ArticleJMIR mHealth and uHealth2017
iPhone Sensors in Tracking Outcome Variables of the 30-Second Chair Stand Test and Stair Climb Test to Evaluate Disability: Cross-Sectional Pilot Study.
Article in JMIR mHealth and uHealth, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Can the Eight Hop Test Be Measured with Sensors? A Systematic Review.Sensors (Basel, Switzerland) · 2022Pooled it
- Artificial Intelligence-Based Proximal Bone Shape Asymmetry Analysis and Clinical Correlation with Cartilage Relaxation Times and Functional Activity.Bioengineering (Basel, Switzerland) · 2026Article
- Reliability of digitally instructed self-reported 30-second chair stand test for lower extremity function.Osteoarthritis and cartilage open · 2025Article
- Smartphone Technology to Facilitate Remote Postural Balance Assessment in Acute Concussion Management: Pilot Study.Sensors (Basel, Switzerland) · 2024Article
- Telemental health in emergency care settings: A qualitative analysis of considerations for sustainability and spread.Academic emergency medicine : official journal of the Society for Academic Emergency Medicine · 2023Article
- Smart Technology and Orthopaedic Surgery: Current Concepts Regarding the Impact of Smartphones and Wearable Technology on Our Patients and Practice.Current reviews in musculoskeletal medicine · 2021Review
- Telehealth in emergency medicine: A consensus conference to map the intersection of telehealth and emergency medicine.Academic emergency medicine : official journal of the Society for Academic Emergency Medicine · 2021Article
- Remote Assessment of Functional Mobility and Strength in Older Cancer Survivors: Protocol for a Validity and Reliability Study.JMIR research protocols · 2020Article
- Applying a User-Centered Approach to Building a Mobile Personal Health Record App: Development and Usability Study.JMIR mHealth and uHealth · 2019Article
- Use of Smartphone-Based Head-Mounted Display Devices to View a Three-Dimensional Dissection Model in a Virtual Reality Environment: Pilot Questionnaire Study.JMIR medical education · 2019Article
- Test-retest reliability of a smartphone app for measuring core stability for two dynamic exercises.PeerJ · 2019Article
- Digital Analysis of Sit-to-Stand in Masters Athletes, Healthy Old People, and Young Adults Using a Depth Sensor.Healthcare (Basel, Switzerland) · 2018Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
backgroundPerformance tests are important to characterize patient disabilities and functional changes. The Osteoarthritis Research Society International and others recommend the 30-second Chair Stand Test and Stair Climb Test, among others, as core tests that capture two distinct types of disability during activities of daily living. However, these two tests are limited by current protocols of testing in clinics. There is a need for an alternative that allows remote testing of functional capabilities during these tests in the osteoarthritis patient population.
objectiveObjectives are to (1) develop an app for testing the functionality of an iPhone's accelerometer and gravity sensor and (2) conduct a pilot study objectively evaluating the criterion validity and test-retest reliability of outcome variables obtained from these sensors during the 30-second Chair Stand Test and Stair Climb Test.
methodsAn iOS app was developed with data collection capabilities from the built-in iPhone accelerometer and gravity sensor tools and linked to Google Firebase. A total of 24 subjects performed the 30-second Chair Stand Test with an iPhone accelerometer collecting data and an external rater manually counting sit-to-stand repetitions. A total of 21 subjects performed the Stair Climb Test with an iPhone gravity sensor turned on and an external rater timing the duration of the test on a stopwatch. App data from Firebase were converted into graphical data and exported into MATLAB for data filtering. Multiple iterations of a data processing algorithm were used to increase robustness and accuracy. MATLAB-generated outcome variables were compared to the manually determined outcome variables of each test. Pearson's correlation coefficients (PCCs), Bland-Altman plots, intraclass correlation coefficients (ICCs), standard errors of measurement, and repeatability coefficients were generated to evaluate criterion validity, agreement, and test-retest reliability of iPhone sensor data against gold-standard manual measurements.
resultsApp accelerometer data during the 30-second Chair Stand Test (PCC=.890) and gravity sensor data during the Stair Climb Test (PCC=.865) were highly correlated to gold-standard manual measurements. Greater than 95% of values on Bland-Altman plots comparing the manual data to the app data fell within the 95% limits of agreement. Strong intraclass correlation was found for trials of the 30-second Chair Stand Test (ICC=.968) and Stair Climb Test (ICC=.902). Standard errors of measurement for both tests were found to be within acceptable thresholds for MATLAB. Repeatability coefficients for the 30-second Chair Stand Test and Stair Climb Test were 0.629 and 1.20, respectively.
conclusionsApp-based performance testing of the 30-second Chair Stand Test and Stair Climb Test is valid and reliable, suggesting its applicability to future, larger-scale studies in the osteoarthritis patient population.
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