Gait phase detection based on inertial measurement unit and force-sensitive resistors embedded in a shoe.

Abstract

This study proposes a system to detect the phases of gait. It consists of an intelligent shoe equipped with an inertial measurement unit (IMU) and force-sensitive resistors (FSRs), and it uses a compound method to recognize gait. The continuous wavelet transform is applied according to accelerations obtained via the IMU to identify heel strike and toe-off events. These events are used to calculate the pressure threshold and proportional factor via the Lopez-Meyer (LM) method by using minimal leave-one-out for training and validation. The LM method can identify the entire sub-phase of the stance of the gait based on ground contact forces measured by using the FSRs and rules of gait event detection. The proposed system was tested on five healthy volunteers who used the intelligent shoe. The results show that it can detect all sub-phases of the gait with an overall accuracy (96%) higher than the LM method. The proportional factor was adaptable to variable body weights, and the reported average errors of competing systems in the literature significantly exceeded the average variation of the proposed system for all phases of gait. The range of errors in the swing phase and sub-phases of stance was also acceptable for application purposes. When the size of the subject's foot was close to that of the intelligent shoe, the error between normative data and phases of gait identified by the detection system was minimal. Furthermore, the proposed system detected abnormalities in the gait circle, and thus, it can be used to monitor the walking activity and measure the motor recovery.