Gait Measurement System Utilizing Missing Point Clouds Caused by Feet With Apple LiDAR Camera

Gait measurement in clinical settings is often limited to qualitative evaluations despite the availability of various measurement devices. Although marker-less motion capture techniques, such as Kinect, have been attracting attention recently, they have rarely been introduced in the field because of the complexity of measurement operations. Therefore, in this letter, we propose a gait measurement algorithm that uses the light detection and ranging (LiDAR) camera of an iPad, a widely used mobile device. First, as part of the floor was hidden by the walking foot, the missing points in the floor point cloud were detected as feet. Subsequently, we placed the potentials at the detected foot positions, summed them over a series of frames, and obtained the local maximum value to obtain the ground position during walking. Spatial gait parameters, such as step length and width, were obtained from the ground position. In an accuracy verification experiment with 13 elderly subjects, the average absolute error of the step length was 28 mm, and that of the step width was 19 mm. These results indicated that the values estimated using the proposed method are useful for evaluating clinical tasks.