Host: The Japan Society of Mechanical Engineers
Name : [in Japanese]
Date : June 06, 2021 - June 08, 2021
The purpose of this research is to detect ‘off phenomenon’ that occurs when a medicine for Parkinson's disease is no longer effective. We focus on the periodicity of gait in patients with Parkinson's disease. A patient is requested to attach a simple device equipped with an accelerometer, and acceleration time series during walking will be collected. We employ LSTM to detect walking abnormalities. In our preliminary experiments, we attempted to detect anomalies by LSTM in eight healthy young people, where the persons are requested to mimic typical performance of off phenomenon. As a result, Mahalanobis distance, which indicates the degree of abnormality, changed, so that the anomaly could be detected. The next problem is how to detect walking phases from accelerometer’s time series observed from patients. To investigate whether usual walking phase detection algorithms are able to be applied, we collected walking date for 60 seconds from two Parkinson's disease patients. As a result, the patients with Hoehn & Yahr severity III had a disordered periodicity, which indicates we have to make a new walking pattern identification algorithm for Parkinson’s patients.
