Modelling and Evaluation of Piezoelectric Actuators for Wearable Neck Rehabilitation Devices
Bibliographic record
Abstract
Neck pain is the most common neck musculoskeletal disorder, and the fourth leading cause of healthy years lost due to disability in the world. Due to the need of hands-on physical therapy and Canada’s aging population, access to treatment will become highly constrained. Wearable devices that allow at-home rehabilitation address this future limitation. However, few have emerged from the laboratory setting because they are limited by the use of conventional actuators. An overlooked type of actuation technology is that of piezoelectric actuators, more specifically, travelling wave ultrasonic motors (TWUM).\nIn this work, a clear procedure that outlines how the required parameters within the hybrid TWUM model can be identified, as well as an assessment of the use of TWUMs within wearable devices for the neck, is presented. The procedure includes custom testing setups that were designed to identify the stator motion parameters, and the Coulomb coefficient of friction. The accuracy of the determined parameters were confirmed when the angular velocity of the hybrid model at different duty cycles was compared to the real TWUM being modelled, producing a coefficient of determination of 0.974. The model was then used to create a position control system that controlled the joints of a virtual robotic manipulator that modelled the neck. The manipulator exhibited a maximum absolute mean error of only 0.0289 m when simulating the required trajectories of range of motion exercises. This performance, in addition to the exemplary traits TWUMs express, demonstrate their potential to advance the field of wearable mechatronic devices.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".