Validation of A single sensor-based Remote Six-Minute Walk Test
Bibliographic record
Abstract
Abstract Background The six-minute walk test (6MWT) is a cornerstone measure of functional capacity, yet its standard corridor-based protocol demands a 30 m hallway, trained staff, and scripted encouragement. These logistical barriers limit accessibility and add cost. Efforts to overcome these limitations with smartphone sensors have fallen short: several studies report 8–40 percent under-estimation and a hard 500 m ceiling in the Apple Watch/iPhone algorithm. Dedicated inertial wearables, placed on a stable limb segment and sampled at high frequency, may achieve clinic-grade accuracy with few environment and logistical constraints. Objective To establish whether the Ambulosono thigh-mounted sensor provides equivalent time-scaled 6MWT distance in supervised and unsupervised environments, and to determine whether auditory cues—silence, American Thoracic Society (ATS) verbal encouragement, or rhythmic music—affect performance. Methods Seventy-six healthy university students performed up to three 6MWTs in two settings: (1) a supervised 12 ± 2 m indoor lane and (2) a self-selected 10–20 m route at home or on campus. Ambulosono recorded all-step walking distance, already rescaled to an exact six minutes by the accompanying mobile application. Duplicate trials within a Setting × Auditory-Condition cell were averaged, yielding 117 unique subject-records. Independent Welch t-tests compared structured and naturalistic distances within each auditory condition; effect size was expressed as Cohen d. Distance distributions were visualised with box-plots, over-laid histograms, and violin plots. Group means were benchmarked against contemporary reference values. Results Scaled 6-min distance ranged from 388 to 481 m across the six Setting × Condition groups. Structured trials exceeded naturalistic trials by 37 m (music), 52 m (verbal), and 61 m (silent); however, none of these differences reached statistical significance (all p > 0.05; d ≤ 0.70) and all lay within Ambulosono’s validated ±5 percent systematic error band. Distance distributions overlapped almost completely. Every group mean fell inside the 400–520 m reference band reported for 18-to 25-year-old walking on 10–20 m lanes who have similar anthropomorphic features and ethic background. Conclusions After rigorous time normalisation, Ambulosono delivers environment-independent 6MWT distance in healthy young adults and meets modern short-lane normative values. These findings support the use of dedicated wearables for remote functional-capacity monitoring and underscore the current limitations of smartphone-only solutions.
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 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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".