Concurrent validity and reliability of a mobile iOS application used to assess calf raise test kinematics

Abstract

Background:Calf raise test (CRT) is used in rehabilitation and sports medicine to evaluate calf muscle function. The Calf Raise application (CRapp) uses computer-vision algorithms to objectively measure CRT outcomes and replicate laboratory-based metrics that are difficult to measure clinically.Objective:To validate the CRapp by examining its concurrent validity and agreement levels against laboratory-based equipment, and its intra- and inter-rater reliability.Design:Observational cross-sectional validation study. MethodsCRT outcomes (i.e., repetitions, positive work, total height, peak height, fatigue index, and peak power) were assessed in thirteen individuals (6 males, 7 females) on three occasions on both legs using the CRapp, 3D motion capture, and force plate simultaneously. Data were extracted from two markers: below lateral malleolus (n = 77) and on the heel (n = 77). Concurrent validity and agreement were determined from 154 data files using intraclass correlation coefficients (ICC3,k), typical errors expressed as coefficient of variations (CV), and Bland-Altman plots to assess biases and precision. Reliability was assessed using ICC3,1 and CV values. ResultsValidity of CRapp outcomes was good to excellent across measures for both markers (mean ICC ≥0.878), precision plots showing good agreement and precision. CV ranged from 0% (repetitions) to 33.3% (fatigue index) and were on average better for the lateral malleolus marker. Inter- and intra-rater reliability were excellent (ICC≥0.949, CV ≤ 5.6%).Conclusion:CRapp is valid and reliable within and between users for measuring CRT outcomes in healthy adults. CRapp provides a tool to objectivise CRT outcomes in research and practice, aligning with recent advances in mobile technologies and their increased use in healthcare.