Deep Learning-Based Temporal Gait Analysis Using a Smartphone IMU in Older Adults with and Without Non-Specific Low Back Pain.
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DOI: 10.3390/bioengineering13080924
Bibliographic record from the original reports
Access labels embedded in these original reference strings are historical. Current access and exact checked components are stated separately below.
Vivar G, Singh S, Bea T, Saal C, Munoz-Martel V, Schega L. Deep Learning-Based Temporal Gait Analysis Using a Smartphone IMU in Older Adults with and Without Non-Specific Low Back Pain. Bioengineering (Basel, Switzerland). 2026;13(8):924. DOI 10.3390/bioengineering13080924 Source examined: Complete article text.
Conditions: COND-LBP Low back pain
Scoped audit evidence
These are source- and component-level audit summaries as of 3 October 2026. Access and comparison scope can differ by report; none certifies every result or the underlying raw data.
Low back pain
- current evidence level: fulltext
Source locator: Methods 2.1–2.4; Results 3.4–3.6; Limitations
Low back pain
- verification level: fulltext
28 older controls/18 NSLBP; same-signal CSAV-assisted manual labels, no Vicon reference; F 1.963/.988 and MAE 10.6/11.2 ms; external 22 young adults with 50% adaptation, zero-shot failure all match.
Source locator: Methods 2.1–2.4; Results 3.4–3.6; Limitations
Reports citing this source
- Gait assessment and prognosis in low back pain · reference 11 · original reference
Update record
- 2026-10-03: Created from the supplied reports and final scoped audit. New evidence should be appended with source version, access date, exact locator and affected report links.
Updating the wiki · Evidence and status guide