학술논문

Assessment of Sensorized Insoles in Balance and Gait in Individuals With Parkinson’s Disease
Document Type
Periodical
Source
IEEE Transactions on Neural Systems and Rehabilitation Engineering IEEE Trans. Neural Syst. Rehabil. Eng. Neural Systems and Rehabilitation Engineering, IEEE Transactions on. 32:1445-1454 2024
Subject
Bioengineering
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Communication, Networking and Broadcast Technologies
Biological control systems
Footwear
Force
Real-time systems
Legged locomotion
Foot
Robot sensing systems
Parkinson’s Disease
instrumented insoles
plantar pressure
wearable sensors
Language
ISSN
1534-4320
1558-0210
Abstract
Individuals with Parkinson’s disease (PD) are characterized by gait and balance disorders limiting their independence and quality of life. Home-based rehabilitation programs, combined with drug therapy, demonstrated to be beneficial in the daily-life activities of PD subjects. Sensorized shoes can extract balance- and gait-related data in home-based scenarios and allow clinicians to monitor subjects’ activities. In this study, we verified the capability of a pair of sensorized shoes (including pressure-sensitive insoles and one inertial measurement unit) in assessing ground-level walking and body weight shift exercises. The shoes can potentially be combined with a sensory biofeedback module that provides vibrotactile cues to individuals. Sensorized shoes have been assessed in terms of the capability of detecting relevant gait events (heel strike, flat foot, toe off), estimating spatiotemporal parameters of gait (stance, swing, and double support duration, stride length), estimating gait variables (vertical ground-reaction force, vGRF; coordinate of the center of pressure along the longitudinal axes of the feet, yCoP; and the dorsiflexion angle of the feet, Pitch angle). The assessment compared the outcomes with those extracted from the gold standard equipment, namely force platforms and a motion capture system. Results of this comparison with 9 PD subjects showed an overall median absolute error lower than 0.03 s in detecting the foot-contact, foot-off, and heel-off gait events while performing ground-level walking and lower than 0.15 s in body weight shift exercises. The computation of spatiotemporal parameters of gait showed median errors of 1.62 % of the stance phase duration and 0.002 m of the step length. Regarding the estimation of vGRF, yCoP, and Pitch angle, the median across-subjects Pearson correlation coefficient was 0.90, 0.94, and 0.91, respectively. These results confirm the suitability of the sensorized shoes for quantifying biomechanical features during body weight shift and gait exercises of PD and pave the way to exploit the biofeedback modules of the bidirectional interface in future studies.