Objective: To investigate the effect of electromyography (EMG)-driven robotic therapy on the recovery of the hand in a stroke case lasting 9 years.
Case: An 18-year-old patient with hemiparesis due to the ischemic lesion was admitted to our clinic with hand impairment. Fifteen sessions (5 weeks x 3 times) of robotic rehabilitation were applied with the Hand of Hope. Average EMG (mV) of flexor digitorum superficialis (FDS) muscle, average force (N) and the rate of force development (RFD)(N/s) were also assessed before and after the treatment following the 5th and 10th sessions and at the end of treatment. Also, Fugl-Meyer Assessment of Upper Extremity Scale (FMU-UE), Motor Activity Log (MAL), Canadian Occupational Performance Score (COPM) and Visual Analog Scale (VAS) were used for assessment before and after the treatment.
Results: The average EMG measured from FDS increased from 0.093-0.133 mV. The average force and average RFD increased from 45.6-97.7 and from 135.6-172.6 respectively. While affected and/or unaffected side force ratio increased dramatically from 54%-82%, the FMA-UE score increased from 56-59. The MAL quality of use score increased from 3.93-4.13. Performance and satisfaction scores of COPM changed from 5.25-7.25 and 4.5-8.25 respectively. VAS score for fatigue changed from 6 to 4.
Discussion: The improvement achieved 9 years later with 15 sessions of rehabilitation suggests that improvement may be possible for chronic stroke patients.
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http://dx.doi.org/10.1016/j.jht.2021.04.022 | DOI Listing |
Wearable Technol
December 2024
Department of Human Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, Amsterdam, The Netherlands.
While active back-support exoskeletons can reduce mechanical loading of the spine, current designs include only one pair of actuated hip joints combined with a rigid structure between the pelvis and trunk attachments, restricting lumbar flexion and consequently intended lifting behavior. This study presents a novel active exoskeleton including actuated lumbar and hip joints as well as subject-specific exoskeleton control based on a real-time active low-back moment estimation. We evaluated the effect of exoskeleton support with different lumbar-to-hip (L/H) support ratios on spine loading, lumbar kinematics, and back muscle electromyography (EMG).
View Article and Find Full Text PDFJ Biomech Eng
March 2025
Human-Centric Design Research Lab, Department of Mechanical Engineering, Texas Tech University, Lubbock, TX 79409.
Estimating muscle forces is crucial for understanding joint dynamics and improving rehabilitation strategies, particularly for patients with neurological disorders who suffer from impaired muscle function. Muscle forces are directly proportional to muscle activations, which can be obtained using electromyography (EMG). EMG-driven modeling estimates muscle forces and joint moments from muscle activations.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Department of Information Engineering, Università Politecnica delle Marche, 60131 Ancona, Italy.
The volitional control of powered assistive devices is commonly performed by mapping the electromyographic (EMG) activity of the lower limb to joints' angular kinematics, which are then used as the input for regulation. However, during walking, the ground reaction force (GRF) plays a central role in the modulation of the gait, providing dynamic stability and propulsion during the stance phase. Including this information within the control loop of prosthetic devices can improve the quality of the final output, providing more physiological walking dynamics that enhances the usability and patient comfort.
View Article and Find Full Text PDFWearable Technol
November 2024
Biomechanical Engineering Department, University of Twente, 7522 NB Enschede, Netherlands.
Commonly, quantitative gait analysis post-stroke is performed in fully equipped laboratories housing costly technologies for quantitative evaluation of a patient's movement capacity. Combining such technologies with an electromyography (EMG)-driven musculoskeletal model can estimate muscle force properties non-invasively, offering clinicians insights into motor impairment mechanisms. However, lab-constrained areas and time-demanding sensor setup and data processing limit the practicality of these technologies in routine clinical care.
View Article and Find Full Text PDFJ Neuroeng Rehabil
November 2024
Department for Mechanical Engineering, Rice University, Houston, TX, USA.
Background: Calibrated electromyography (EMG)-driven musculoskeletal models can provide insight into internal quantities (e.g., muscle forces) that are difficult or impossible to measure experimentally.
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