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SMoBAICS: The Smart Modular Biosignal Acquisition and Identification System for Prosthesis Control and Rehabilitation Monitoring

SMoBAICS: The Smart Modular Biosignal Acquisition and Identification System for Prosthesis Control and Rehabilitation Monitoring

Volkhard Klinger
Copyright: © 2017 |Volume: 5 |Issue: 2 |Pages: 24
ISSN: 2155-5621|EISSN: 2155-563X|EISBN13: 9781522514749|DOI: 10.4018/IJPHIM.2017070103
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MLA

Klinger, Volkhard. "SMoBAICS: The Smart Modular Biosignal Acquisition and Identification System for Prosthesis Control and Rehabilitation Monitoring." IJPHIM vol.5, no.2 2017: pp.34-57. http://doi.org/10.4018/IJPHIM.2017070103

APA

Klinger, V. (2017). SMoBAICS: The Smart Modular Biosignal Acquisition and Identification System for Prosthesis Control and Rehabilitation Monitoring. International Journal of Privacy and Health Information Management (IJPHIM), 5(2), 34-57. http://doi.org/10.4018/IJPHIM.2017070103

Chicago

Klinger, Volkhard. "SMoBAICS: The Smart Modular Biosignal Acquisition and Identification System for Prosthesis Control and Rehabilitation Monitoring," International Journal of Privacy and Health Information Management (IJPHIM) 5, no.2: 34-57. http://doi.org/10.4018/IJPHIM.2017070103

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Abstract

Simulation and modelling are powerful methods in computer aided therapy, rehabilitation monitoring, identification and control. The smart modular biosignal acquisition and identification system (SMoBAICS) provides methods and techniques to acquire electromyogram (EMG)- and electroneurogram (ENG)-based data for the evaluation and identification of biosignals. In this paper the author focuses 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 bioinformatical processes. Based on this we are stepping up of efforts to develop substitute methods and computer-aided simulation models with the objective of reducing animal testing. This work continues the former work about system identification and biosignal acquisition and verification systems presented in (Bohlmann et al., 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. Different application scenarios are shown to illustrate the system in different application fields. The author presents results of the enhanced closed-loop verification approach and of the signal quality using the Cuff-electrode-based ENG-data acquisition system.

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