Although researches had analyzed gait using small sensors, they analyzed only normal gaits. Thus, a research that can overcome the spatial limitations of the existing motion analyses and diagnose abnormal gaits for medical treatment is needed. Accordingly, this research developed the portable gait detection system that can detect gait using a gyroscope, and evaluated the accuracy of the system. The results showed an average recognition error rate of 1.7% for the normal and abnormal gaits, and confirmed that the gait cycle was detected with a high degree of accuracy. Using these characteristics, we could distinguish or diagnose, and treat, an abnormal gait.

Gait is a voluntary movement that requires interactions between sensory, muscular and central nerve systems. Therefore, gait disorder may improve by using the external stimulus on sensory system. However, there have not been many studies on biomechanical changes of gait, a dynamic posture of body, when a somatosensory stimulation is applied. Gait experiment was performed to validate this hardware in actual situation with 3-dimensional motion analysis and gait analysis. The results showed changed ground reaction force and angle of joint, which was considered that local somatosensory stimulation gave immediate feedback and changed the characteristics of gait during the gait. The study used a real-time analysis of patient's movement and external stimulation applied at proper timing and its results would be usefully applied in patients who requires gait guidance and have gait abnormality due to lack of balance for rehabilitation.