Lower Extremity Muscle Activation In Hypermobile Ehlers-Danlos Syndrome
Bibliographic record
Abstract
Hypermobility related conditions (HM) such as hypermobile type Ehlers Danlos Syndrome (hEDS) are characterized by hypermobility of the joints, pain, fatigue, and weakness. Recently, we found no significant difference in cost of transport or muscle dynamics between HM and age- and sex-matched control participants despite significantly higher self-reported pain and lower plantarflexor strength in HM. Weaker muscles require a higher level of activation to produce a given force, which may explain high self-reported walking pain and fatigue in HM. PURPOSE: To assess the effect of HM and speed on muscle activation of lower-extremity muscles during walking. METHODS: 10 HM (33.7 ± 14.6 years; 71.4 ± 11.3 kg; 169.7 ± 6.7 cm) and 10 age- and sex- matched control participants (32.9 ± 14.8 years; 66.8 ± 15.2 kg; 165.6 ± 10.4 cm) walked at 80%, 100% and 120% of their preferred walking speed on a motorized treadmill for 6 minutes at each speed. EMG sensors placed on the lateral gastrocnemius (LG), soleus (SOL), tibialis anterior (TA) and fibularis longus (FL) were used to quantify average root mean square (RMS) amplitude throughout the gait cycle, which was quantified from 10 consecutive strides during the last minute at each speed. RMS was normalized to mean activities over the gait cycle at the preferred speed. A three-way repeated measures ANOVA (speed x gait cycle phase x group) was used to assess differences in muscle activity across the gait cycle between groups and speeds. RESULTS: There were no significant differences in preferred walking speed (HM: 1.06 ± 0.31 m/s; CON: 1.17 ± 0.28 m/s, p = 0.31), but HM were ~ 50% weaker (p < 0.05) and reported ~30% greater pain (p = 0.009) compared to CON. Muscle activity increased with speed (p < 0.0001). A significant phase x group interaction for LG and SOL was seen. Across muscles, HM RMS was significantly lower during swing compared to CON at both slow and fast speeds (p < 0.05). Muscle coactivation (SOL/TA and LG/TA) was not significantly different across speeds or between groups (p > 0.245). CONCLUSIONS: Our results suggest similar activity of lower-extremity muscles between HM and controls, despite greater weakness and pain in HM. These results support the notion that lower-extremity ankle joint work and/or power may be reduced in HM to compensate for lower extremity muscle weakness.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".