Personalized Interactive Music Systems for Physical Activity and Exercise: Exploratory Systematic Review and Meta-Analysis
Authors:
- Andrew DansoADAndrew Danso
- Tiia KekäläinenTKTiia Kekäläinen
- Friederike KoehlerFKFriederike Koehler
- Keegan KnittleKKKeegan Knittle
- Patti NijhuisPNPatti Nijhuis
- Iballa BurunatIBIballa Burunat
- Pedro NetoPNPedro Neto
- Anastasios MavrolampadosAMAnastasios Mavrolampados
- William M RandallWRWilliam M Randall
- Niels Chr HansenNHNiels Chr Hansen
- Alessandro AnsaniAlessandro Ansani
- Timo RantalainenTRTimo Rantalainen
Open Access
- 8 September 2025
- journal article
- review article
- Published by JMIR Publications Inc. in JMIR Human Factors
- Vol. 12, e70372
Abstract
Background: Personalized Interactive Music Systems (PIMSs) are emerging as promising devices for enhancing physical activity and exercise outcomes. By leveraging real-time data and adaptive technologies, PIMSs align musical features, such as tempo and genre, with users’ physical activity patterns, including frequency and intensity, enhancing their overall experience. Objective: This exploratory systematic review and meta-analysis evaluates the effectiveness of PIMSs across physical, psychophysical, and affective domains. Methods: Searches across 9 databases identified 18 eligible studies, of which 6 (comprising 17 intervention arms) contained sufficient data for meta-analysis. Random-effects meta-analyses and meta-regression were performed to assess outcomes for physical activity levels, physical exertion, ratings of perceived exertion, and affective valence. Results: Results showed significant improvements in physical activity levels (g=0.49, CI 0.07 to 0.91, P=.02, k=4) and affective valence (g=1.65, CI 0.35 to 2.96, P=.01, k=4), with faster music tempo identified as a significant moderator (P=.03). No significant effects were observed for ratings of perceived exertion (g=0.72, CI −0.13 to 1.58, P=.10, k=3) or physical exertion (g=0.78, CI −0.55 to 2.11, P=.25, k=5). Conclusions: Substantial heterogeneity and limited study quality indicate the need for more robust, randomized controlled trials to establish the efficacy of PIMSs in diverse populations.Keywords
All Related Versions
This publication has 62 references indexed in Scilit:
- Context-Aware Music Recommender System Based on Automatic Detection of the User’s Physical Activity2020
- Risk‐of‐bias VISualization (robvis): An R package and Shiny web app for visualizing risk‐of‐bias assessmentsResearch Synthesis Methods, 2020
- Music‐Related Interventions in the Exercise Domain2020
- Updated guidance for trusted systematic reviews: a new edition of the Cochrane Handbook for Systematic Reviews of InterventionsCochrane Database of Systematic Reviews, 2019
- The SoundBike: musical sonification strategies to enhance cyclists’ spontaneous synchronization to external musicJournal on Multimodal User Interfaces, 2018
- Affective–Reflective Theory of physical inactivity and exerciseGerman Journal of Exercise and Sport Research, 2017
- The Behavior Change Technique Taxonomy (v1) of 93 Hierarchically Clustered Techniques: Building an International Consensus for the Reporting of Behavior Change InterventionsAnnals of Behavioral Medicine, 2013
- moBeat: Using Interactive Music to Guide and Motivate Users During Aerobic ExercisingApplied Psychophysiology and Biofeedback, 2011
- Role of tempo entrainment in psychophysiological differentiation of happy and sad music?International Journal of Psychophysiology, 2008
- Metabolic equivalents (METS) in exercise testing, exercise prescription, and evaluation of functional capacityClinical Cardiology, 1990