ReviewJournal of physical therapy science2023
Reliability and validity of quantitative evaluation of anticipatory postural adjustments using smartphones.
Review in Journal of physical therapy science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Correlation Between Pain Intensity and Trunk Sway in Seated Posture Among Office Workers with Chronic Spinal Pain: A Pilot Field-Based Study.Sensors (Basel, Switzerland) · 2025Article
- Patients with chronic ankle instability exhibit increased sensorimotor cortex, dorsolateral prefrontal cortex, and superior temporal gyrus activation during single-leg stance: a functional near-infrared spectroscopy study.Frontiers in human neuroscience · 2025Article
- Association between freezing of gait and anticipatory postural adjustments in Parkinson's disease.Journal of physical therapy science · 2024Article
- Enhancing public health in developing nations through smartphone-based motor assessment.Frontiers in digital health · 2024Article
- Editorial: Natural products and pseudo-natural products against veterinary disease-causing microorganisms.Frontiers in veterinary science · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
[Purpose] This study aimed to investigate the reliability and validity of the quantitative evaluation of anticipatory postural adjustments using smartphones. [Participants and Methods] The study included 10 young control participants who underwent a one-legged stance with an accelerometer and a smartphone that were simultaneously attached to their lower back (L5). Acceleration was measured as the mediolateral component of the lumbar movement toward the stance side. The peak value of the time (peak latency) and the amount of displacement (peak magnitude) in the stance side direction of the lumbar acceleration were analyzed as anticipatory postural adjustment features. Intra-rater reliability was calculated for both accelerometer and smartphone measurements, while inter-rater reliability was calculated for smartphone measurements by two examiners. Validity was determined for both accelerometer and smartphone measurements. [Results] In this study, the intra-rater reliability of the peak latency and peak magnitude in accelerometer and smartphone measurements was confirmed, as was the inter-rater reliability in smartphone measurements. The intra-rater reliability was confirmed through re-testing, while the validity of the accelerometer and smartphone measurements was also confirmed. [Conclusion] The findings of this study suggest that the use of smartphones to measure anticipatory postural adjustments is highly reliable and valid, making it a useful clinical balance index. The method is simple and can be used for continuous patient monitoring.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.