Objective: This study aims to develop a non-contact monitoring system using Wi-Fi waves, a widely available household technology, to objectively assess motor symptoms in Parkinson’s disease (PD).

Background: As motor symptoms in PD fluctuate within a day and vary from day to day, accurate monitoring of these fluctuations is crucial for optimizing treatment. Traditional symptom diaries are subjective and often inaccurate, while wearable devices suffer from low compliance due to discomfort associated with prolonged use.

Method: We conducted a preliminary study involving one PD patient and one healthy control. Wi-Fi sensing was implemented in a controlled environment equipped with three Wi-Fi router sets, and motor assessments were performed using the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) Part III. Wi-Fi signal fluctuations during rest and movement were recorded and analyzed to compare the amplitude patterns between the PD patient and the healthy control.

Results: In the healthy control, Wi-Fi signal amplitude demonstrated significant variations both during movement and at rest. In contrast, the PD patient exhibited a consistently lower amplitude. These differences indicate that Wi-Fi sensing can capture distinct motor patterns associated with PD.

Conclusion: This study demonstrates the potential of Wi-Fi sensing as a non-contact method for assessing PD motor symptoms. The findings suggest that Wi-Fi signals may serve as objective markers of motor impairment in PD. Future work will focus on increasing the sample size and developing a machine learning model.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/development-of-a-non-contact-monitoring-technology-for-the-motor-symptoms-of-parkinsons-disease-using-wi-fi-sensing/