Effect of Spatially Distributed Sequential Stimulation on Fatigue in Functional Electrical Stimulation Rowing
Bibliographic record
Abstract
<i>Objective:</i> A critical limitation in clinical applications using functional electrical stimulation (FES) for rehabilitation exercises is the rapid onset of muscle fatigue. Spatially distributed sequential stimulation (SDSS) has been demonstrated to reduce muscle fatigue during FES compared to conventional single electrode stimulation (SES) in single joint movements. Here we investigated the fatigue reducing ability of SDSS in a clinical application, i.e., FES-rowing, in able-bodied (AB) participants. <i>Methods:</i> FES was delivered to the quadriceps and hamstring of 15 AB participants (five female, ten male) for fatiguing FES-rowing trials using SES and SDSS, participants rowed with voluntary arm effort while endeavoring to keep their legs relaxed. Fatigue was characterized by the time elapsed until a percent decrease occurred in power output (TTF), as well as the trial length indicating the time elapsed until the complete stop of rowing. <i>Result:</i> Trial length was significantly longer in SDSS rowing than in SES (t-test, <inline-formula> <tex-math notation="LaTeX">${p} < 0.01$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">${d}=0.71$ </tex-math></inline-formula>), with an average SDSS:SES trial length ratio of 1.31 ± 0.47. TTF<inline-formula> <tex-math notation="LaTeX">$_{SDSS}$ </tex-math></inline-formula> was significantly longer than TTF<inline-formula> <tex-math notation="LaTeX">$_{SES}$ </tex-math></inline-formula> with a median TTF<inline-formula> <tex-math notation="LaTeX">$_{SDSS}$ </tex-math></inline-formula>:TTF<inline-formula> <tex-math notation="LaTeX">$_{SES}$ </tex-math></inline-formula> ratio of 1.34 ranging from 1.03 to 5.41 (Wilcoxon Ranked Sum, <inline-formula> <tex-math notation="LaTeX">${p} < 0.01$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">${r}=0.62$ </tex-math></inline-formula>). No rower experienced a decrease in TTF with SDSS. <i>Conclusion:</i> SDSS reduced fatigue during FES-rowing when compared to SES in AB individuals, resulting in a lengthened FES-rowing period by approximately 30%. Application of SDSS would increase the effectiveness of FES-rowing as rehabilitative exercise for individuals with paralyses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".