Abstract
Conditioning and processing of biological signals represent interesting challenges for wearable electronics in health applications. Information gathering from these signals requires complex hardware circuitry and dedicated computation resources. The design of innovative analog front-end integrated circuits, combined with efficient signal processing algorithms, allows the development of platforms for monitoring, activity and gesture recognition based on embedded real-time systems. This paper describes an Electromyography pattern recognition system based on the combination of low cost passive sensors, an innovative analog front-end and a low power microcontroller. The performance of the proposed system matches state-of-the-art high-end active sensors, opening the way to the development of affordable and accurate wearable devices. Show more
Publication status
publishedExternal links
Book title
2014 IEEE Biomedical Circuits and Systems Conference (BioCAS) ProceedingsPages / Article No.
Publisher
CurranEvent
Organisational unit
03996 - Benini, Luca / Benini, Luca
03380 - Huang, Qiuting (emeritus) / Huang, Qiuting (emeritus)
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ETH Bibliography
yes
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