Gait Phase Detection Using 3D-Printed Piezoelectric Force Myography Sensors
Latsch B, Schäfer N, Schaumann S, Graffe S, Mahmoudi A, Grimmer M, Altmann AA, Ben Dali O, Seiler J, Rinderknecht S, Beckerle P, Kupnik M (2024)
Publication Type: Conference contribution
Publication year: 2024
Publisher: Institute of Electrical and Electronics Engineers Inc.
Conference Proceedings Title: IEEE Ultrasonics, Ferroelectrics, and Frequency Control Joint Symposium, UFFC-JS 2024 - Proceedings
Event location: Taipei, TWN
ISBN: 9798350371901
DOI: 10.1109/UFFC-JS60046.2024.10794064
Abstract
Muscle activity can be utilized to detect a user's movement intention in human-machine interactions. Electromyography (EMG) is the prevalent method to assess muscle activity but has critical disadvantages in its practical implementation, particularly for long-term measurements, which are required in wearable devices. Force myography (FMG) offers an alternative approach, mechanically detecting muscle contractions by assessing the tissue deformation. Highly sensitive ferroelectrets qualify for detecting subtle muscle movements using FMG. We propose to attach individual ferroelectret sensor patches superficially to the muscle bellies, thereby avoiding crosstalk from other muscles. The sensors are additively manufactured using polypropylene, which allows for application-specific customizations. In order to investigate the suitability of these sensors for FMG during walking, we conduct a study with seven unimpaired participants. Heel strike and toe-off events are determined from the data of four leg muscles, while the ground reaction force provided by an instrumented treadmill serves as a reference. Tibialis anterior (TA) and vastus medialis (VM) suit best for determining toe-off and heel strike events, with small deviations of 3.3%±1.7% for toe-off detection at the TA and -1.2%±1.2% for heel strike detection at the VM. The experimental results demonstrate the suitability of our ferroelectret sensors as a possible substitute for EMG, underscoring their potential in assistive devices such as exoskeletons and prostheses.
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Germany (DE)How to cite
APA:
Latsch, B., Schäfer, N., Schaumann, S., Graffe, S., Mahmoudi, A., Grimmer, M.,... Kupnik, M. (2024). Gait Phase Detection Using 3D-Printed Piezoelectric Force Myography Sensors. In IEEE Ultrasonics, Ferroelectrics, and Frequency Control Joint Symposium, UFFC-JS 2024 - Proceedings. Taipei, TWN: Institute of Electrical and Electronics Engineers Inc..
MLA:
Latsch, Bastian, et al. "Gait Phase Detection Using 3D-Printed Piezoelectric Force Myography Sensors." Proceedings of the 2024 IEEE Ultrasonics, Ferroelectrics, and Frequency Control Joint Symposium, UFFC-JS 2024, Taipei, TWN Institute of Electrical and Electronics Engineers Inc., 2024.
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