ArticleJMIR mHealth and uHealth2018
A Wearable Sensor-Based Exercise Biofeedback System: Mixed Methods Evaluation of Formulift.
Article in JMIR mHealth and uHealth, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 24 citations in OpenAlex.
- Wearable Sensor-Based Exercise Biofeedback for Orthopaedic Rehabilitation: A Mixed Methods User Evaluation of a Prototype System.Sensors (Basel, Switzerland) · 2019Trial
- Persian adaptation and validation of the user version of The Mobile Application Rating Scale (uMARS).PloS one · 2025Article
- Clinical Utility and Usability of the Digital Box and Block Test: Mixed Methods Study.JMIR rehabilitation and assistive technologies · 2024Article
- Attributes, Methods, and Frameworks Used to Evaluate Wearables and Their Companion mHealth Apps: Scoping Review.JMIR mHealth and uHealth · 2024Article
- Assessment of an IMU-Based Experimental Set-Up for Upper Limb Motion in Obese Subjects.Sensors (Basel, Switzerland) · 2023Article
- The Role and Importance of Using Sensor-Based Devices in Medical Rehabilitation: A Literature Review on the New Therapeutic Approaches.Sensors (Basel, Switzerland) · 2023Review
- Alberta Rating Index for Apps: Study of Reliability and Validity.Canadian journal of occupational therapy. Revue canadienne d'ergotherapie · 2022Article
- Spanish adaptation and validation of the User Version of the Mobile Application Rating Scale (uMARS).Journal of the American Medical Informatics Association : JAMIA · 2021Article
- A Biofeedback App for Migraine: Development and Usability Study.JMIR formative research · 2021Article
- The WOMEN-UP Solution, a Patient-Centered Innovative e-Health Tool for Pelvic Floor Muscle Training: Qualitative and Usability Study during Early-Stage Development.International journal of environmental research and public health · 2021Article
- ExerSense: Physical Exercise Recognition and Counting Algorithm from Wearables Robust to Positioning.Sensors (Basel, Switzerland) · 2020Article
- Comparing the Usability and Acceptability of Wearable Sensors Among Older Irish Adults in a Real-World Context: Observational Study.JMIR mHealth and uHealth · 2020Observational
- Measuring Mental Effort for Creating Mobile Data Collection Applications.International journal of environmental research and public health · 2020Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundFormulift is a newly developed mobile health (mHealth) app that connects to a single inertial measurement unit (IMU) worn on the left thigh. The IMU captures users' movements as they exercise, and the app analyzes the data to count repetitions in real time and classify users' exercise technique. The app also offers feedback and guidance to users on exercising safely and effectively.
objectiveThe aim of this study was to assess the Formulift system with three different and realistic types of potential users (beginner gym-goers, experienced gym-goers, and qualified strength and conditioning [S&C] coaches) under a number of categories: (1) usability, (2) functionality, (3) the perceived impact of the system, and (4) the subjective quality of the system. It was also desired to discover suggestions for future improvements to the system.
methodsA total of 15 healthy volunteers participated (12 males; 3 females; age: 23.8 years [SD 1.80]; height: 1.79 m [SD 0.07], body mass: 78.4 kg [SD 9.6]). Five participants were beginner gym-goers, 5 were experienced gym-goers, and 5 were qualified and practicing S&C coaches. IMU data were first collected from each participant to create individualized exercise classifiers for them. They then completed a number of nonexercise-related tasks with the app. Following this, a workout was completed using the system, involving squats, deadlifts, lunges, and single-leg squats. Participants were then interviewed about their user experience and completed the System Usability Scale (SUS) and the user version of the Mobile Application Rating Scale (uMARS). Thematic analysis was completed on all interview transcripts, and survey results were analyzed.
resultsQualitative and quantitative analysis found the system has "good" to "excellent" usability. The system achieved a mean (SD) SUS usability score of 79.2 (8.8). Functionality was also deemed to be good, with many users reporting positively on the systems repetition counting, technique classification, and feedback. A number of bugs were found, and other suggested changes to the system were also made. The overall subjective quality of the app was good, with a median star rating of 4 out of 5 (interquartile range, IQR: 3-5). Participants also reported that the system would aid their technique, provide motivation, reassure them, and help them avoid injury.
conclusionsThis study demonstrated an overall positive evaluation of Formulift in the categories of usability, functionality, perceived impact, and subjective quality. Users also suggested a number of changes for future iterations of the system. These findings are the first of their kind and show great promise for wearable sensor-based exercise biofeedback systems.
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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.