Biofeedback in team settings: A systematic review of applications and outcomes
Biofeedback has shown great potential for enhancing individual performance, yet its application in team contexts remains underexplored. This systematic review examines how biofeedback functions within teams, identifying key design components and their impact on team effectiveness. We propose a framework that categorizes biofeedback into three phases: physiological data collection, processing, and feedback delivery. Our analysis of 30 empirical studies reveals that biofeedback can improve team processes by promoting balanced communication, enhancing awareness of team dynamics, and facilitating collaboration. Additionally, biofeedback fosters emergent team states such as connectedness, empathy, and social presence, supporting team cohesion. While evidence indicates that biofeedback enhances dyadic team performance, its impact on larger teams remains limited to subjective performance evaluations. The review identifies key research gaps, including limited study of autonomic nervous system activity, insufficient team-level data processing methods, and a narrow focus on visual feedback. We outline practical considerations for designing biofeedback systems that enhance team effectiveness across contexts. Future research should refine biofeedback designs, extend applications beyond the lab, and incorporate interdisciplinary insights to strengthen theoretical models. This review lays the groundwork for advancing team biofeedback research and practice. • Reviews 30 studies on biofeedback applications in team settings • Presents framework for data collection, processing, and feedback delivery • Shows biofeedback enhances team communication, coordination, and collaboration • Biofeedback improves team states like connectedness, empathy, and social presence • Finds biofeedback improves dyad performance and subjective outcomes in larger teams
Authors
- Elwira A. Hałgas (ORCID: https://orcid.org/0000-0002-7301-9576)
- Travis J. Wiltshire (ORCID: https://orcid.org/0000-0001-7630-2695)
- Kyana Hyun Joo van Eijndhoven (ORCID: https://orcid.org/0000-0001-5639-0827)
- Jingwen Yang (ORCID: https://orcid.org/0000-0002-6050-656X)
- Josette Gevers (ORCID: https://orcid.org/0000-0003-3881-5793)
Institutions
- Artificial Intelligence in Medicine (Canada) (CA)
- Eindhoven University of Technology (NL)
Publication Details
- Journal
- Computers in Human Behavior Reports
- Published
- 2025-10-17
- DOI
- https://doi.org/10.1016/j.chbr.2025.100831
- Primary Topic
- Team Dynamics and Performance
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- European Commission