Closed-loop control of ankle plantarflexors and dorsiflexors using an inverted pendulum apparatus: A pilot study
Bibliographic record
Abstract
Considerable demand exists for a device to facilitate hands-free, stable stance in individuals with neurological disorders such as spinal cord injury (SCI) and stroke. In this regard, applying functional electrical stimulation (FES) to muscles of the lower limbs in closed loop has shown promise. In particular, it has been suggested that a PID control strategy could offer functional benefits to stability by mimicking the neurological control strategy employed in able-bodied stance. In this proof of concept study, we tested this assertion by examining the potential of a PID control strategy with gravity compensation to effectively maintain balance during quiet stance by regulating FES-induced contractions of the ankle plantarflexors and dorsiflexors in able-bodied individuals. A novel Inverted Pendulum Standing Apparatus (IPSA) was employed to simulate quiet stance whilst minimizing the voluntary control of able-bodied subjects. Quiet and perturbed standing trials were performed in 3 able-bodied subjects. Performance metrics including those pertaining to stability during quiet stance (root mean square difference), perturbation rejection capabilities (settling time, peak deviation), and ability to transition from an offset initial position (settling time), were examined. For all 3 subjects and for all of the metrics examined, our results showed that the proposed closed-loop controlled FES system improved performance in comparison to voluntary control. These results indicate that the PID plus gravity control strategy used in this study offers meaningful benefits over voluntary control in terms of standing stability. Thus, the controller could potentially be applied to the problem of improving or restoring standing ability in some neurologic patient populations.
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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".