Towards Gait Analysis And Rehabilitation of Parkinson's Disease Patients

This paper aims at designing an efficient real-time gait analysis algorithm to detect a possible fall. Four-meter Go and Back (4G) scale has been designed for taking measurements of experiments. Two wireless accelerometers are put on waist positions of 17 subjects suffering from Parkinson's disease. Based on information captured, a real-time gait analysis algorithm is implemented to detect an ambulatory deviation. Furthermore, the proposed method is flexible to adjust to respond to the gait-related movements. Other researchers can use this algorithm in their gait-related studies. In this paper, different gait-related parameters are also discussed and represented through a 4GB scale.