Human gait analysis by body segmentation and center of gravity

The physiological condition of a person may affect his/her daily behaviour such as gait or posture. For example under the fatigue condition, a person may be used to walk in a slower pace than usual. This paper presents a novel gait analysis approach to detect movement variations such as walking pace or speed change, walking with bending, walking with heavy breath, arm or leg swing change. Based on the geometry of the silhouette, we segment the body to five main parts including head, upper body, lower body, arms and legs. For a specific analysis, we segment the torso to upper and lower body. For the walking pace analysis, we use the leg movement in the lower body to find the max distance in a pace cycle and corresponding pace speed. The angles between the head or upper body and the vertical line are used to detect the walking with bending or walking with breathing. The arm swing angle or pace variation during walking can also be detected. We compare the normal condition with other abnormal condition such as people who have respiratory obstruction leading to heavy breathing, and have stomach ache resulting humpbacked status. These cause the angle of upper body different with normal condition, so we can observe these signals to give a warning notice. Our experiments show that with these fine posture features, we are able to detect a person's gait change. Examples are that a person is humpbacked, or the arm/leg swing and pace distance are in abnormal rhythm. From our gait analysis approach, we observe that when people are in a tired condition, they are used to adopt a static and comfortable pace distance to walk in our experimental results.