Mapping of electrodermal activity (EDA) during outdoor community-level mobility tasks in individuals with lower-limb amputation
Bibliographic record
Abstract
INTRODUCTION: Balance confidence and perception of task challenge is an important construct to measure in rehabilitation of people with lower-limb amputation (LLA). Measurement of electrodermal activity (EDA) captures physiological arousal responses reflecting an individual's perceived challenge in a task. This study explores the feasibility of the use of EDA during outdoor walking tasks to capture task-specific physiological arousal changes associated with perception of challenge in people with amputation. OBJECTIVE: To develop and demonstrate feasibility of a portable EDA/GPS system mapping physiological arousal while challenging walking balance outdoors in individuals with LLA and controls. METHODS: Sixteen people (eight with LLA and eight age-/sex-matched controls) completed an outdoor walking course in the community (3 laps). A battery-powered portable device was developed containing EDA/GPS sensors with data logged on a microcontroller. Phasic EDA response was extracted from EDA signal to explore the physiological arousal response to walking tasks. RESULTS: Physiological arousal demonstrated task-specific modulation with ascending stairs without a handrail showing higher levels of phasic EDA than walking on a paved incline (p = 0.01) or a gravel decline (p = 0.01) in people with LLA. While evidence of habituation over repeated trials was shown in controls with lap 1 of walking down a gravel decline showing higher levels of phasic EDA than lap 3 (p = 0.01). Phasic EDA maps, representative of arousal levels throughout the walking course, showed individual-specific response. CONCLUSION: Mapping of EDA during outdoor walking is feasible. Modulation of physiological arousal between outdoor walking tasks and over repeated trials is suggestive of clinical utility. Further research is warranted to explore how EDA may be incorporated into assessment of response to outdoor walking amongst individuals following LLA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".