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Abstract Patients with neuromuscular disease fail to produce necessary muscle force and have trouble maintaining joint moment required to perform activities of daily living. Measuring muscle force values in patients with neuromuscular disease is important but challenging. Electromyography (EMG) can be used to obtain muscle activation values, which can be converted to muscle forces and joint torques. Surface electrodes can measure activations of superficial muscles, but fine-wire electrodes are needed for deep muscles, although it is invasive and require skilled personnel and preparation time. EMG-driven modeling with surface electrodes alone could underestimate the net torque. In this research, authors propose a methodology to predict muscle activations from deeper muscles of the upper extremity. This method finds missing muscle activation one at a time by combining an EMG-driven musculoskeletal model and muscle synergies. This method tracks inverse dynamics joint moments to determine synergy vector weights and predict muscle activation of selected shoulder and elbow muscles of a healthy subject. In addition, muscle-tendon parameter values (optimal fiber length, tendon slack length, and maximum isometric force) have been personalized to the experimental subject. The methodology is tested for a wide range of rehabilitation tasks of the upper extremity across multiple healthy subjects. Results show this methodology can determine single unmeasured muscle activation up to Pearson's correlation coefficient (R) of 0.99 (root mean squared error, RMSE = 0.001) and 0.92 (RMSE = 0.13) for the elbow and shoulder muscles, respectively, for one degree-of-freedom (DoF) tasks. For more complicated five DoF tasks, activation prediction accuracy can reach up to R = 0.71 (RMSE = 0.29).
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Peripheral artery disease affects the function of the legs of claudicating patients in a diffuse manner irrespective of the segment of the arterial tree primarily involved
Different levels of arterial occlusive disease (aortoiliac, femoropopliteal, multi-level disease) can produce claudication symptoms in different leg muscle groups (buttocks, thighs, calves) in patients with peripheral artery disease (PAD). We tested the hypothesis that different locations of occlusive disease uniquely affect the muscles of PAD legs and produce distinctive patterns in the way claudicating patients walk. Ninety-seven PAD patients and 35 healthy controls were recruited. PAD patients were categorized to aortoiliac, femoropopliteal and multi-level disease groups using computerized tomographic angiography. Subjects performed walking trials both pain-free and during claudication pain and joint kinematics, kinetics, and spatiotemporal parameters were calculated to evaluate the net contribution of the calf, thigh and buttock muscles. PAD patients with occlusive disease affecting different segments of the arterial tree (aortoiliac, femoropopliteal, multi-level disease) presented with symptoms affecting different muscle groups of the lower extremity (calves, thighs and buttocks alone or in combination). However, no significant biomechanical differences were found between PAD groups during the pain-free conditions with minimal differences between PAD groups in the claudicating state. All statistical differences in the pain-free condition occurred between healthy controls and one or more PAD groups. A discriminant analysis function was able to adequately predict if a subject was a control with over 70% accuracy, but the function was unable to differentiate between PAD groups. In-depth gait analyses of claudicating PAD patients indicate that different locations of arterial disease produce claudication symptoms that affect different muscle groups across the lower extremity but impact the function of the leg muscles in a diffuse manner generating similar walking impairments.
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- Award ID(s):
- 2124918
- PAR ID:
- 10436288
- Editor(s):
- Isenberg, Jeffrey S
- Date Published:
- Journal Name:
- PLOS ONE
- Volume:
- 17
- Issue:
- 7
- ISSN:
- 1932-6203
- Page Range / eLocation ID:
- e0264598
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1371/journal.pone.0264598
