Smart platform-based IoT-modules for applications in health care and rehabilitation

Abstract

Embedded systems and the Internet of Things (IoT) enable new procedures, measurement and analysis methods in the field of biomedical systems. The measurement of data, based on electrocardiogram (ECG)-, electromyogram (EMG)- or electroneurogram (ENG)-signals, allows a multitude of new approaches in diagnosis, prevention or rehabilitation. As part of a project for ENG-based control of prostheses, a platform has been designed, called smart modular biosignal acquisition, identification and control system (SMoBAICS), that also uses IoT-devices. In this paper, different IoT-devices are presented and described. In the context of an analysis of use cases, it becomes clear that the platform represents a toolbox, which provides appropriate modules and module configurations for different requirements. The designed IoT-devices use standard interfaces in order to integrate a specific additional function into the system. In the focus are two microcontroller (mC)-devices with different characteristics and a front-end system that enables the connection of a variety of Force Sensing Resistor (FSR)-sensors. Based on this platform architecture, many applications were presented, and examples were given of how the required functionality for the corresponding application can be achieved with the help of these IoT-systems. This platform enables a fusion of the various sensor data with the objective of motion identification and prosthesis control based on this by reading out various data (forces, acceleration, ENG-data, etc.) and integrating identification algorithms.

Hardware-/Software-Platform | Data-Driven Methods | Modelling | Simulation | Sensor Fusion

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