An Unobtrusive Method for Remote Quantification of Parkinson’s and Essential Tremor Using mm-Wave Sensing

Tremor is a primary symptom of common movement disorders such as essential tremor and Parkinson’s disease. People experiencing tremors face difficulty in performing everyday tasks which negatively impacts their independence. Tremor quantification helps clinicians in evaluating disease progression and treatment response. The majority of the existing methods include cameras or motion sensors embedded in wearables and hand-held devices. The continuous wearing of contact sensors can be uneasy for the patients while the cameras cause privacy concerns. This article proposes a novel method for tremor quantification using a frequency-modulated continuous wave (FMCW) radar sensor. In this article, an off-the-shelf, low-cost FMCW radar has been configured to capture vibrations induced in distal limbs, a representative feature of essential and Parkinson’s Tremors. Moreover, a signal processing chain is developed to extract characteristic tremor frequency and amplitude by reconstructing the tremor signal from the radar return signals. For robustness and increased accuracy, static clutter and voluntary body motion are eliminated. Extensive experiments were performed and results were compared to the state-of-the-art methods that use accelerometers and gyroscopes. A strong correlation (
${R}^{{2}} >0.97$
) is found between the reference sensor readings and predicted values for both quantified parameters. The mean error for the frequency and amplitude is 0.14 Hz and 0.03 cm, respectively. Results demonstrate a superior accuracy as compared to the existing non-contact techniques, with the added advantage of privacy and integrity preserving for the end-user. Hence, the proposed system can provide reliable long-term objective assessment, aiding clinicians in the evaluation of tremor severity and treatment effectiveness.