Breathing Biofeedback for Police Officers in a Stressful Virtual Environment: Challenges and Opportunities
Open accessAbstract
As part of the Dutch national science program “Professional Games for Professional Skills” we developed a stress-exposure biofeedback training in virtual reality (VR) for the Dutch police. We aim to reduce the acute negative impact of stress on performance, as well as long-term consequences for mental health by facilitating physiological stress regulation during a demanding decision task. Conventional biofeedback applications mainly train physiological regulation at rest. This might limit the transfer of the regulation skills to stressful situations. In contrast, we provide the user with the opportunity to practice breathing regulation while they carry out a complex task in VR. This setting poses challenges from a technical – (real-time processing of noisy biosignals) as well as from a user-experience perspective (multi-tasking). We illustrate how we approach these challenges in our training and hope to contribute a useful reference for researchers and developers in academia or industry who are interested in using biosignals to control elements in a dynamic virtual environment.
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VR and BF successfully enhanced breathing training.
“Furthermore, VR and BF successfully enhanced breathing training (Brammer et al., 2021;Rockstroh et al., 2021).”
From Frontal Electroencephalography Asymmetry and Desynchronized Functional Connectivity Associated with Long-Term and Short-Term Breathing Training (2026) · cites this paper as Brammer et al., 2021
In ‘Challenge 1: Choice of the Biofeedback Parameter > Prioritizing Controllability’ (page unavailable), the pilot data show lower breathing rates and higher biofeedback scores in sessions with biofeedback, as well as improvement across sessions. This supports a benefit from biofeedback in the VR training, but the paper describes the findings as suggestive and does not isolate whether VR itself enhanced breathing training. (LLM, conf=0.87)
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Cites
Matplotlib: a 2D graphics environment
Hunter, J. D. (2007) · Computing in Science & Engineering · doi:10.1109/mcse.2007.55 · Cited by 39,249 · see citing works
SciPy 1.0: fundamental algorithms for scientific computing in Python
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., et al. (2020) · Nature Methods · doi:10.1038/s41592-019-0686-2 · Cited by 38,430 · see citing works
SciPy 1.0: fundamental algorithms for scientific computing in Python
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., et al. (2019) · Apollo - University of Cambridge Repository · doi:10.17863/cam.64134 · Cited by 10,460 · see citing works
The NumPy Array: A Structure for Efficient Numerical Computation
van der Walt, S., Colbert, S. C., & Varoquaux, G. P. (2011) · Computing in Science & Engineering · doi:10.1109/mcse.2011.37 · Cited by 10,445 · see citing works
Multiple resources and performance prediction
Wickens, C. D. (2002) · Theoretical Issues in Ergonomics Science · doi:10.1080/14639220210123806 · Cited by 2,621 · cited 1× · see citing works
“The player has to allocate cognitive resources to both the decision task as well as the physiological regulation, which can worsen performance on both tasks (Wickens, 2002).”
BackgroundMoving beyond P values: data analysis with estimation graphics
Ho, J., Tumkaya, T., Aryal, S., Choi, H., & Claridge‐Chang, A. (2019) · Nature Methods · doi:10.1038/s41592-019-0470-3 · Cited by 1,770 · see citing works
Waskom, M., Botvinnik, O. B., O'Kane, D., Hobson, P., Ostblom, J., Lukauskas, S., Gemperline, D. C., Augspurger, T., Halchenko, Y., Cole, J. B., et al. (2014) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.592845 · Cited by 1,119 · see citing works
The physiological effects of slow breathing in the healthy human
Russo, M. A., Santarelli, D. M., & O’Rourke, D. (2017) · Breathe · doi:10.1183/20734735.009817 · Cited by 665 · see citing works
Price, C. J., & Hooven, C. (2018) · Frontiers in Psychology · doi:10.3389/fpsyg.2018.00798 · Cited by 519 · see citing works
The influence of task demand and learning on the psychophysiological response
Fairclough, S. H., Venables, L., & Tattersall, A. J. (2005) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2004.11.003 · Cited by 292 · see citing works
Nacke, L. E., Kalyn, M. R., Lough, C., & Mandryk, R. L. (2011) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/1978942.1978958 · Cited by 256 · see citing works
The experience of agency in human-computer interactions: a review
Limerick, H., Coyle, D., & Moore, J. W. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00643 · Cited by 241 · see citing works
Routine Work Environment Stress and PTSD Symptoms in Police Officers
Maguen, S., Metzler, T. J., McCaslin, S. E., Inslicht, S. S., Henn‐Haase, C., Neylan, T. C., & Marmar, C. R. (2009) · The Journal of Nervous and Mental Disease · doi:10.1097/nmd.0b013e3181b975f8 · Cited by 212 · see citing works
Respiratory Frequency during Exercise: The Neglected Physiological Measure
Nicolò, A., Massaroni, C., & Passfield, L. (2017) · Frontiers in Physiology · doi:10.3389/fphys.2017.00922 · Cited by 208 · see citing works
Effects of anxiety on handgun shooting behavior of police officers: a pilot study
Nieuwenhuys, A., & Oudejans, R. R. D. (2009) · Anxiety Stress & Coping · doi:10.1080/10615800902977494 · Cited by 187 · see citing works
Biofeedback for Everyday Stress Management: A Systematic Review
Yu, B., Funk, M., Hu, J., Wang, Q., & Feijs, L. M. G. (2018) · Frontiers in ICT · doi:10.3389/fict.2018.00023 · Cited by 185 · see citing works
Virtual Reality Applications for Stress Management Training in the Military
Pallavicini, F., Argenton, L., Toniazzi, N., Aceti, L., & Mantovani, F. (2016) · Aerospace Medicine and Human Performance · doi:10.3357/amhp.4596.2016 · Cited by 182 · see citing works
Complex Motor Learning and Police Training: Applied, Cognitive, and Clinical Perspectives
Nota, P. M. D., & Huhta, J. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.01797 · Cited by 167 · see citing works
van Rooij, M. M. J. W., Lobel, A., Harris, O., Smit, N., & Granic, I. (2016) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/2851581.2892452 · Cited by 160 · see citing works
Self-citationDriskell, J. E., & Johnston, J. H. (1998) · American Psychological Association eBooks · doi:10.1037/10278-007 · Cited by 151 · see citing works
A Training Method to Improve Police Use of Force Decision Making
Andersen, J. P., & Gustafsberg, H. (2016) · SAGE Open · doi:10.1177/2158244016638708 · Cited by 148 · see citing works
Bouchard, S., Bernier, F., Boivin, É., Morin, B., & Robillard, G. (2012) · PLoS ONE · doi:10.1371/journal.pone.0036169 · Cited by 140 · see citing works
Scholten, H., & Granic, I. (2019) · Journal of Medical Internet Research · doi:10.2196/11528 · Cited by 138 · see citing works
Self-citationVirtual reality in the application of heart rate variability biofeedback
Rockstroh, C., Blum, J., & Göritz, A. S. (2019) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2019.06.011 · Cited by 128 · see citing works
System Latency Guidelines Then and Now – Is Zero Latency Really Considered Necessary?
Attig, C., Rauh, N., Franke, T., & Krems, J. F. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-58475-1_1 · Cited by 101 · see citing works
Does Stress Training Generalize to Novel Settings?
Driskell, J. E., Johnston, J. H., & Eduardo Salas, A. (2001) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1518/001872001775992471 · Cited by 99 · see citing works
Reducing noise by repetition: introduction to signal averaging
Hassan, U., & Anwar, M. S. (2010) · European Journal of Physics · doi:10.1088/0143-0807/31/3/003 · Cited by 93 · see citing works
Tolin, D. F., Davies, C. D., Moskow, D. M., & Hofmann, S. G. (2020) · Advances in experimental medicine and biology · doi:10.1007/978-981-32-9705-0_16 · Cited by 90 · see citing works
Weerdmeester, J., van Rooij, M. M. J. W., Engels, R. C. M. E., & Granic, I. (2020) · Journal of Medical Internet Research · doi:10.2196/14958 · Cited by 88 · see citing works
Self-citationNieuwenhuys, A., Caljouw, S. R., Leijsen, M. R., Schmeits, B. A. J., & Oudejans, R. R. D. (2009) · Ergonomics · doi:10.1080/00140130903287981 · Cited by 65 · see citing works
Jerčić, P., & Sundstedt, V. (2019) · Entertainment Computing · doi:10.1016/j.entcom.2019.01.001 · Cited by 58 · see citing works
Respiration and Heart Rate Modulation Due to Competing Cognitive Tasks While Driving
Hidalgo-Muñoz, A. R., Béquet, A. J., Astier-Juvenon, M., Pépin, G., Fort, A., Jallais, C., Tattegrain, H., & Gabaude, C. (2019) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2018.00525 · Cited by 44 · see citing works
'Spectrum': Spectral Analysis in Python
Cokelaer, T., & Hasch, J. (2017) · The Journal of Open Source Software · doi:10.21105/joss.00348 · Cited by 40 · see citing works
Visual Biofeedback and Game Adaptation in Relaxation Skill Transfer
Parnandi, A., & Gutiérrez‐Osuna, R. (2017) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2017.2705088 · Cited by 33 · see citing works
Effects of Mental Strength Training for Police Officers: a Three-Wave Quasi-experimental Study
van der Meulen, E., Bosmans, M. W. G., Lens, K. M. E., Lahlah, E., & van der Velden, P. G. (2017) · Journal of Police and Criminal Psychology · doi:10.1007/s11896-017-9247-8 · Cited by 30 · see citing works
Attention, Comprehension, Execution
Sun, Z., Cao, N., & Ma, X. (2017) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3027063.3053082 · Cited by 10 · see citing works
Michela, A., van Rooij, M. M. J. W., Klumpers, F., van Peer, J. M., Karin Roelofs, A., & Granic, I. (2019) · Psychological Inquiry · doi:10.1080/1047840x.2019.1693872 · Cited by 8 · see citing works
Self-citation
Flagged first, then by citations
1 of the 38 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Approach-Avoidance Decisions Under Threat: The Role of Autonomic Psychophysiological States
Livermore, J. J. A., Klaassen, F. H., Bramson, B., Hulsman, A. M., Meijer, S. W., Held, L. K., Klumpers, F., de Voogd, L. D., & Roelofs, K. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.621517 · Cited by 101 · see citing works
Self-citationImmersive Innovations: Exploring the Diverse Applications of Virtual Reality (VR) in Healthcare
Javvaji, C. K., Reddy, H., Vagha, J. D., Taksande, A. M., Kommareddy, A., & Reddy, N. S. (2024) · Cureus · doi:10.7759/cureus.56137 · Cited by 62 · see citing works
Defensive freezing and its relation to approach–avoidance decision-making under threat
Klaassen, F. H., Held, L. K., Figner, B., O’Reilly, J. X., Klumpers, F., de Voogd, L. D., & Karin Roelofs, A. (2021) · Scientific Reports · doi:10.1038/s41598-021-90968-z · Cited by 49 · see citing works
Self-citationMichela, A., van Peer, J. M., Brammer, J. C., Nies, A., van Rooij, M. M. J. W., Oostenveld, R., Dorrestijn, W., Smit, A. S., Karin Roelofs, A., Klumpers, F., et al. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.806163 · Cited by 37 · see citing works
Self-citationVirtual Reality for Pulmonary Rehabilitation: Comprehensive Review
Pittara, M., Matsangidou, M., & Pattichis, C. S. (2023) · JMIR Rehabilitation and Assistive Technologies · doi:10.2196/47114 · Cited by 35 · see citing works
Muñoz, J. E., Lavoie, J. A. A., & Pope, A. (2024) · Frontiers in Psychology · doi:10.3389/fpsyg.2024.1390677 · Cited by 26 · see citing works
Effects of Acute Stress on Psychophysiology in Armed Tactical Occupations: A Narrative Review
Stephenson, M. D., Schram, B. L., Canetti, E. F. D., & Orr, R. M. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19031802 · Cited by 22 · see citing works
Stress Out: Translating Real-World Stressors into Audio-Visual Stress Cues in VR for Police Training
Nguyen, Q., Jaspaert, E., Murtinger, M., Schrom-Feiertag, H., Egger-Lampl, S., & Tscheligi, M. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-85616-8_32 · Cited by 18 · see citing works
Getting stress-related disorders under control: the untapped potential of neurofeedback
Krause, F., Linden, D. E. J., & Hermans, E. J. (2024) · Trends in Neurosciences · doi:10.1016/j.tins.2024.08.007 · Cited by 16 · see citing works
Evaluating the Role of Breathing Guidance on Game-Based Interventions for Relaxation Training
Gummidela, V. N. C., Silva, D. R. D. C., & Gutiérrez‐Osuna, R. (2021) · Frontiers in Digital Health · doi:10.3389/fdgth.2021.760268 · Cited by 16 · see citing works
Choi, S., Michalski, N. D., & Snyder, J. A. (2022) · Criminal Justice Review · doi:10.1177/07340168221093549 · Cited by 11 · see citing works
Podoletz, L., McGill, M., McIlhatton, D., Marshall, J., Healy, N., & Tanczer, L. M. (2024) · ACM Symposium on Virtual Reality Software and Technology (VRST) · doi:10.1145/3641825.3687707 · Cited by 14 · see citing works
Immersive VR for investigating threat avoidance: The VRthreat toolkit for Unity
Brookes, J., Hall, S., Frühholz, S., & Bach, D. R. (2023) · Behavior Research Methods · doi:10.3758/s13428-023-02241-y · Cited by 9 · see citing works
Kleygrewe, L., Hutter, V., Koedijk, M., & Oudejans, R. R. D. (2023) · Ergonomics · doi:10.1080/00140139.2023.2236819 · Cited by 9 · see citing works
Ng, H. H., Wu, C. W., Hsu, H., Huang, C., Hsu, A., Chao, Y., Jung, T., & Chuang, C. (2024) · JMIR Formative Research · doi:10.2196/55478 · Cited by 9 · see citing works
Burr, L. A., Betzlbacher, N., Meschtscherjakov, A., & Tscheligi, M. (2022) · Lecture notes in computer science · doi:10.1007/978-3-030-98438-0_5 · Cited by 8 · see citing works
How Officers Perform and Grow under Stress: Police Training in Virtual Reality
Voigt, L., & Frenkel, M. O. (2023) · Springer eBooks · doi:10.1007/978-3-031-41100-7_9 · Cited by 7 · see citing works
Saúde mental na Segurança Pública frente à pandemia: uma revisão narrativa
Guimarães, L. A. M., Massuda, J., & de Oliveira, F. F. (2023) · Revista Brasileira de Ciências Policiais · doi:10.31412/rbcp.v14i12.1025 · Cited by 5 · see citing works
Michela, A., van Peer, J. M., Brammer, J. C., Nies, A., van Rooij, M. M. J. W., Oostenveld, R., Dorrestijn, W., Smit, A. S., Karin Roelofs, A., Klumpers, F., et al. (2021) · doi:10.31234/osf.io/3qnvk · Cited by 5 · see citing works
Self-citationThe relationship between spirituality and mental health among police trainees
He, M., Lu, J., Chen, J. H., & Tong, K. K. (2023) · Policing An International Journal · doi:10.1108/pijpsm-09-2022-0125 · Cited by 5 · see citing works
Does Gamified Breath-Biofeedback Promote Adherence, Relaxation, and Skill Transfer in the Wild?
Silva, D. R. D. C., & Gutiérrez‐Osuna, R. (2024) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2024.3428390 · Cited by 3 · see citing works
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Spears, J., Romero, D. E., McVay, K. E., & Surrat, E. (2024) · NeuroRegulation · doi:10.15540/nr.11.1.81 · Cited by 4 · see citing works
Norton-Gardner, I., & Tramel, W. (2025) · Springer eBooks · doi:10.1007/978-3-031-87305-8_11 · Cited by 2 · see citing works
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Finseth, T. (2021) · doi:10.31274/td-20240329-40 · Cited by 3 · see citing works
Vihonen, H., Karvonen, J., Gustafsberg, H., Huhta, J., Kangasniemi, H., Jama, T., & Hoppu, S. (2025) · BMC Emergency Medicine · doi:10.1186/s12873-025-01235-7 · Cited by 1 · see citing works
Volpato, E., & Poletti, V. (2024) · Springer eBooks · doi:10.1007/978-3-031-32046-0_174-1 · Cited by 1 · see citing works
Sung, P.-C. (2022) · International Journal of Applied Science and Engineering · doi:10.6703/ijase.202212_19(4).010 · Cited by 1 · see citing works
Systematic Literature Review Terhadap Interpersonal Skill Technology Developer
Fitroh, Amri, F. B., & Arizky, F. M. (2023) · SATIN - Sains dan Teknologi Informasi · doi:10.33372/ja1v5z80 · Cited by 1 · see citing works
Pinc, T. (2023) · Research Square · doi:10.21203/rs.3.rs-3060003/v1 · Cited by 1 · see citing works
Kleygrewe, L. (2023) · doi:10.5463/thesis.312 · Cited by 1 · see citing works
Ng, H.-Y. H., Hsu, A.-L., Wu, C. W., Huang, C.-M., Chao, Y.-P., Jung, T.-P., & Chuang, C.-H. (2026) · Mindfulness · doi:10.1007/s12671-025-02734-1
“Furthermore, VR and BF successfully enhanced breathing training (Brammer et al., 2021; Rockstroh et al., 2021).”
Definition, Scope, and Applications of Physiotherapy Biofeedback: Systematic Reviews
Oh, J.-S., Lee, K.-J., & Kim, S.-G. (2023) · Journal of the Korean Society of Physical Medicine · doi:10.13066/kspm.2023.18.4.109
Health Problems of Police Officers in Brazil That Arise in The Performance of Their Work
(2023) · International journal of criminology and criminal law. · doi:10.33140/ijccl.01.01.04
Volpato, E., & Poletti, V. (2025) · Springer eBooks · doi:10.1007/978-3-031-73363-5_174
EmoLoop: An adaptive VR biofeedback system for stress regulation
Lima, R., Chirico, A., Gaggioli, A., Gamboa, H. F. S., & Badia, S. B. I. (2026) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2026.103916
Electrodermal signatures of stress during tactical law enforcement training
Bigliassi, M., Curtis, J., Yasutake, V. V., Acosta, K., Bagherian, D., Laing, R., & Balban, M. Y. (2026) · Stress · doi:10.1080/10253890.2026.2723354
Adaptive exposure therapy for Social Anxiety Disorder: a preliminary validation in virtual reality
Frumento, S., Paparo, N., Briglia, M., Martini, M., Chessa, M., Greco, A., & Menicucci, D. (2026) · European Conference on Cognitive Ergonomics · doi:10.1145/3822301.3822334
Cerazy, D., & Kraszewski, S. (2026) · doi:10.2196/preprints.115272
- Authors
- Brammer, J. C., van Peer, J. M., Michela, A., van Rooij, M. M. J. W., Oostenveld, R., Klumpers, F., Dorrestijn, W., Granic, I., & Roelofs, K.
- Affiliations
- Radboud University Nijmegen (NL)
- Corresponding author
- Brammer, Jan C.
- Venue
- Frontiers in Psychology
- Publisher
- Frontiers Media SA
- Published
- 2021-03-12
- Volume
- 12
- Pages
- 586553-586553
- ISSN
- 1664-1078 (ISSN-L)
- PMC
- PMC7994769
- OpenAlex
- W3136023411
- Cited by
- 38
- References
- 38
- Citations by year
- 2026: 5 · 2025: 3 · 2024: 8 · 2023: 11 · 2022: 5 · 2021: 6
- FWCI
- 4.60
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Psychology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Radboud Repository (Radboud University) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Radboud Repository (Radboud University) (submittedVersion, other-oa)
- Funders
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek
- Topics
- Physical Sciences › Computer Science › Human-Computer Interaction › Virtual Reality Applications and Impacts
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Keywords
- biofeedback, respiratory control, police officers, occupational stress, virtual reality training, biomedical signal processing, multitasking, mental health, decision-making under stress
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