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Video s3
    Details
    Poster
    Presenter(s)
    Miguel Cacho-Soblechero Headshot
    Affiliation
    Affiliation
    Imperial College London
    Country
    Abstract

    This paper presents a 4 channel ASIC for sEMG sensing with in-built muscle fatigue and activity feature extraction. Each channel filters and conditions the electrode signal in parallel, while extracting key features for Low Back Pain (LBP) fatigue monitoring and forecasting: Zero Crossing rate and Root Mean Square through sEMG Envelope. The channels are integrated with a Transimpedance Amplifier, an 10-Bit ADC and a Digital Control Unit to digitise and enable transmission of extracted features. Fabricated in TSMC 180nm, these channels present a compact form factor (90$\mu m \times$ 630$\mu m$) and a low power consumption (42.61 $\mu W$), ideal characteristic for wearable devices utilised for long-term monitoring of activities.

    Slides
    • A 4-Channel sEMG ASIC with Real-Time Muscle Fatigue Feature Extraction (application/pdf)