A Microsoft Kinect-Based Point-of-Care Gait Assessment Framework for Multiple Sclerosis Patients

Abstract

Gait impairment is a prevalent and important difficulty for patients with multiple sclerosis (MS), a common neurological disorder. An easy to use tool to objectively evaluate gait in MS patients in a clinical setting can assist clinicians to perform an objective assessment. The overall objective of this study is to develop a framework to quantify gait abnormalities in MS patients using the Microsoft Kinect for the Windows sensor; an inexpensive, easy to use, portable camera. Specifically, we aim to evaluate its feasibility for utilization in a clinical setting, assess its reliability, evaluate the validity of gait indices obtained, and evaluate a novel set of gait indices based on the concept of dynamic time warping. In this study, ten ambulatory MS patients, and ten age and sex-matched normal controls were studied at one session in a clinical setting with gait assessment using a Kinect camera. The expanded disability status scale (EDSS) clinical ambulation score was calculated for the MS subjects, and patients completed the Multiple Sclerosis walking scale (MSWS). Based on this study, we established the potential feasibility of using a Microsoft Kinect camera in a clinical setting. Seven out of the eight gait indices obtained using the proposed method were reliable with intraclass correlation coefficients ranging from 0.61 to 0.99. All eight MS gait indices were significantly different from those of the controls (p-values less than 0.05). Finally, seven out of the eight MS gait indices were correlated with the objective and subjective gait measures (Pearson's correlation coefficients greater than 0.40). This study shows that the Kinect camera is an easy to use tool to assess gait in MS patients in a clinical setting.

Monitoring and Assessment of Rehabilitation Progress on Range of Motion After Total Knee Replacement by Sensor-Based System

“…Lorenzi et al [21] presented a mobile healthcare device to monitor human motion disorders. Gholami et al [22] designed a Kinect system to assess gait parameters in multiple sclerosis patients. Kun et al [23] developed a sensor set and an algorithm to estimate knee-joint kinematics.…”

Distinct Feature Extraction for Video-Based Gait Phase Classification

“…However, no numerical classification results are presented and lack of abnormal data is a limitation of this preliminary study to determe empirical thresholds. A point-of-care gait assessment framework in [36] quantifies several gait indices and evaluates limb impairment for patients with multiple sclerosis, involving Dynamic Time Warping (DTW), Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). However, [36] reports that the inaccuracy of the captured joint trajectories limits the validation of this preliminary study.…”

Gait phase classification for in-home gait assessment

“…However, there is no numerical performance report. A point-of-care gait assessment framework that adopts dynamic time warping (DTW), principal component analysis (PCA) and linear discriminant analyses of gait indices is proposed in [25] to quantify gait abnormalities, evaluating limb impairment for patients with multiple sclerosis. However, there is no benchmarking system provided in the study.…”