Biosignal acquisition system for prosthesis control and rehabilitation monitoring

Simulation, modelling and verification are powerful methods in computer aided therapy, rehabilitation monitoring, identification and control. They are major prerequisites to face great challenges in medical technology. To realize tasks and services like an on-line data monitoring or a nerve signal based prosthesis control, smart, intelligent and mobile systems are required. Here we present data acquisition and learning systems providing methods and techniques to acquire electromyogram (EMG)and electroneurogram (ENG)based data for the evaluation and identification of biosignals. We focus on the development, integration and verification of platform technologies which support this entire data processing. Simulation and verification approaches are integrated to evaluate causal relationships between physiological and bioinformatics processes. Based on this we are stepping up efforts to develop substitute methods and computer-aided simulation models with the objective of reducing experiments on animals. This work continues the former work about system identification and biosignal acquisition and verification systems presented in (Bohlmann, Klinger, and Szczerbicka 2010; Klinger and Klauke 2013; Klinger 2014). This paper focuses on the next generation of an embedded data acquisition and identification system and its flexible platform architecture. We present results of the enhanced closed-loop verification approach and of the signal quality using the Cuff-electrode-based ENG-data acquisition system.