The Effect of Cycling While Typing on Patterns of Upper Body Muscle Activation
Bibliographic record
Abstract
OBJECTIVE: To investigate the effect of one's sex and pedaling intensity on upper body muscle activation patterns during typing while cycling. BACKGROUND: Females are at a higher risk for computer work-related musculoskeletal disorders, and mobile workstations have been suggested to induce healthier muscular patterns compared with sitting. However, the neuromuscular characteristics of performing computer work in a cycling workstation have not been investigated. METHOD: Twenty-two participants (10 females) completed a 60-min computer typing task while pedaling on a cycle ergometer at two different intensities (25%, 4% heart rate reserve). Surface electromyography (EMG) was recorded from seven muscles of the upper body. Effects of time, sex, and intensity were assessed for muscle activation (RMS), activation variability (CV), and normalized mutual information (NMI) via generalized estimating equations. RESULTS: With time, neck/shoulder CV increased in males during higher pedaling intensity, whereas in females it decreased during lower intensity. In females, RMS of neck/shoulder and NMI of neck/shoulder muscle pairs were lower, whereas forearm RMS was 34.2% higher with higher intensity cycling compared with lower intensity. Lower back RMS decreased 28.3% in the initial half of the task in females, but in males it increased 14.4% in the later half. CONCLUSION AND APPLICATION: Cycling workstation showed a sex- and intensity-specific EMG response. These differing responses should be considered when implementing the use of cycling workstation and may be important for preventing/managing sex-specific muscle fatigue and musculoskeletal disorders.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".