Abstract
Technology advancements in wireless communication and embedded computing are fostering their evolution from standalone elements to smart objects seamlessly integrated in the broader context of the Internet of Things. In this context, wearable sensors represent the building block for new cyber-physical social systems, which aim at improving the well-being of people by monitoring and measuring their activities and provide an immediate feedback to the users. In this paper, we introduce ePhysio, a large-scale and flexible platform for sensor-assisted physiotherapy and remote management of musculoskeletal diseases. The system leverages networking and computing tools to provide real-time and ubiquitous monitoring of patients. We propose three use cases which differ in scale and context and are characterized by different human interactions: single-user therapy, indoor group therapy, and on-field therapy. For each use case, we identify the social interactions, e.g., between the patient and the physician and between different users and the performance requirements in terms of monitoring frequency, communication, and computation. We then propose three related deployments, highlighting the technologies that can be applied in a real system. Finally, we describe a proof-of-concept implementation, which demonstrates the feasibility of the proposed solution.
Highlights
Nowadays, wearable sensors are the principal component of a system for monitoring, in an accurate and reliable way, human activities and behaviors
Recent advancements in wireless technologies and communication protocols [5] are fostering the seamless integration of wearable devices into a larger system, promoting their evolution from standalone elements connected to vertical ad-hoc systems to smart objects integrated in the broader context of the Internet of Things (IoT)
inertial measurement systems (IMUs) estimate the orientation of the body segments at the locations where they are attached by combining multi-sensor information through dedicated optimal sensor fusion algorithms mainly based on Kalman filtering [24]
Summary
Wearable sensors are the principal component of a system for monitoring, in an accurate and reliable way, human activities and behaviors. Recent advancements in wireless technologies and communication protocols [5] are fostering the seamless integration of wearable devices into a larger system, promoting their evolution from standalone elements connected to vertical ad-hoc systems to smart objects integrated in the broader context of the Internet of Things (IoT). In this context, wearable embedded systems represent a new building block for the creation of a new generation of cyber-physical system, in which humans are Sensors 2019, 19, 2; doi:10.3390/s19010002 www.mdpi.com/journal/sensors. We present ePhysio, a modular sensing platform to monitor, stimulate, and encourage patient activity performance using gamification strategies and social engagement.
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