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Abstract
Forefoot amputation, a type of partial foot amputation, involves the surgical disarticulation of either the interphalangeal or metatarsophalangeal joints. This procedure not only removes critical joint structures but also alters the positioning of associated muscles. Forefoot amputations significantly affect gait patterns and redistribute plantar pressure maps across the plantar surface of the foot. The phalanges are crucial in absorbing and redistributing plantar pressure during the gait cycle. The absence of phalanges and the loss of metatarsophalangeal joints alter the normal pressure distribution maps, possibly shifting peak pressure from one local foot region to another region of the foot. This research aims to understand how the lower extremity muscles produce force in patients with forefoot amputations during walking and to compare that to healthy individuals. Muscle activation data will be recorded using electromyography (EMG) sensors. The EMG system will be connected to a data acquisition (DAQ) board to transfer information from the “EMG Works Acquisition” application to the “Cortex” motion capture system in the lab. This setup will enable the collection of muscle activation data during motion analysis, such as a regular gait cycle. For the first part of the study, experimental gait data will be collected at the Gait Biomechanics Laboratory. For the second part, gait simulations will be conducted using the OpenSim software (version 4.5), utilizing a "Rajagopal 2016" model to estimate the muscle forces. The model will be adjusted to match the specific anthropometry of each subject using the “Scale” tool in OpenSim. After scaling, experimental marker data will be processed with the “Inverse Kinematics” tool to compute joint angles by minimizing errors between experimental marker trajectories and virtual markers on the scaled model. The joint angles will then be refined using the “Residual Reduction Algorithm (RRA)” tool, which improves kinematic data and enhances dynamic consistency between measured and calculated forces. The final step in OpenSim will involve using the “Computed Muscle Control (CMC)” tool to estimate individual muscle forces during the gait cycle. We hypothesize to observe significant differences in muscle activations and force patterns between forefoot amputees and healthy individuals. Specifically, healthy subjects are expected to exhibit higher levels of muscle activation and force production, while patients with forefoot amputations are expected to show adaptive, lower activation levels. The results of this study will provide insights regarding the physiological adaptations of muscles in response to disrupted gait patterns in patients with forefoot amputations. This will contribute to a better understanding of the rehabilitation process for improving the quality of health of an affected patient.
Recommended Citation
Melgar, Anthony; Caruntu, Dumitru; La Fontaine, Javier; Venegas, Luis; and Rahman, Hafizur, "Muscle Force Analysis in Patients with Forefoot Amputees and Healthy Subjects During Walking" (2025). Research Symposium. 20.
https://scholarworks.utrgv.edu/somrs/2025/posters/20
Included in
Biomechanics and Biotransport Commons, Medicine and Health Sciences Commons, Other Biomedical Engineering and Bioengineering Commons
Muscle Force Analysis in Patients with Forefoot Amputees and Healthy Subjects During Walking
Forefoot amputation, a type of partial foot amputation, involves the surgical disarticulation of either the interphalangeal or metatarsophalangeal joints. This procedure not only removes critical joint structures but also alters the positioning of associated muscles. Forefoot amputations significantly affect gait patterns and redistribute plantar pressure maps across the plantar surface of the foot. The phalanges are crucial in absorbing and redistributing plantar pressure during the gait cycle. The absence of phalanges and the loss of metatarsophalangeal joints alter the normal pressure distribution maps, possibly shifting peak pressure from one local foot region to another region of the foot. This research aims to understand how the lower extremity muscles produce force in patients with forefoot amputations during walking and to compare that to healthy individuals. Muscle activation data will be recorded using electromyography (EMG) sensors. The EMG system will be connected to a data acquisition (DAQ) board to transfer information from the “EMG Works Acquisition” application to the “Cortex” motion capture system in the lab. This setup will enable the collection of muscle activation data during motion analysis, such as a regular gait cycle. For the first part of the study, experimental gait data will be collected at the Gait Biomechanics Laboratory. For the second part, gait simulations will be conducted using the OpenSim software (version 4.5), utilizing a "Rajagopal 2016" model to estimate the muscle forces. The model will be adjusted to match the specific anthropometry of each subject using the “Scale” tool in OpenSim. After scaling, experimental marker data will be processed with the “Inverse Kinematics” tool to compute joint angles by minimizing errors between experimental marker trajectories and virtual markers on the scaled model. The joint angles will then be refined using the “Residual Reduction Algorithm (RRA)” tool, which improves kinematic data and enhances dynamic consistency between measured and calculated forces. The final step in OpenSim will involve using the “Computed Muscle Control (CMC)” tool to estimate individual muscle forces during the gait cycle. We hypothesize to observe significant differences in muscle activations and force patterns between forefoot amputees and healthy individuals. Specifically, healthy subjects are expected to exhibit higher levels of muscle activation and force production, while patients with forefoot amputations are expected to show adaptive, lower activation levels. The results of this study will provide insights regarding the physiological adaptations of muscles in response to disrupted gait patterns in patients with forefoot amputations. This will contribute to a better understanding of the rehabilitation process for improving the quality of health of an affected patient.
