Design of a Soft Upper Body Exosuit to Reduce Strain on Trunk Muscles During Gait
Bibliographic record
Abstract
Trunk lean is a phenomenon that occurs naturally in humans during gait, believed to help maintain stability by moving the body’s center of gravity over the base of support. However, excessive strain on the trunk muscles can lead to injury. This is especially relevant to the elderly who have a more pronounced trunk lean and reduced gait speed, as the trunk is key to gait stability. Therefore, the motivation for this project was to investigate if a soft upper body exosuit can assist in gait by reducing strain on the trunk muscles during trunk lean thereby improving stability, ease of gait, and lowering risk of injury. The first phase of the project was a literature review to see what work had been done regarding upper body exosuits and to see what can be done to improve upon/modify existing designs to be optimized for targeting trunk lean. The next phase was mathematically modelling the upper body to guide the design of the exosuit’s torque requirements. This model used static moment analysis using published data on the locations of the center of mass of various limbs. Following this was the CAD design and fabrication of the exosuit, of which two prototypes were constructed, as the first lacked sufficient strength due to a numerical error. The suit is actuated via a cable system in which two motors, mounted at the base of the neck, route cables down the back and anchor them at the thighs. The tension can then be adjusted by the user to match whatever their natural trunk lean angle is. Future work for this project includes incorporating an IMU so the tension can be adjusted dynamically based on the user’s trunk lean angle at any given time, as well as improving the device’s structural integrity to improve durability.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".