Biofeedback Videogames for Anxiety Regulation

Project Lead Category Project status
Joanneke Weerdmeester Anxiety Writing Dissertation

This project explores the potential of using biofeedback video games for anxiety regulation. Specifically, the projects aims to 1) develop and assessing the efficacy of the biofeedback game DEEP, a breath-based biofeedback video game, as an anxiety regulation tool and 2) identify possible determinants of change in biofeedback interventions for anxiety regulation.

Project team


Biofeedback is the process of measuring an individual’s physiological states and feeding information about these changes back to them so that they can learn how to regulate their physiological activity to improve their wellbeing (Gilbert & Moss, 2003). In biofeedback training, participants are given insight into changes in their physiology such as heart rate, breathing or even brain activity by showing them visualisations (e.g., moving graphs of changes in heart rate) of these changes (Gilbert & Moss, 2003; Schwartz & Andrasik, 2017). These visualisations contribute to participants’ awareness of internal body signals, also known as interoceptive awareness, which is an important part of effective emotion regulation (Gross, 2002; Kever et al., 2015). In addition operant learning principles such as conditioning and reinforcement are used to teach participants how to effectively regulate their physiology. For example, a pleasant tone can indicate when someone’s physiology has reached an optimal level of activity (Gilbert & Moss, 2003; Hammond, 2005, 2007; Lehrer et al., 2000; Peper et al., 2009; Schwartz & Andrasik, 2017). 

While biofeedback has been shown to be effective as a treatment for anxiety (Goessl et al., 2017; Hammond, 2005; Richardson & Rothstein, 2008; Schoenberg & David, 2014; Schwartz & Andrasik, 2017; Tolin et al., 2020; Yucha & Montgomery, 2008) there are some practical issues that prevented a wide adaptation including specific hardware requirements and high costs. Furthermore, biofeedback training involves many trials which requires a huge time commitment and the trials are fairly repetitive making it difficult for participants to stay motivated, in particular when it comes to young participants (e.g. (Dedeepya et al., 2014; A. Parnandi & Gutierrez-Osuna, 2017). Another drawback of biofeedback training is that there is little understanding of the mechanisms of change; the majority of studies testing the effectiveness of biofeedback interventions focus mainly on outcome measures, such as symptom reductions (Weerdmeester, Van Rooij, Engels, & Granic, 2020; Wheat & Larkin, 2010). However, in order for treatments to be strengthened and tailored, it is crucial to know what factors contribute to successful change (and which ones do not) (Kazdin, 2014).The current project aimed to adress some of these barriers by exploring the potential of using biofeedback video games for anxiety regulation and to to identify possible mechanisms of change in biofeedback interventions for anxiety regulation. 

Our research 
In the past four years, most of our research has focused on assessing the potential of DEEP, a biofeedback-based virtual reality (VR) game. In this game, players move through an enchanting underwater world by using their own breath. This game was created by Owen Harris and Niki Smit (Monobanda PLAY) to provide players with a sanctuary where they can de-stress. Within this project, the game is currently being further developed and validated as a possible intervention for children with anxiety. DEEP stimulates players (through biofeedback) to use deep, diaphragmatic breathing. It is played by using a VR headset combined with a customized belt that measures the expansion of the diaphragm. The values of this sensor influence the game and are reflected in feedback in various ways. First of all, the player is informed about their breathing by way of their movement. Breathing in deeply gives the players an upward (when close to the ground) or forward force, and these forces are strengthened by deeply breathing out. The player is also given various forms of visual feedback. For example, a circle in the center of the screen shrinks and expands in accordance to the expansion of the player's diaphragm. In addition, elements in the environment (such as plants) change color or change in size/movement, mirroring the player's breathing. By giving this (bio)feedback to the player, they can become more aware of their breathing and are stimulated to breath in a deep and calm manner. 

So far we have conducted multiple studies including pilot studies, an implementation trial in special eduction, and most recently a Randomized Controlled Trial to assess whether DEEP could help alleviate anxiety. In addition we wrote an extensive review regarding biofeedback interventions for anxiety regulation. In this review we identified several psychological mechanisms of change that may be tied to adaptive outcomes of biofeedback interventions and we included a set of guidelines to for a new phase of biofeedback therapy, inspired by game design and the potential of wearable biosensors.


Project team

Joanneke Weerdmeester title=
Joanneke Weerdmeester

Researcher, psychologist, PhD-candidate, gamer, dungeon master, language enthusiast and lover of all things geeky.




E-mail Joanneke

Isabela Granic title=
Isabela Granic

Professor and Chair of the Developmental Psychopathology department in the Behavioural Science Institute; writer; voracious podcast consumer; mother of two upstanding little gamers


Director of GEMH Lab


E-mail Isabela

Rutger Engels title=
Rutger Engels


CEO at Trimbos Institute / Professor Developmental Psychopathology Utrecht University


E-mail Rutger

Marieke van Rooij title=
Marieke van Rooij

Assistant prof. and data geek at the GEMH lab, dynamical modelling, personalisation, wants to put the I back into AI, news junkie, cat lover.


Assistant Professor


E-mail Marieke

Tom Hollenstein title=
Tom Hollenstein

Associate Professor in Developmental Psychology at Queen's University in Kingston, Ontario, Canada.


Associate Professor - Collaborator


E-mail Tom


All sources

Dedeepya, P., Nuvvula, S., Kamatham, R., & Nirmala, S. V. (2014). Behavioural and physiological outcomes of biofeedback therapy on dental anxiety of children undergoing restorations: a randomised controlled trial. Eur Arch Paediatr Dent, 15(2), 97-103.

Gilbert, C. & Moss, D (2003). Biofeedback and biological monitoring. Handbook of mind-body medicine in primary care: Behavioral and physiological tools, 109-122.

Goessl, V. C., Curtiss, J. E., & Hofmann, S. G. (2017). The effect of heart rate variability biofeedback training on stress and anxiety: a meta-analysis. Psychol Med, 47(15), 2578-2586.

Gross, J. J. (2002). Emotion regulation: Affective, cognitive, and social consequences. Psychophysiology, 39(3), 281-291.

Hammond, D. C. (2005). Neurofeedback treatment of depression and anxiety. J Adult Dev, 12(2-3), 131-137.

Hammond, D. C. (2007). What is neurofeedback? J Neurother, 10(4), 25-36.

Kazdin, A. E. (2014). Moderators, mediators and mechanisms of change in psychotherapy. In W. Lutz & S. Knox (Eds.), Explorations in mental health. Quantitative and qualitative methods in psychotherapy research (pp. 87-101). Routledge/Taylor & Francis Group.

Kever, A., Pollatos, O., Vermeulen, N., & Grynberg, D. (2015). Interoceptive sensitivity facilitates both antecedent-and response-focused emotion regulation strategies. Pers Individ Dif, 87, 20-23.

Lehrer, P. M., Vaschillo, E., & Vaschillo, B. (2000). Resonant frequency biofeedback training to increase cardiac variability: Rationale and manual for training. Appl Psychophysiol Biofeedback, 25(3), 177-191.

Parnandi, A., & Gutierrez-Osuna, R. (2017). Physiological modalities for relaxation skill transfer in biofeedback games. IEEE J Biomed Health Inform, 21(2), 361-371.

Richardson, K. M., & Rothstein, H. R. (2008). Effects of occupational stress management intervention programs: a meta-analysis. Journal of occupational health psychology, 13(1), 69-93.

Schoenberg, P. L., & David, A. S. (2014). Biofeedback for psychiatric disorders: a systematic review. Applied psychophysiology and biofeedback, 39(2), 109-135.

Schwartz, M. S., & Andrasik, F. (2017). Biofeedback: A practitioner's guide (M. S. Schwartz & F. Andrasik, Eds. 4th. ed. ed.). Guilford Publications.

Tolin, D. F., Davies, C. D., Moskow, D. M., & Hofmann, S. G. (2020). Biofeedback and neurofeedback for anxiety disorders: a quantitative and qualitative systematic review. In Y.-K. Kim (Ed.), Anxiety disorders. Rethinking and understanding recent discoveries. (pp. 265-291). Springer Nature Singapore, Pte Ltd. .

Wheat, A. L., & Larkin, K. T. (2010). Biofeedback of heart rate variability and related physiology: A critical review. Applied psychophysiology and biofeedback, 35(3), 229-242.

Yucha, C., & Montgomery, D. (2008). Evidence-based practice in biofeedback and neurofeedback. Wheat Ridge, CO: AAPB.

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