On-shoe wearable sensors for gait and turning assessment of patients with Parkinson's disease.

Assessment of locomotion through simple tests such as timed up and go (TUG) or walking trials can provide valuable information for the evaluation of treatment and the early diagnosis of people with Parkinson's disease (PD). Common methods used in clinics are either based on complex motion laboratory settings or simple timing outcomes using stop watches. The goal of this paper is to present an innovative technology based on wearable sensors on-shoe and processing algorithm, which provides outcome measures characterizing PD motor symptoms during TUG and gait tests. Our results on ten PD patients and ten age-matched elderly subjects indicate an accuracy ± precision of 2.8 ± 2.4 cm/s and 1.3 ± 3.0 cm for stride velocity and stride length estimation compared to optical motion capture, with the advantage of being practical to use in home or clinics without any discomfort for the subject. In addition, the use of novel spatio-temporal parameters, including turning, swing width, path length, and their intercycle variability, was also validated and showed interesting tendencies for discriminating patients in ON and OFF states and control subjects.

Gait assessment in Parkinson's disease: toward an ambulatory system for long-term monitoring.

An ambulatory gait analysis method using body-attached gyroscopes to estimate spatio-temporal parameters of gait has been proposed and validated against a reference system for normal and pathologic gait. Later, ten Parkinson's disease (PD) patients with subthalamic nucleus deep brain stimulation (STN-DBS) implantation participated in gait measurements using our device. They walked one to three times on a 20-m walkway. Patients did the test twice: once STN-DBS was ON and once 180 min after turning it OFF. A group of ten age-matched normal subjects were also measured as controls. For each gait cycle, spatio-temporal parameters such as stride length (SL), stride velocity (SV), stance (ST), double support (DS), and gait cycle time (GC) were calculated. We found that PD patients had significantly different gait parameters comparing to controls. They had 52% less SV, 60% less SL, and 40% longer GC. Also they had significantly longer ST and DS (11% and 59% more, respectively) than controls. STN-DBS significantly improved gait parameters. During the stim ON period, PD patients had 31% faster SV, 26% longer SL, 6% shorter ST, and 26% shorter DS. GC, however, was not significantly different. Some of the gait parameters had high correlation with Unified Parkinson's Disease Rating Scale (UPDRS) subscores including SL with a significant correlation (r = -0.90) with UPDRS gait subscore. We concluded that our method provides a simple yet effective way of ambulatory gait analysis in PD patients with results confirming those obtained from much more complex and expensive methods used in gait labs.