Abstract
Because muscles must be repetitively activated during functional electrical stimulation, it is desirable to identify the stimulation pattern that produces the most force. Previous experimental work has shown that the optimal pattern contains an initial high-frequency burst of pulses (i.e., an initial doublet or triplet) followed by a low, constant-frequency portion. Pattern optimization is particularly challenging, because a muscle's contractile characteristics and, therefore, the optimal pattern change under different physiological conditions and are different for each person. This work describes the continued development and testing of a mathematical model that predicts isometric forces from fresh and fatigued muscles in response to brief trains of electrical pulses. By use of this model and an optimization algorithm, stimulation patterns that produced maximum forces from each subject were identified.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 917-925 |
| Number of pages | 9 |
| Journal | Journal of Applied Physiology |
| Volume | 88 |
| Issue number | 3 |
| State | Published - Mar 2000 |
| Externally published | Yes |
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Keywords
- Doublets
- Fatigue
- Functional electrical stimulation
- Human quadriceps femoris muscle
- Variable-frequency trains
ASJC Scopus subject areas
- Physiology
- Endocrinology
- Orthopedics and Sports Medicine
- Physical Therapy, Sports Therapy and Rehabilitation
Cite this
Development of a mathematical model that predicts optimal muscle activation patterns by using brief trains. / Ding, Jun; Wexler, Anthony S.; Binder-Macleod, Stuart A.
In: Journal of Applied Physiology, Vol. 88, No. 3, 03.2000, p. 917-925.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Development of a mathematical model that predicts optimal muscle activation patterns by using brief trains
AU - Ding, Jun
AU - Wexler, Anthony S.
AU - Binder-Macleod, Stuart A.
PY - 2000/3
Y1 - 2000/3
N2 - Because muscles must be repetitively activated during functional electrical stimulation, it is desirable to identify the stimulation pattern that produces the most force. Previous experimental work has shown that the optimal pattern contains an initial high-frequency burst of pulses (i.e., an initial doublet or triplet) followed by a low, constant-frequency portion. Pattern optimization is particularly challenging, because a muscle's contractile characteristics and, therefore, the optimal pattern change under different physiological conditions and are different for each person. This work describes the continued development and testing of a mathematical model that predicts isometric forces from fresh and fatigued muscles in response to brief trains of electrical pulses. By use of this model and an optimization algorithm, stimulation patterns that produced maximum forces from each subject were identified.
AB - Because muscles must be repetitively activated during functional electrical stimulation, it is desirable to identify the stimulation pattern that produces the most force. Previous experimental work has shown that the optimal pattern contains an initial high-frequency burst of pulses (i.e., an initial doublet or triplet) followed by a low, constant-frequency portion. Pattern optimization is particularly challenging, because a muscle's contractile characteristics and, therefore, the optimal pattern change under different physiological conditions and are different for each person. This work describes the continued development and testing of a mathematical model that predicts isometric forces from fresh and fatigued muscles in response to brief trains of electrical pulses. By use of this model and an optimization algorithm, stimulation patterns that produced maximum forces from each subject were identified.
KW - Doublets
KW - Fatigue
KW - Functional electrical stimulation
KW - Human quadriceps femoris muscle
KW - Variable-frequency trains
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UR - http://www.scopus.com/inward/citedby.url?scp=0034055477&partnerID=8YFLogxK
M3 - Article
VL - 88
SP - 917
EP - 925
JO - Journal of Applied Physiology
JF - Journal of Applied Physiology
SN - 8750-7587
IS - 3
ER -