Modeling 3D Ground Reaction Forces During Walking Using Nanocomposite Piezo-Responsive Foam Sensors
Conference: American College of Sports Medicine 63rd Annual Meeting
Abstract: This study presents a new technique for acquiring ground reaction forces from novel, nanocomposite piezo-responsive foam (NCPF) sensors. A shoe was fitted with four NCPF sensors located at the heel, arch, ball, and toe positions. Running data was collected simultaneously from both the shoe sensors and from a force-sensing treadmill. A portion (30 randomly selected stance phases) of the treadmill data was used to develop a predictive stochastic model of GRF based on the sensor inputs. The stochastic model was then used to predict GRF for the remaining shoe sensor data, which was then benchmarked against the treadmill data. The results indicated that this model was able to predict forces in the x-axis (anterior-posterior) with 2.38% error, forces in the y-axis (medial-lateral) with 6.01% error, and forces in the z-axis (vertical) with 2.43% error. These novel sensors hold potential to dramatically improve both the ease and expense associated with GRF data, as well as allow unprecedented ability to measure GRF during real world applications outside of the laboratory.
Listed In: Biomechanical Engineering, Gait, Mechanical Engineering, Sports Science,
Tagged In: ground reaction forces, nanocomposites, wearable sensors
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Abstract: This study presents a new technique for acquiring ground reaction forces from novel, nanocomposite piezo-responsive foam (NCPF) sensors. A shoe was fitted with four NCPF sensors located at the heel, arch, ball, and toe positions. Running data was collected simultaneously from both the shoe sensors and from a force-sensing treadmill. A portion (30 randomly selected stance phases) of the treadmill data was used to develop a predictive stochastic model of GRF based on the sensor inputs. The stochastic model was then used to predict GRF for the remaining shoe sensor data, which was then benchmarked against the treadmill data. The results indicated that this model was able to predict forces in the x-axis (anterior-posterior) with 2.38% error, forces in the y-axis (medial-lateral) with 6.01% error, and forces in the z-axis (vertical) with 2.43% error. These novel sensors hold potential to dramatically improve both the ease and expense associated with GRF data, as well as allow unprecedented ability to measure GRF during real world applications outside of the laboratory.
Listed In: Biomechanical Engineering, Gait, Mechanical Engineering, Sports Science,
Tagged In: ground reaction forces, nanocomposites, wearable sensors
View PDF | Contact Author