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Fatigue during functional neuromuscular stimulation
H B Boom1, A J Mulder, P H Veltink
1Biomedical Engineering Division, Faculty of Electrical Engineering, University of Twente, Enschede, The Netherlands.
Progress in Brain Research
|January 1, 1993
Summary
Intermittent electrical stimulation significantly delays muscle fatigue in paraplegics compared to continuous stimulation. This finding is crucial for developing better controllers for functional neuromuscular stimulation (FNS).
Area of Science:
- Neurology
- Biomedical Engineering
- Rehabilitation Science
Background:
- Muscle fatigue limits the effectiveness of functional neuromuscular stimulation (FNS).
- Understanding fatigue parameters during intermittent stimulation is essential for optimizing FNS protocols.
- Previous research has not fully elucidated the impact of intermittent stimulation on fatigue.
Purpose of the Study:
- To compare muscle fatigue generated by continuous electrical stimulation versus intermittent stimulation schemes.
- To investigate how fatigue parameters are influenced by different stimulation patterns in T5-T6 paraplegics.
- To develop a model for FNS controllers that accounts for fatigue-induced non-stationarity.
Main Methods:
- Experiments were conducted on T5-T6 paraplegics using both continuous and intermittent electrical stimulation.
- Torque development over time was measured and analyzed using exponential time constants.
- Average torque over time was calculated for intermittent stimulation to estimate fatigue parameters.
Main Results:
- Continuous stimulation resulted in torque decay described by a double exponential, with a falling time constant of 100-200 sec.
- Intermittent stimulation markedly postponed fatigue, with torque time courses also following a double exponential.
- Fatigue led to a decline in average muscle torque to a patient-specific constant level, independent of the stimulation duty cycle.
Conclusions:
- Intermittent electrical stimulation is a viable strategy to mitigate muscle fatigue in FNS applications.
- The developed model accurately estimates fatigue parameters and can inform the design of adaptive FNS controllers.
- Findings provide insights into managing non-stationarity caused by fatigue in neuromuscular electrical stimulation.