Algorithm to estimate the knee angle in normal gait: trajectory generation approach to intelligent transfemoral prosthesis
This paper presents an algorithm to estimate the knee angle from hip angle and gait parameters. This algorithm uses a single sensor on the thigh to achieve the estimation. Hip-knee natural correlations were employed in order to analyze the gait flexion-extension movements in two stages: 1) when the foot is not in full contact with the floor (swing phase and heel contact); 2) when the whole sole makes contact with the ground (stance phase). The estimation is developed in real-time for gait movements and speed fluctuations do not distort the angle estimated. In addition, the simple linear regression was used to approximate the estimated angle to actual knee angle. The experimental results obtained from the gait studies, showed an acceptable knee angle approximation; the mean error estimation was 8.25∘. The major goal of this work was the development of an algorithm that can solve the problem of human body-intelligent transfemoral prosthesis coordination, even if there are gait speed fluctuations.
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