Activity Monitor Placed at the Nonparetic Ankle Is Accurate in Measuring Step Counts During Community Walking in Poststroke Individuals: A Validation Study
Bibliographic record
Abstract
BACKGROUND: Different environmental factors may affect the accuracy of step-count activity monitors (AM). However, the validation conditions for AM accuracy largely differ from ecological environments. OBJECTIVES: To assess and compare the accuracy of AM in counting steps among poststroke individuals: during different locomotor tasks, with AM placed at the nonparetic ankle or hip, and when walking in a laboratory or inside a mall. DESIGN: Validation study. SETTINGS: Laboratory and community settings. PARTICIPANTS: Twenty persons with chronic hemiparesis, independent walkers. METHODS: First session: participants performed level walking (6-minute walk test [6MWT]), ramps, and stairs in the laboratory with AM placed at the nonparetic ankle and hip. Second session: participants walked a mall circuit, including the three tasks, with AM placed at the nonparetic ankle. The sessions were video recorded. MAIN OUTCOME MEASUREMENTS: Absolute difference between the steps counted by AM and the steps viewed on the video recordings (errors, %); occurrence of errors greater than 10%. RESULTS: Median errors were similar for the 6MWT (0.86 [0.22, 7.70]%), ramps (2.17 [0.89, 9.61]%), and stairs (8.33 [2.65, 19.22]%) with AM at the ankle. Step-count error was lower when AM was placed at the ankle (8.33 [2.65, 19.22]%) than at the hip (9.26 [3.25, 42.63]%, P = .03). The greatest errors were observed among the slowest participants (≤0.4 m/s) on ramps and stairs, whereas some faster participants (>1 m/s) experienced the greatest error during the 6MWT. Median error was slightly increased in the mall circuit (2.67 [0.61, 12.54]%) compared with the 6MWT (0.50 [0.24, 6.79]%, P = .04), with more participants showing errors >10% during the circuit (7 vs 2, P = .05). CONCLUSIONS: Step counts are accurately measured with AM placed at the nonparetic ankle in laboratory and community settings. Accuracy can be altered by stairs and ramps among the slowest walkers and by prolonged walking tasks among faster walkers. LEVEL OF EVIDENCE: III.
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 | 0.000 |
| 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 | 0.000 |
| 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".