Literature DB >> 28807362

Leg movement tracking in automatic video-based one-leg stance evaluation.

Jacek Kawa1, Paula Stępień2, Wojciech Kapko3, Aleksandra Niedziela2, Jarosław Derejczyk3.   

Abstract

Falls are a major risk in elder population. Early diagnosis is therefore an important step towards increasing the safety of elders. One of the common diagnostic tests is the Berg Balance Scale (BBS), consisting of 14 exercises arranged from the easiest (sitting-to-standing) to the most demanding (one-leg stance). In this study a novel approach to the automatic assessment of the time in which the patient can remain in the one-leg stance position without loosing balance is introduced. The data is collected using a regular video camera. No markers, special garments, or system calibration are required. Two groups are examined. The first group consists of 16 students: healthy, young adults (12 female, 4 male, avg. 20yrs±1). The second group consists of 50 elders (39 female, 11 male, avg. 78.8yrs±5.9). Data (short, one minute recordings) are collected in a controlled environment using a digital video recorder (50fps, 1920×1080) fixed to a tripod. Data are processed off-line. First, the region of interest is determined. Next, the Kanade-Lucas-Tomasi tracking is performed. Best tracks are selected based on the registered vertical movement and two tracks are obtained corresponding to the left and right leg movements. Tracks are later subjected to the sparse signal baseline estimation, denoising and thresholding to detect the raised leg. Results are compared frame-wise to the ground truth reference obtained in the manual processing procedure. Both legs are evaluated in the elder group (in all cases several attempts featuring both legs were registered), resulting in 89.18%±11.27% DICE, 93.07%±5.43% sensitivity and 96.94%±6.11% specificity values for both legs. The signal of a single leg is evaluated in the student group (in all cases only one attempt was needed to perform the full examination) resulting in 98.96%±1.2% DICE, 98.78%±1.65% sensitivity and 98.73%±2.69% specificity values. This is the first step towards a video-based system enabling the automatic assessment of the four last, most vital tasks of the Berg Balance Scale evaluation.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Automatic balance analysis; Berg Balance Scale; One-leg stance; Telegeriatrics

Mesh:

Year:  2017        PMID: 28807362     DOI: 10.1016/j.compmedimag.2017.07.003

Source DB:  PubMed          Journal:  Comput Med Imaging Graph        ISSN: 0895-6111            Impact factor:   4.790


  2 in total

1.  Computer Aided Written Character Feature Extraction in Progressive Supranuclear Palsy and Parkinson's Disease.

Authors:  Paula Stępień; Jacek Kawa; Emilia J Sitek; Dariusz Wieczorek; Rafał Sikorski; Magda Dąbrowska; Jarosław Sławek; Ewa Pietka
Journal:  Sensors (Basel)       Date:  2022-02-21       Impact factor: 3.576

2.  Validity of the frame subtraction method in dynamic postural stability.

Authors:  Megumi Ota; Hiroshige Tateuchi; Takaya Hashiguchi; Karen Fujiwara; Ayano Sasaki; Kiseki Okumura; Noriaki Ichihashi
Journal:  BMC Sports Sci Med Rehabil       Date:  2022-09-26
  2 in total

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