A smartphone based system for freezing of gait monitoring for Parkinson's disease patients

摘要

Freezing of gait (FoG) is an aberrant gait in Parkinson's disease (PD), which is usually associated with fall risks and reduction of patients' life quality. Efficient intervention for patients to remove FoG has been proposed using context-aware rhythmic auditory cueing during FoG episodes, which relys on accurate detection of FoG. And clinical diagnosis of PD is partly based on the severity of FoG. In the present study we designed a wearable system based on smartphone for detection and monitoring of FoG for PD patients in daily life. We developed the time-frequency combined algorithm for FoG detection. Test of the system on nine PD patients showed an improved performance with a sensitivity of 90.8% and a specificity of 91.4% in FoG detection compared to the previous frequency domain algorithm. The monitoring information includes time, site and duration of each FoG and the total count of FoG in daily life which could act as objective references for clinical diagnosis of Parkinson's disease.