Symptom detection and prediction using inertial sensor-based gait analysis

Internally funded project


Start date : 01.05.2021


Project details

Scientific Abstract

Parkinson's disease after Alzheimer's is the second most common neurodegenerative disease which mainly affects the patient's mobility and produces gait insecurity and impairment. As patients experience various, asymmetrical and heterogeneous gait characteristics, personalized medication should be at the center of attention in controlling motor complications in Parkinson's patients. potentially, inertial measurement units (IMUs) can be utilized for long-term observation of the disease progress and estimating gait parameters. This project is dedicated to detecting and possibly predicting the motor symptoms of Parkinson's disease such as Bradykinesia, Dyskinesia, and the freeze of gait. This also includes the improvement of the existing gait analysis algorithms to fit the parkinsonian gait more accurately, which is the basis of symptom detection.

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