## 2 Description of SHERPAM Platform  
The case study presented in this article is based on the acceptability study carried out in the SHERPAM project. The different technologies integrated in the SHERPAM platform  
Figure 1: The Unified Theory of Technology Acceptance and Use (UTAUT) according to [PERSON] et al. (adapted figure) [8]. “Performance expectancy is defined as the degree to which an individual believes that using the system will help him or her to attain gains in job” [9] p. 447. “Effort expectancy is defined as the degree of ease associated with the use of the system” [9] p. 450. “Social influence is defined as the degree to which an individual perceives that important others believe he or she should use the new system” [9] p. 451. “Facilitating conditions are defined as the degree to which an individual believes that an organizational and technical infrastructure exists to support use of the system” [9] p. 453. Behavioral Intention is defined as intending, predicting, or planning to use the system in the next months. The effect of these four determinants is moderated by age, gender, experience, and voluntariness of use (the degree to which use of the innovation is perceived as being voluntary, or of free will). have been developed for the medical environment, with the aim of transmitting a data stream (i.e., health data) to a remote server. Thus, the platform (Figure 2) has been designed to cover all stages of data acquisition, transmission and processing, while meeting the following criteria:  
* **Extensibility:** since distinct pathologies may require different types of data, the system is not limited to a pre-defined, unchanging set of sensors. On the contrary it is scalable so that it can easily accommodate new types of sensors or data processing algorithms if required. * **Self-sufficiency:** the system allows that data acquired by sensors to be processed either \"locally\" or on a remote site. Local processing makes it possible for the sensing system worn by a subject to run autonomously--although possibly in a degraded mode--when no communication network is available. In contrast remote processing makes it possible to run advanced (CPU intensive) algorithms on the data acquired by the sensors. An aggregation server for data collection. This segment, like the previous one, is equipped with all the necessary means for encryption and data security. * **Agility:** the system is agile in terms of network connectivity. It switches between cellular networks (2.5G/3G/4G) and Wi-Fi hotspots depending on their availability, but also other parameters such as the nature of the data to be transmitted or the power consumption related to the use of each type of network. * **Disruption-tolerance:** Transmissions in the system are \"bundle-oriented\", which allows network disruptions to be tolerated (including long disruptions as can be observed in \"white zones\" that are not covered by any wireless network) without ever losing important data. These constraints and considerations led to the SHERPAM platform. To provide a better understanding, a very brief description is given here. The frontend is crucial, it aims to establish communication between a smart-phone and a set of sensors available on the market. For the present study, the Zephir and the Actigraph were retained, as were the communication channel, which aims to establish a communication system that adapts to the existing mode of communication (3G, 4G, WiFi) [27], and the aggregation server for data collection. This segment, like the previous one, is equipped with all the necessary means for encryption and data security [28]. The data processing targets different populations. A first one regrouping cyclists and Cardiac patients. For this population, the objective was to  
Figure 2: Synthetic view of the SHERPAM platform used in this study. The SHERPAM platform is a system device capable of transmitting a data stream to a remote server.