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

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. 20 yrs±1). The second group consists of 50 elders (39 female, 11 male, avg. 78.8 yrs ± 5.9). Data (short, one minute recordings) are collected in a controlled environment using a digital video recorder (50 fps, 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.