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Ultrasound Echogenicity as an Indicator of Muscle Fatigue during Functional Electrical Stimulation
Qiang Zhang1,2, Ashwin Iyer1,2, Krysten Lambeth1,2
1UNC/NCSU Joint Department of Biomedical Engineering, North Carolina State University, Raleigh, NC 27695, USA.
Sensors (Basel, Switzerland)
|January 11, 2022
Summary
Ultrasound echogenicity effectively measures functional electrical stimulation (FES)-induced muscle fatigue. This technique offers a computationally efficient method for real-time fatigue detection in FES neurorehabilitation.
Area of Science:
- Biomedical Engineering
- Rehabilitation Technology
- Neuroscience
Background:
- Functional electrical stimulation (FES) aids mobility in neurological conditions but is limited by rapid muscle fatigue.
- Developing reliable methods to detect FES-induced muscle fatigue is crucial for effective neurorehabilitation.
Purpose of the Study:
- To investigate ultrasound (US) imaging-derived echogenicity as a sensitive indicator of FES-induced muscle fatigue.
- To assess the correlation between US echogenicity and muscle fatigue under isometric and dynamic conditions.
Main Methods:
- Eight non-disabled participants underwent FES on their tibialis anterior (TA) muscles during isometric and dynamic ankle dorsiflexion.
- Synchronously collected data included ankle torque/angle, US echogenicity signals from TA, and stimulation intensity.
- Analyzed the relative change in US echogenicity (ERC) in relation to muscle fatigue progression.
Main Results:
- US echogenicity relative change (ERC) showed an exponential decrease with progressing fatigue under both isometric (R2=0.891±0.081) and dynamic (R2=0.858±0.065) conditions.
- A strong linear relationship was observed between US ERC and muscle fatigue benchmarks (R2=0.840±0.054 isometric; R2=0.794±0.065 dynamic).
Conclusions:
- US echogenicity is a computationally efficient signal that accurately represents FES-induced muscle fatigue.
- This finding supports the potential for real-time implementation of US echogenicity in FES systems for closed-loop fatigue management.
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