [START_REF] Jenkins | Using cognitive work analysis to explore activity allocation within military domains[END_REF] or [START_REF] Stanton | How a submarine returns to periscope depth: Analysing complex sociotechnical systems using Cognitive Work Analysis[END_REF]. In this paper, we propose to make up for these weaknesses.

This paper aims at improving the SOCA stage and at integrating explicitly DFA into the CWA framework. It proposes a tool for designers that will enable them to verify that a particular solution will meet the purpose of the system, regardless of the work situation.

It is divided in three parts. The first one presents, among the CWA levels and associated tools, those that provide useful data for function allocation; it also shows the limits of the existing tools. The second part introduces the methodological proposal. The last part provides a case study in order to illustrate and discuss the anticipated benefits. WDA deals with the constraints that are placed on actors by the functional structure of the field or environment in which the work occurs [START_REF] Naikar | Work domain analysis: Concepts, guidelines, and cases[END_REF]. This phase is associated with a modelling tool, the AH. This tool enables the description of a work domain in terms of five levels of abstraction: functional purpose (the purpose of the work domain, its "raison d'être"), value and priority measures (the criteria ensuring that the system progresses toward the functional purpose), purpose-related functions (the general functions that are performed in order to achieve the functional purpose), object-related processes (processes and capabilities characterising the objects used by the general functions), and physical objects.

ConTA is related to the activity required for achieving a system's purpose with a set of specific resources. Naikar, Moylan, and Pearce (2006) and [START_REF] Naikar | Work domain analysis: Concepts, guidelines, and cases[END_REF] propose to characterize this activity as a set of recurring work situations, work functions, or control tasks. These authors introduce the CAT for modelling activities in work systems. This template highlights the contextual relationships between the various elements of ConTA and graphically illustrates all of the combinations of work situations, work functions, and control tasks that are possible. [START_REF] Naikar | Analysing activity in complex systems with cognitive work analysis: concepts, guidelines and case study for control task analysis[END_REF] explain that the decomposition of activity into work situations is appropriate in systems where work is segmented according to time and space (in hospitals or schools for example), whereas activity is better characterized by its content, independently of its temporal of spatial characteristics, in other systems. In those cases, it is appropriate to decompose activity into a set of work functions. Work functions are related to functions to be performed in a work system. They are defined at the purpose-related functions level or at the object-related processes level in the AH [START_REF] Jenkins | Using cognitive work analysis to explore activity allocation within military domains[END_REF]. In a research laboratory, activity is divided into work functions such as writing papers, conducting experiments, and reading.

The CAT is designed to represent activity both in terms of work situations and work functions. A graphical code is used to distinguish work situations in which a work function can occur and those in which a work function will typically occur. According to [START_REF] Stanton | How a submarine returns to periscope depth: Analysing complex sociotechnical systems using Cognitive Work Analysis[END_REF] and as depicted in Figure 1, a work function -in a given situation -may be qualified as expected (it can occur and typically occurs), optional (it can occur but does not typically occur), or impossible (it never occurs). The decision ladder is then used to decompose activity into a set of control tasks for each work situation and/or work functions.

SOCA addresses the constraints governing how the team communicates and cooperation [START_REF] Jenkins | Using cognitive work analysis to explore activity allocation within military domains[END_REF]. It aims to determine the distribution of work demands, communication, and cooperation amongst the actors (i.e. the different resources of the system under investigation). [START_REF] Jenkins | Using cognitive work analysis to explore activity allocation within military domains[END_REF] propose to map actors (represented by means of a colour code) onto the AH and more precisely onto the functions described at the levels of the purposerelated function and of the object-related processes (SOCA-AH). In the same way, they map actors onto the CAT in order to show where these can have an influence on the system (SOCA-CAT). They take into account, at this stage, the actors' capability to perform a certain work function during a certain work situation. Cells occupied by more than one actor indicate that either or all of the identified actors can support the activity. According to these authors, this representation of constraints helps to identify and evaluate potential combinations of working practices in order to determine optimal practices. This analysis may be carried out according to Rasmussen et al.'s (1994) six criteria: (a) actor competencies, (b) access to information and means of action, (c) coordination demands, (d) workload, (e) safety and reliability, and (f) existing regulations. These criteria are either input data to model DFA problems (e.g. actor competencies) or evaluation criteria to choose allocations (e.g. workload).

The existing tools of the CWA enable the identification of potential allocations of resources to work functions. However, they do not provide the means to evaluate and optimize these according to the work situation characteristics and, most importantly, according to the work situation variations.

SOLVING DYNAMIC FUNCTION ALLOCATION PROBLEMS WITH CWA

Defining a dynamic function allocation entails taking dynamic situations and resource availability into account. For that purpose, designers need a definition of work situations and a modelling of resource constraints adapted to the specific problem, as well as a method used to formalize and to evaluate the STS according to different complex situations.

The notion of work situation seems to be very useful to deal with the question of DFA although its "modern" definition [START_REF] Naikar | Analysing activity in complex systems with cognitive work analysis: concepts, guidelines and case study for control task analysis[END_REF], used in the works of [START_REF] Jenkins | Using cognitive work analysis to explore activity allocation within military domains[END_REF][START_REF] Stanton | How a submarine returns to periscope depth: Analysing complex sociotechnical systems using Cognitive Work Analysis[END_REF] was not originally thought to model this specific problem. The use of this concept for DFA problems raises therefore new questions: [START_REF] Naikar | Analysing activity in complex systems with cognitive work analysis: concepts, guidelines and case study for control task analysis[END_REF], work situations are characterized by some absolute or relative constants of time or location (work can occur at a specific place or at a specific distance of a moving position, and work can occur at a specific moment or just before or after a mission phase). For instance, in the context of aircraft system analysis, [START_REF] Naikar | Analysing activity in complex systems with cognitive work analysis: concepts, guidelines and case study for control task analysis[END_REF] described five different situations fitting with mission phases ("on ground not in aircraft", "on ground in aircraft", "enroute to station", "on station", "enroute to base"). However, could the situation "flying in bad weather conditions" be considered as a spatio-temporal situation? This kind of work situation can occur at any place and any time, as there is no unit of time and place, or relationship with a mission phase or a moving place. [START_REF] Cuny | Decision-making in controlling development of driving/piloting situations[END_REF] remind that "in ergonomic psychology, the situation theoretically includes all variables forming a system of potential interactions with the activity as its operational framework". Work situations can be therefore more generally influenced and characterized by the external and internal conditions of the system (the information level or the nature of the system environment, temporal pressure, etc.). "When" and "where" questions should be thus completed or replaced by the question "In which internal and external conditions does the system operate?" so as to define work situations.

Are time and location sufficiently detailed to distinguish all the work situations? According to

Do work situations include incidental or critical situations?

The recent applications of the CAT [START_REF] Jenkins | Using cognitive work analysis to explore activity allocation within military domains[END_REF][START_REF] Stanton | How a submarine returns to periscope depth: Analysing complex sociotechnical systems using Cognitive Work Analysis[END_REF]) are centred on nominal phases of the mission. However, the dynamic function allocation could also take some degraded situations into account (the failure of some system components, uncertainty or absence of knowledge regarding information relative to the mission, etc.).

Are work situations independent from each other?

The different work situations are independent from each other if they are defined according to time or location. However, if we also consider work situations according to internal and external conditions, the situations « enroute to station » and « flying in bad weather conditions » could occur in parallel. [START_REF] Naikar | Analysing activity in complex systems with cognitive work analysis: concepts, guidelines and case study for control task analysis[END_REF] assert that the decomposition of activity into work situations and work functions can be done at different levels of detail or granularity. They provide an example of this granularity issue. Situations such as "On ground not in aircraft", "On ground in aircraft", and the "in the air" situations ("enroute to station" and "enroute to base") are typically the conjunction of two elementary situations, defined by the location of the activity in relation to the plane and to the ground ("on ground" versus "in the air", "in aircraft" versus "not in aircraft"). The different elements of internal and external conditions could therefore be a unit of description of work situations.

What is the granularity of the modelling of work situations?

How can forgetting work situations and a combinatorial explosion of situations be avoided?

The number of situations could increase very fast if numerous conditions are considered and combined. For instance, taking into account the weather conditions (cloudy or sunny), tactical conditions (in fight zone, not in fight zone) and system capacity conditions (full tank of fuel, almost empty tank) and the five situations given by [START_REF] Naikar | Analysing activity in complex systems with cognitive work analysis: concepts, guidelines and case study for control task analysis[END_REF] results in having to consider and model 40 different situations. Complex situations should be considered as the result of the conjunction of several elementary situations that are not always independent from each other.

The modelling of resource availability in dynamic situations is also a crucial question for dealing with DFA issues. [START_REF] Jenkins | Using cognitive work analysis to explore activity allocation within military domains[END_REF] and [START_REF] Stanton | How a submarine returns to periscope depth: Analysing complex sociotechnical systems using Cognitive Work Analysis[END_REF] propose to map resources and actors, especially on the AH and CAT. However, they do not formalize in detail the constraints that can occur between these resources in dynamic situations, which is necessary to define the DFA problem. Selecting to allocate a resource to a function could be dependent on the use of this resource or another one for another function. This relation of dependence among resources can be expressed at the design stage (modelled in SOCA-AH) or in the case of a situation that creates some unavailability or dependence (modelled in SOCA-CAT). The following list represents an attempt to model these constraints: a) binary constraints: a resource can be allocated or not to a function; b) disjunctive constraints: one or several resources can be allocated to the same function; c) exclusive constraints: two resources cannot work in parallel on the same or on different functions; d) capacity constraints: the number of functions allocated to one resource or both resources is limited; e) conditional constraints: a resource can be allocated to a function only if one or several resources are allocated to one or several functions; f) antecedence constraints: this is a special case of conditional constraints to which a temporal dimension has been added; a resource may be allocated to a function only if one or several resources were previously allocated to one or several functions. Using these elements of detail or adaptation of CWA leads to proposing a method using SOCA-AH and SOCA-CAT models and SOCA criteria so as to formalize and solve the DFA problem.

SOCA-AH is centred on the analysis of functions and resources and would be used to assess the choices made by the designers regarding the composition of the system. The model provides a means of assessing whether a function is statically allocated to a resource (only one resource is planned in the system to carry out the function: there is only one coloured actor in a box of AH) or whether a function is admissible for dynamic allocation to a resource (several resources are planned and some of them could carry out the function: there are at least two coloured actors in a box of AH).

SOCA-CAT is centred on the analysis of situated functions and resources and would be used to assess the choices made by the designers regarding the functioning of the system in dynamic situations. The model provides a means to assess the potential risks of the DFA in different complex situations and to find, when it is possible, the best system configuration to deal with situations. The SOCA-CAT is composed of the designers' choices that are represented by different types of functions actionable in a given elementary situation. A function can be "expected" (a function with a bar inside a dotted box can occur and typically occurs), "optional" (a function inside a dotted box without a bar can occur but does not typically occur) or "impossible" (a function outside the dotted box can never occur). Moreover, some functions are designed with different allocation possibilities (different resources or configurations of resources can carry out the function).

When complex situations are considered, namely when the conjunction of several elementary situations is examined, designers should check whether there is no conflict between the choices made for the elementary situations. They must look for functions that are "expected" in an elementary situation and that are "impossible" for all resources of the system in other elementary situations. Let us consider situation S* as the conjunction of elementary situations Si and Sj. SOCA-CAT would be useful to model:  a minimal configuration list MinConfig(S*) of functions that can be allocated to a resource and are "expected" in a complex situation. The list is composed of the functionresource couples, noted Fi-Ri, that are at least considered once as "expected" in situation Si and Sj.

 a list Pot(S*) representing all the functions that can be allocated to a resource and are "possible" (i.e. "expected" or "optional") in a complex situation. The list is composed of the Fi-Ri couples that are considered in all situations Si and Sj as "expected" or "optional".

From these two lists, the designers could first check whether there are any design conflicts between concurrent elementary situations modelled with SOCA-CAT, i.e. whether MinConf(S*) is included in Pot(S*). Hence, they deal with a decision problem, depicted in Figure 2, which can be written as:

Figure 2: Decision problem of function allocation

If the answer to the decision problem is positive, that is, if there is no design conflict, the designers could then deal with an optimization problem. They look for the best configuration in the list Pot(S*) that minimizes a criterion of dynamic function allocation defined in SOCA (e.g. the workload of some resources). This problem can be written as:

∀𝑆*, m𝑖𝑛𝑖𝑚𝑖𝑧𝑒 DFA_Criterion(𝑆𝑜𝑙𝑢𝑡𝑖𝑜𝑛(𝑆*)), 𝑤𝑖𝑡ℎ 𝑀𝑖𝑛𝐶𝑜𝑛𝑓(𝑆*) 𝑆𝑜𝑙𝑢𝑡𝑖𝑜𝑛(𝑆*) Pot(𝑆*).

The following section presents an implementation of this method on a case study.

EXAMPLE OF APPLICATION

The proposed CWA-based DFA method was applied on a small human-machine system composed of technical components (an electric pedal-assist bike, a GPS navigation system, physiological sensors, a battery gauge) and a human agent (a cyclist). The system can be considered as an instance of STS. It is both an intentional and a causal system: the system reacts to the variations on the road due to actions of other road users and to the laws of nature. This "simple" case study was chosen to illustrate the method proposed in this paper. The application example must therefore be considered as a first proof of concept. It simulates a design problem inspired by the new needs resulting from the recent popularization of pedal-assist bikes and the development and integration of new technologies. Indeed, new uses have appeared: cyclists want to avoid daily battery recharging, or they wish to integrate unplanned routes to their usual routine without having to do without power assist on the final slopes before arriving home. Hence, the assist capacities of electric bikes need to be better adapted to the cyclists' individual goals (such as duration and length of trips) and to dynamic situations (ascents, wind, road traffic). Adaptation also involves improved battery use and assistance optimization any time on the route while securing the bikers' safety. Furthermore new technologies enable adding physical and software devices onto the electric bikes so as to guarantee bikers a safe and effective ride. Designers thus need to be given a method to evaluate whether the resources and the dynamic function allocation are sufficient to meet these objectives of safety and performance.

Defining function allocation with the existing CWA tools

CWA modelling tools were used to model the functional constraints (AH), the situational constraints (CAT), and the resource constraints related to the DFA problem.

Work Domain Analysis (Abstraction Hierarchy)

The functional purpose of the system is to guarantee a safe and effective ride towards a desired destination.

Meeting this objective entails that the system must comply with some values and priorities related to performance and safety, shown in Figure 3 from left to right. The safety priorities from the smallest to the largest scale of the system are the following ones: minimal battery level for cyclists' safety; system integrity; adaptation of the system to the road; adaptation of the system to the road management system. The performance priorities are related to the management of the location objective (the system must help the cyclists reach the desired destination), the management of the path duration, and the management of the cyclists' tiredness. Consideration should be given to the humanmachine cooperation issue, in terms of the following purpose-related functions, which can be cognitive and motor functions: supplying propulsion to ride the bike and to reach the location objective; route planning means regularly geolocating the system and choosing an adapted path; controlling system capacities to monitor internal conditions (in this case, the energetic states of human and technical components of the system that could result in an accident or underperformance); controlling the environment (i.e. monitoring external conditions such as the weather, road grade and quality, stop signs, etc).

Figure 3: Abstraction Hierarchy and SOCA-AH

The object-related processes and the physical objects are defined in relation to the hybrid nature of the humanmachine system. The human actor is situated within the system; hence, the physical objects can be defined in terms of human capacity (for instance muscles or the nervous system) and technical capacity (for instance motor or sensors). This dichotomy between human and technical parts will be used in the SOCA phase to categorize the resources to which the functions could be allocated.

Control Task Analysis (Contextual Activity Template)

The work situations were modelled with different internal and external conditions, as indicated in the proposal of the method (see Figure 4). As in the example given by [START_REF] Naikar | Analysing activity in complex systems with cognitive work analysis: concepts, guidelines and case study for control task analysis[END_REF], some situations (S2 to S5) could result from the conjunction of elementary conditions (knowledge level of the cyclists on the path to reach their destination, and difficulty level resulting from the road quality, grade, and traffic). Other situations depend on only one condition (speed, GPS signal access). The distinction between "expected", "optional", and "impossible" situation-related functions was examined in this CWA phase and then refined in SOCA-CAT. The detailed design choices of this function classification are explained in the following paragraphs dealing with SOCA.

Social-Organization and Cooperation Analysis (reuse of previous models)

Only two resources (actors) were considered to investigate this DFA within a human-machine system. In Figures 3 and4, the functions allocated to human were coloured in blue (they will be noted Fi-H in the following paragraphs, with i as index), and those allocated to machine were coloured in green (noted Fi-M). The AH and the CAT were therefore coloured according to functional and situational design choices, providing what Jenkins et al. ( 2008) call SOCA-AH and SOCA-CAT models.

The SOCA-AH model shows that the function F4 is chosen by designers to be achieved by human (it is therefore a static allocation).

The SOCA-CAT model enables designers to refine the situational design choices according to human and technical resources. Some functions can be "expected" for human and "optional" for machine in certain conditions (in the good situation S4, the cyclists typically pedal, and electric assist is not typically activated, even if it is possible), or they can be "expected" for both human and machine (in the difficult situation S2, electric assist is typically activated). Some functions can also be « impossible » for human or machine in certain conditions. For instance, when the speed exceeds 30 km/h, the electric assist cannot be activated; when the battery is low, a design choice could be the deactivation of the GPS receiver and physiological sensors power for the benefit of the sole electric propulsion power; or when the cyclists know the route or when they are tired, they never planned the path to the desired destination. Some other constraints -resource constraints -have to be considered on the SOCA-AH and SOCA-CAT. The system under investigation is a "pedal-assist" bike, i.e. the electric motor would be activated only if the cyclists pedal (this is a conditional constraint: F1-M can be allocated only if F1-H is allocated). The system is also not equipped with sensors able to monitor the road environment (so F4-M is "impossible" and only F4-H can exist). Moreover, the other functions are ruled by a disjunctive constraint: functions must be allocated to at least one of the two resources.

Solving a dynamic function allocation problem with CWA

The use of previous CWA modelling tools would help designers assess whether their function-and situationdependent choices of resources generate conflicts threatening the safety or the performance of the activity of bike riding, and would allow them choosing an optimal situated function allocation when there is no conflict.

In Figure 4 only eight « elementary » or « simple » situations were defined, arising from the consideration of six variables of internal or external conditions (speed, road difficulty, knowledge of route, GPS signal access, user tiredness, and battery level). The proposed method entails verifying whether the function allocation choices onto the eight modelled elementary situations can deal with complex situations (i.e. the different conjunctions of the elementary situations), instead of considering and modelling all the combinations of the six condition variables. In the latter case, if only two modalities were considered for each variable (e.g. difficult or easy road conditions), up to 64 situations should be completely examined and defined by the designers. The proposal seeks to deal with this combinatorial explosion and to reduce this number by stressing the conflictual conjunctions that should be modelled in addition to these eight elementary situations.

Let us consider two cases: S*=S1US4US6, a rather favorable conjunction of elementary situations (Speed>30km/h, known route, easy road conditions, no GPS cover), and S**=S2US7US8, a difficult complex situation (unknown route, difficult road conditions, tired user, and low battery). The notation Fi-H and Fi-M explained in the proposal is kept for dealing with these examples.  MinConfig is the list of all the Fi-H and Fi-M that are "expected" (with circle and whiskers) in at least one elementary situation composing the complex situation. For this minimal list, it should be noted that only one resource is sometimes sufficient to allocate to a function like F2 or F3 (this is therefore an exclusive constraint noted XOR). Moreover, for the specific case of F1 (ruled by a conditional constraints of F1-H on F1-M), F1-M is expected as well as F1-H in S2, S3 or S7.

In the complex situation S*, F4-H is expected in S1, both F1-H and F4-H are expected in S4 and in S6, so MinConf(S*)={F1-H, F4-H}. In the complex situation S**, all modeled Fi-H and Fi-M of SOCA-CAT are expected in S2. So MinConf(S**)={F1-H ; F1-M; F2-H XOR F2-M ; F3-H XOR F3-M ; F4-H}.  Pot is the list of all the Fi-H and Fi-M that are not "impossible" (not outside dotted boxes) in every elementary situation composing the complex situation (i.e. the list of all the Fi-H and Fi-M that are "expected" or "optional" in every considered elementary situation).

For this maximal list of potential Fi-H and Fi-M, two resources can be allocated separately or together to the same functions: they are therefore both included in the list. Moreover, the conditional constraints are taken into account (e.g. for the specific case of F1, the constraint will be noted F1-M if F1-H). In the case of S*, F2-M is impossible in S6, F2-H and F3-H are both impossible in S4. So Pot(S*)={F1-H ; F1-M if F1-H ;F3-M ; F4-H}.

In the case S**, F2-H is impossible in S7, and both F2-M and F3-M are impossible in S8, whereas all the Fi-H and  If the answer is positive, there is at least one admissible allocation in the complex situation that meets the system functional purpose. This happens in the case S*, where MinConf(S*) is included in Pot(S*).

When possible, an optimization problem can then be solved with DFA criteria. For instance, let us consider the physical and mental workload of the cyclist, or the consumed power of the machine (i.e. the allocation of functions must be minimal respectively on the human or on the machine). The solutions of DFA in S* are thus:  Solution(S*, min cyclist workload)={F1-H; F1-M; F4-H}: electric assist must be implemented to decrease the physical workload, and the automated monitoring of system capacities F3-M is deactivated to avoid an information overload.

 Solution(S*, min energy consumption)={F1-H ;F4-H}:

the machine can be completely deactivated for propulsion and information processing, so as to keep enough battery to help the cyclist in hard road conditions.

DISCUSSION

At the theoretical level, this paper proposes a method that follows the formative nature and the focus on constraints modelling of CWA so as to deal with the DFA issue. This At the methodological level, the proposal is intended to help designers deal with the combinatorial explosion resulting from the combination of the different conditions that form complex situations. Instead of modelling all these complex situations, designers would be able to simply add new condition variables to the previously examined elementary situations and to observe the DFA properties of emergent situations. The analysis of the conjunctions of elementary situations in SOCA-CAT would then enable them to detect design conflicts. In this case, these conflictual complex situations should be completely defined and modelled by designers. Otherwise, that means the dynamic function allocation works in these complex situations, and the DFA problem can be considered as a local optimization problem (the best configuration is looked for in each situation according to specific criteria).

In terms of future perspectives, the proposed method could be further developed by integrating the temporal dimension: in the early design stages, situational constraints could be tested according to baseline scenarios to help designers assess the quality and the influence of their choices on the safety and the performance of the system in realistic situations. The number of design conflicts or the total cost generated from the DFA criteria could then be calculated to assess different design solutions. Considering the temporal dimension is also a way of thinking of a DFA problem not only as a local optimization but also as a global optimization problem (i.e. over entire scenarios).

Moreover, it would also be necessary to take into account the constraints modelled at other stages of CWA, such as the decisional constraints and the strategic constraints respectively defined in SOCA-DL (Decision Ladder in ConTA) and SOCA-IFM (Information Flow Map in StrA). Different cognitive styles could be distinguished that influence DFA (for instance the consideration of a person who always uses the GPS, even if this use is optional in certain situations).

Table 1 :

 1 CWA methodology summary (adapted from Jenkins et al., 2008 and Stanton and Bessell, 2014) DEFINING FUNCTION ALLOCATION WITH THE EXISTING CWA MODELS Dynamic function allocation (DFA) requires knowing the work functions that should be allocated (what), the situations in which they may be allocated (when and where), and the ressources that could be associated with a given function (who). Three phases of the CWA (WDA, ConTa, and SOCA) provide these data through two main existing tools: the Abstraction Hierarchy (AH) and the Contextual Activity Template (CAT).

Figure 1 :

 1 Figure 1: CAT Layout (from Bessell and Stanton, 2014)

Figure 4 :

 4 Figure 4: Contextual Activity Template and SOCA-CAT

Fi-M are

  possible in S2. So Pot(S**)={F1-H ;F1-M if F1-H ;F3-H; F4-H}. First the problem decision must be solved: " "  If the answer is negative, there exist a design conflict, and there is no admissible solution to the problem of dynamic function allocation in the situation under investigation. This happens in the case S**, where neither F2-H nor F2-M are present in Pot(S**) whereas they were in MinConf(S**) under the form F2-H XOR F2-M: MinConf(S**) is not included in Pot(S**). This design conflict is represented in Figure 4, in purple.

  contribution aims at continuing the work made on SOCA around the DFA question (Jenkins et al., 2008; Stanton and Bessell, 2014) by considering: a) SOCA-AH as a means to examine the constraints relative to the design choice of resources in terms of static function allocation (one sole resource for one function) or potential dynamic function allocation (several separate resources for one function); b) SOCA-CAT as a means to examine the constraints relative to the activation of resources in different situations that would influence the possibility and the choice of dynamic function allocation. This last consideration especially involved revisiting the concept of work situation defined by Naikar et al. (2006) relative to the specific question of DFA by characterizing it in terms of external and internal conditions.