論文ID: 2024EDP7285
Parkinson's disease (PD) is an intractable neurological disease that affects approximately 100-150 per 100, 000 people in Japan, with more than 95% of these patients aged 60 years or older. The Hoehn and Yahr staging scale (H-Y scale) [1] and Unified Parkinson's Disease Rating Scale (UPDRS) score [2] are typical indicators of PD severity, but subjective aspects cannot be completely excluded. This is due to the limited means to quantitatively measure and evaluate gait as a motor symptom of PD. However, in recent years, human movement has been measured by wearable devices and other devices in daily life. In this paper, we took this wearable-device measurement one step further and aimed to apply insole-type pressure sensors to medical care. We collected data from two patients with PD at H-Y stage 2 and nine patients with PD at H-Y stage 3, then generated a time-series pattern representing their gait patterns. By analyzing these gait patterns, we found that the sum of the three toe sensors and the sum of the two heel sensors provided stable data. The overlap time of the two summed sensor values and the deviations of each summed sensor value were defined as features. Using the features, we proposed PD severity estimation based on the k-means method. Experimental results showed that the estimation of Yahr 3 and healthy individuals was achieved with high accuracy, but Yahr 2 was often classified as a healthy individual.
