3D-Printed Piezoelectric PLA-Based Insole for Event Detection in Gait Analysis

Detecting human movement is crucial for the control of lower limb wearable robotics designed to assist daily activities or rehabilitation tasks. Sensorized insoles present a viable option for extracting control inputs, such as gait events and the corresponding phases, essential for regulating the magnitude and timing of assistance. Given their highly sensitive piezoelectric response to dynamic loading, ferroelectrets emerge as a cost-effective solution for customizing sensors suitable for these autonomous systems. Within this study, an insole with four ferroelectret sensors is 3D-printed monolithically from polylactic acid (PLA) onto bulk films of the same material through seamless thermal fusion. Sensor and insole are characterized through a testing machine and by conducting human walking experiments on an instrumented treadmill. The testing machine results indicate suitable sensor performance for the application in wearable robotics concerning the sensitivity, minimal detectable change, hysteresis, drift, and repeatability. Walking experiments reveal the insole's capability to detect gait events such as heel strikes with minimal variability and on average 16 ms faster compared to the reference of vertical ground reaction forces across all walking speeds above 1 m/s. The peak sensor outputs strongly relate to the reference while both exhibit a linear (R-2 > 95%) increase corresponding to walking speed. In conclusion, the study findings demonstrate the feasibility of PLA-based ferroelectrets as customized insole sensors for event detection in gait analysis, enabling assessment of human biomechanics with minimal impact on the natural gait and control of autonomous wearable robotics, such as exoskeletons.