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Development of an Isokinetic Functional Electrical Stimulation Cycle Ergometer
- Source :
- Neuromodulation: Technology at the Neural Interface. 7:56-64
- Publication Year :
- 2004
- Publisher :
- Elsevier BV, 2004.
-
Abstract
- An isokinetic functional electrical stimulation leg cycle ergometer (iFES-LCE) was developed for individuals with spinal cord injury (SCI). The iFES-LCE was designed to allow cycle training over a broad range of pedalling cadences (5-60 rev/min) to promote both muscular strength and cardiorespiratory fitness. A commercially available motorized cycle ergometer was integrated with a custom built FES system, a laptop computer, and a specialized chair that restricted lateral leg movements. Sample biomechanical data were collected from an SCI subject performing FES cycling to demonstrate the IFES-LCE's performance characteristics. Calibration of the IFES-LCE system revealed a linear relationship between torque applied to the axle of the motorized ergometer and the braking motor current generated to maintain velocity. Performance data derived from iFES-LCE motor torque agreed closely with similar data collected using strain-gauge instrumented pedals (cross-correlations = 0.93-0.98). The iFES-LCE was shown to work well across a range of pedaling cadences. We conclude that the new iFES-LCE system may offer improved training potential by allowing cycling over a broad range of pedaling cadences, especially low cadence. This device also improves upon the accuracy of other ergometers by adjusting for the passive load of the legs.
- Subjects :
- medicine.medical_specialty
Neurology & Neurosurgery
business.industry
Work (physics)
Isokinetic Exercise
General Medicine
Physical strength
Axle
Anesthesiology and Pain Medicine
Physical medicine and rehabilitation
Neurology
medicine
Torque
Functional electrical stimulation
Cycle ergometer
Neurology (clinical)
Cadence
business
Simulation
Subjects
Details
- ISSN :
- 10947159
- Volume :
- 7
- Database :
- OpenAIRE
- Journal :
- Neuromodulation: Technology at the Neural Interface
- Accession number :
- edsair.doi.dedup.....128e89153eb74c4da463cab33484d6d5
- Full Text :
- https://doi.org/10.1111/j.1525-1403.2004.04007.x