Motion tracking and gait feature estimation for recognising Parkinson’s disease using MS Kinect

Abstract

BackgroundAnalysis of gait features provides important information during the treatment of neurological disorders, including Parkinson’s disease. It is also used to observe the effects of medication and rehabilitation. The methodology presented in this paper enables the detection of selected gait attributes by Microsoft (MS) Kinect image and depth sensors to track movements in three-dimensional space.Methods The experimental part of the paper is devoted to the study of three sets of individuals: 18 patients with Parkinson’s disease, 18 healthy aged-matched individuals, and 15 students. The methodological part of the paper includes the use of digital signal-processing methods for rejecting gross data-acquisition errors, segmenting video frames, and extracting gait features. The proposed algorithm describes methods for estimating the leg length, normalised average stride length (SL), and gait velocity (GV) of the individuals in the given sets using MS Kinect data.ResultsThe main objective of this work involves the recognition of selected gait disorders in both the clinical and everyday settings. The results obtained include an evaluation of leg lengths, with a mean difference of 0.004 m in the complete set of 51 individuals studied, and of the gait features of patients with Parkinson’s disease (SL: 0.38 m, GV: 0.61 m/s) and an age-matched reference set (SL: 0.54 m, GV: 0.81 m/s). Combining both features allowed for the use of neural networks to classify and evaluate the selectivity, specificity, and accuracy. The achieved accuracy was 97.2 %, which suggests the potential use of MS Kinect image and depth sensors for these applications.ConclusionsDiscussion points include the possibility of using the MS Kinect sensors as inexpensive replacements for complex multi-camera systems and treadmill walking in gait-feature detection for the recognition of selected gait disorders.

A Review on Accelerometry-Based Gait Analysis and Emerging Clinical Applications

“…Video images have been used in [57] [92]. Microsoft (MS) Kinect image and depth sensors provide a simple 3D modeling using image and depth sensors which have shown to be effective in analysis of gait disorders [93] and to recognise PD gait [94].…”

Kinect‐based gait analyses of patients with Parkinson's disease, patients with stroke with hemiplegia, and healthy adults

“…Kinect can help physicians explore the field of body recognition and subjects' motor function. Tupa et al 1 used normalized stride length (SL) and gait velocity (GV) for recognition and achieved a high accuracy rate of 97.2%.…”

Measurement Straight Leg Raise for Low Back Pain Based Grayscale Depth

“…Research using Kinect to detect falls in the elderly parent to test the movement of healthy people through the movement of sitting and standing [11]. Paper [12] analyzed that features of a person's gait can provide important information for the treatment of neurological disorders, including Parkinson disease and to observe the effects of treatment and rehabilitation. The methodology used allows detecting attributes gait by using the image sensor and the depth of Microsoft Kinect to track motion in three-dimensional space.…”