An Exploratory Investigation on the Use of Closed-Loop Electrical Stimulation to Assist Individuals with Stroke to Perform Fine Movements with Their Hemiparetic Arm
Bibliographic record
Abstract
Stroke is the leading cause of upper limb impairments resulting in disability. Modern rehabilitation includes training with robotic exoskeletons and functional electrical stimulation (FES). However, there is a gap in knowledge to define the detailed use of FES in stroke rehabilitation. In this paper, we explore applying closed-loop FES to the upper extremities of healthy volunteers and individuals with a hemiparetic arm resulting from stroke. We used a set of gyroscopes to monitor arm movements and used a non-linear controller, namely, the robust integral of the sign of the error (RISE), to assess the viability of controlling FES in closed loop. Further, we explored the application of closed-loop FES in improving functional tasks performed by individuals with stroke. Four healthy individuals of ages 27-32 years old and five individuals with stroke of ages 61-83 years old participated in this study. We used the Rehastim FES unit (Hasomed Ltd.) with real-time modulation of pulse width and amplitude. Both healthy and stroke individuals were tested in RISE-controlled single and multi-joint upper limb motions following first a sinusoidal trajectory. Individuals with stroke were also asked to perform the following functional tasks: picking up a basket, picking and placing an object on a table, cutting a pizza, pulling back a chair, eating with a spoon, as well as using a stapler and grasping a pen. Healthy individuals were instructed to keep their arm relaxed during the experiment. Most individuals with stroke were able to follow the sinusoid trajectories with their arm joints under the sole excitation of the closed-loop-controlled FES. One individual with stroke, who was unable to perform any of the functional tasks independently, succeeded in completing all the tasks when FES was used. Three other individuals with stroke, who were unable to complete a few tasks independently, completed some of them when FES was used. The remaining stroke participant was able to complete all tasks with and without FES. Our results suggest that individuals with a low Fugl-Meyer score or a higher level of disability may benefit the most with the use of closed-loop-controlled FES.
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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 | 0.001 | 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".