Skip to main content
Video s3
    Details
    Presenter(s)
    Muhammad Rizwan Khan Headshot
    Affiliation
    Affiliation
    Lahore University of Management Sciences
    Country
    Author(s)
    Affiliation
    Affiliation
    Lahore University of Management Sciences
    Display Name
    Wala Saadeh
    Affiliation
    Affiliation
    Lahore University of Management Sciences
    Affiliation
    Affiliation
    Lahore University of Management Sciences
    Abstract

    A wearable EMG based tremor detection and suppression system is presented. This work proposes a novel design enabling low-power consumption, wearability, lower computational cost and lower latency. An analog front end (AFE) is designed containing cascaded filters and a Driven Right-Leg (DRL) feedback for high-level noise removal of up to 1V. A CC1352R microcontroller with an integrated BLE along with RTOS is utilized to achieve low-power processing. A user-friendly interface is provided using Android application (AP) that allows immediate sharing of data to caretakers or database. A 128-point FFT is employed with a simple implementation in terms of computation and a variable-voltage skin-impedance based muscle stimulation is being used. The system is operable on coin cell batteries for more than 3 weeks. The overall average power consumption of the system is 4.8mW with average current 1.35mA and a detection latency of <0.2s is achieved.

    Slides
    • Wearable Low-Power Closed-Loop System for Tremor Detection and Stimulation Using Electromyography (EMG) (application/pdf)