Estimation of 3D Ground Reaction Force Using Nanocomposite Piezo-Responsive Foam Sensors During Walking

• Published in: Annals of biomedical engineering Vol. 45; no. 9; pp. 2122 - 2134
• Main Authors: Rosquist, Parker G., Collins, Gavin, Merrell, A. Jake, Tuttle, Noelle J., Tracy, James B., Bird, Evan T., Seeley, Matthew K., Fullwood, David T., Christensen, William F., Bowden, Anton E.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.09.2017; Springer Nature B.V
• Subjects: Adult; Biochemistry; Biological and Medical Physics; Biomechanics; Biomedical and Life Sciences; Biomedical Engineering and Bioengineering; Biomedicine; Biophysics; Classical Mechanics; Demographics; Demography; Female; Fitness equipment; Gait - physiology; Human motion; Humans; Inserts; Male; Models, Biological; Nanocomposites; Sensors; Three dimensional motion; Walking; Walking - physiology; Nanocomposite; Foam sensor; Wearable sensor; Ground reaction force; Functional data analysis; Gait analysis
• ISSN: 0090-6964; 1573-9686; 1573-9686
• DOI: 10.1007/s10439-017-1852-2

This paper describes a method for the estimation of the 3D ground reaction force (GRF) during human walking using novel nanocomposite piezo-responsive foam (NCPF) sensors. Nine subjects (5 male, 4 female) walked on a force-instrumented treadmill at 1.34 m/s for 120 s each while wearing a shoe that was instrumented with four NCPF sensors. GRF data, measured via the treadmill, and sensor data, measured via the NCPF inserts, were used in a tenfold cross validation process to calibrate a separate model for each individual. The calibration model estimated average anterior–posterior, mediolateral and vertical GRF with mean average errors (MAE) of 6.52 N (2.14%), 4.79 N (6.34%), and 15.4 N (2.15%), respectively. Two additional models were created using the sensor data from all subjects and subject demographics. A tenfold cross validation process for this combined data set resulted in models that estimated average anterior–posterior, mediolateral and vertical GRF with less than 8.16 N (2.41%), 6.63 N (7.37%), and 19.4 N (2.31%) errors, respectively. Intra-subject estimates based on the model had a higher accuracy than inter-subject estimates, likely due to the relatively small subject cohort used in creating the model. The novel NCPF sensors demonstrate the ability to accurately estimate 3D GRF during human movement outside of the traditional biomechanics laboratory setting.