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Tremor-Tamer: Real-Time Counter-Vibration Suppression for Parkinsonian Tremor

CSEF · 2026 Medicine & Physiology (Junior Division)

Adarsh Venkatesh

Overview

Neurological tremors , including those caused by Parkinson’s disease and other tremor disorders can significantly impair daily functioning, making routine tasks difficult and reducing independence and daily quality of life. This project designed and tested a low-cost Active Tremor-Tamer prototype designed to reduce tremor using sensor-based counter-vibration similar in concept to noise-cancelling, but for motion. An Arduino Nano reads an MPU-6050 accelerometer mounted on the tremor simulator to measure shaking, after which a control algorithm estimates tremor activity in the 4–12 Hz range and drives a vibration motor through a MOSFET module using a custom turn ON/OFF algorithm. Performance was evaluated using a repeatable tremor simulator capable of generating controlled oscillations across multiple frequencies. The device was tested in several modes: motor OFF (baseline), passive-only , active and hybrid (passive+active) modes, enabling comparison and clear separation of added weight damping effects from true active control. For each frequency, multiple trials were recorded; tremor magnitude was quantified using RMS acceleration, with mean ± standard deviation error bars. The algorithm was tuned to achieve zero false activations on natural movement and 100% detection within the 4–6 Hz Parkinsonian band, while reducing tremor amplitude by 32–56% across 4, 6, 8, 10, and 12 Hz. The phase-cancel mode provided the greatest reduction in tremor amplitude while maintaining safe, low-voltage operation.

Competition history

  • CSEF 2026 Medicine & Physiology (Junior Division) · Entry J-15-18

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