An Experimental Study on the Validity and Reliability of a Smartphone Application to Acquire Temporal Variables during the Single Sit-to-Stand Test with Older Adults

Abstract

Smartphone sensors have often been proposed as pervasive measurement systems to assess mobility in older adults due to their ease of use and low-cost. This study analyzes a smartphone-based application’s validity and reliability to quantify temporal variables during the single sit-to-stand test with institutionalized older adults. Forty older adults (20 women and 20 men; 78.9 ± 8.6 years) volunteered to participate in this study. All participants performed the single sit-to-stand test. Each sit-to-stand repetition was performed after an acoustic signal was emitted by the smartphone app. All data were acquired simultaneously with a smartphone and a digital video camera. The measured temporal variables were stand-up time and total time. The relative reliability and systematic bias inter-device were assessed using the intraclass correlation coefficient (ICC) and Bland-Altman plots. In contrast, absolute reliability was assessed using the standard error of measurement and coefficient of variation (CV). Inter-device concurrent validity was assessed through correlation analysis. The absolute percent error (APE) and the accuracy were also calculated. The results showed excellent reliability (ICC = 0.92–0.97; CV = 1.85–3.03) and very strong relationships inter-devices for the stand-up time (r = 0.94) and the total time (r = 0.98). The APE was lower than 6%, and the accuracy was higher than 94%. Based on our data, the findings suggest that the smartphone application is valid and reliable to collect the stand-up time and total time during the single sit-to-stand test with older adults.

System for Tracking and Evaluating Performance (Step-App®): validation and clinical application of a mobile telemonitoring system in patients with knee and hip total arthroplasty. A prospective cohort study

“…Lastly, STS is a simple test routinely used in rehabilitation clinical practice to assess lower limb muscle strength and physical performance, and different mobile applications have been proposed to digitally evaluate this outcome measure. 51 - 53 On the other hand, the currently available applications were not wearable, required different instruments, 53 or were validated for a single or five repetitions. 51 , 52 Thus, to our knowledge, this is the first mobile application for the assessment of the 30STS test.…”

“… 51 - 53 On the other hand, the currently available applications were not wearable, required different instruments, 53 or were validated for a single or five repetitions. 51 , 52 Thus, to our knowledge, this is the first mobile application for the assessment of the 30STS test.…”

Estimation of Functional Aerobic Capacity Using the Sit-to-Stand Test in Older Adults with Heart Failure with Preserved Ejection Fraction

“…A cardiopulmonary exercise test should assess the VO 2 peak in future studies. Future studies could also assess the STS test using smartphone applications or inertial sensors to quantify temporal variables and other interesting functional kinematic variables during the 5-STS [ 63 ]. As BMI affected the 5-STS and 6MWT performance, future studies should assess the relationship between BMI and body composition and physical functional performance in older adults with HFpEF [ 50 , 64 ].…”

Towards Detecting Pneumonia Progression in COVID-19 Patients by Monitoring Sleep Disturbance Using Data Streams of Non-Invasive Sensor Networks

“…Such pre-processing can include basic validation of the user inputs by making sure that they are within reasonable ranges, or more advanced processing based on machine learning, signal processing, or time series analysis algorithms. For example, such methods can be implemented within a mobile application on the edge to identify patterns and measure the results of various functional tests, such as the Heel-Rise test [ 33 ], Sit-to-Stand test [ 34 ], Functional Reach Test [ 35 ], or the Timed Up and Go test [ 36 ]. In some cases, these tests’ results could be directly calculated within the mobile app and then provided as already-processed results to the cloud.…”