Selective neural stimulation methods improve cycling exercise performance after spinal cord injury: a case series Article Swipe
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· 2021
· Open Access
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· DOI: https://doi.org/10.1186/s12984-021-00912-5
Background Exercise after paralysis can help prevent secondary health complications, but achieving adequate exercise volumes and intensities is difficult with loss of motor control. Existing electrical stimulation-driven cycling systems involve the paralyzed musculature but result in rapid force decline and muscle fatigue, limiting their effectiveness. This study explores the effects of selective stimulation patterns delivered through multi-contact nerve cuff electrodes on functional exercise output, with the goal of increasing work performed and power maintained within each bout of exercise. Methods Three people with spinal cord injury and implanted stimulation systems performed cycling trials using conventional (S-Max), low overlap (S-Low), low duty cycle (C-Max), and/or combined low overlap and low duty cycle (C-Low) stimulation patterns. Outcome measures include total work (W), end power (P end ), power fluctuation indices (PFI), charge accumulation (Q), and efficiency (η). Mann–Whitney tests were used for statistical comparisons of W and P end between a selective pattern and S-Max. Welch’s ANOVAs were used to evaluate differences in PFIs among all patterns tested within a participant (n ≥ 90 per stimulation condition). Results At least one selective pattern significantly (p < 0.05) increased W and P end over S-Max in each participant. All selective patterns also reduced Q and increased η compared with S-Max for all participants. C-Max significantly (p < 0.01) increased PFI, indicating a decrease in ride smoothness with low duty cycle patterns. Conclusions Selective stimulation patterns can increase work performed and power sustained by paralyzed muscles prior to fatigue with increased stimulation efficiency. While still effective, low duty cycle patterns can cause inconsistent power outputs each pedal stroke, but this can be managed by utilizing optimized stimulation levels. Increasing work and sustained power each exercise session has the potential to ultimately improve the physiological benefits of stimulation-driven exercise.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1186/s12984-021-00912-5
- https://jneuroengrehab.biomedcentral.com/track/pdf/10.1186/s12984-021-00912-5
- OA Status
- gold
- Cited By
- 11
- References
- 55
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3186677817
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3186677817Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1186/s12984-021-00912-5Digital Object Identifier
- Title
-
Selective neural stimulation methods improve cycling exercise performance after spinal cord injury: a case seriesWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-07-23Full publication date if available
- Authors
-
Kristen Gelenitis, Kevin M. Foglyano, Lisa M. Lombardo, Ronald J. TrioloList of authors in order
- Landing page
-
https://doi.org/10.1186/s12984-021-00912-5Publisher landing page
- PDF URL
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https://jneuroengrehab.biomedcentral.com/track/pdf/10.1186/s12984-021-00912-5Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://jneuroengrehab.biomedcentral.com/track/pdf/10.1186/s12984-021-00912-5Direct OA link when available
- Concepts
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Spinal cord injury, Stimulation, Duty cycle, Physical medicine and rehabilitation, Cycling, Functional electrical stimulation, Medicine, Rehabilitation, Physical therapy, Work (physics), Spinal cord, Anesthesia, Psychology, Neuroscience, Power (physics), Internal medicine, Physics, Quantum mechanics, Archaeology, Thermodynamics, HistoryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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11Total citation count in OpenAlex
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2025: 3, 2024: 3, 2023: 1, 2022: 4Per-year citation counts (last 5 years)
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55Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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