Utility of Portable Electromyography for Quantifying Muscle Activity during Daily Use
Bibliographic record
Abstract
BACKGROUND: Mobility has been studied using performance, questionnaire, pedometer and accelerometer measures, but these tools do not provide information about muscle activity. To better understand mechanisms associated with movement impairment as they relate to function, it is valuable to quantify muscle activity during everyday activities. OBJECTIVE: This report presents electromyography (EMG) during daily activities from the affected and unaffected limbs of a 74-year-old man who survived a stroke 12 years ago, compared to 7 older healthy men who had not experienced a stroke. METHODS: The biceps brachii, triceps brachii, quadriceps and hamstring muscles were recorded continuously for one 8-hour session in the unaffected limbs of the stroke survivor and control subjects. On a second day, EMG from these same muscles of the affected side was recorded for 4 h. Bursts (amplitude >2% maximum effort, duration >0.1 s) and gaps (amplitude <1% maximum effort, duration >0.1 s) of EMG were quantified for the number of times they occurred, mean event duration (seconds), mean peak amplitude (percent maximum voluntary efforts) and rate of activity (event activity/second). RESULTS: Burst and gap patterns of the unaffected limb muscles were similar between the stroke survivor and controls. Increased numbers of bursts (approx. 40%) and gaps (approx. 44%) were seen in the subject's lower limb muscles of his affected versus unaffected side. Biceps brachii burst activity of the affected limb was increased, whereas triceps brachii burst activity was decreased. These muscle activity changes in the affected limb suggest that the triceps brachii was relatively inactive and the biceps brachii and lower limb muscles were active in an 'on' and 'off' pattern. CONCLUSION: Muscle activity in the unaffected limb of the stroke survivor was similar compared to control subjects, but the affected limb differed from the unaffected after stroke. Portable EMG to monitor muscle activity for prolonged periods was not reported to be an impediment by the case or control subjects. Using this technology, EMG bursts and gaps can be recorded and used to describe muscle activity. Future work may consider the feasibility of this technique to monitor rehabilitation progression or long-term plasticity of muscle activity.
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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 | 0.000 |
| 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".