Biofeedback-based connected mental health interventions for anxiety: Systematic literature review

Mahra Alneyadi, Nidal Drissi, Mariam Almeqbaali, Sofia Ouhbi

Research output: Contribution to journalReview articlepeer-review

17 Citations (Scopus)


Background: Connected mental health, which refers to the use of technology for mental health care and technology-based therapeutic solutions, has become an established field of research. Biofeedback is one of the approaches used in connected mental health solutions, which is mainly based on the analysis of physiological indicators for the assessment and management of the psychological state. Biofeedback is recommended by many therapists and has been used for conditions including depression, insomnia, and anxiety. Anxiety is associated with several physiological symptoms, including muscle tension and breathing issues, which makes the inclusion of biofeedback useful for anxiety detection and management. Objective: The aim of this study was to identify interventions using biofeedback as a part of their process for anxiety management and investigate their perceived effectiveness. Methods: A systematic literature review of publications presenting empirically evaluated biofeedback-based interventions for anxiety was conducted. The systematic literature review was based on publications retrieved from IEEE Digital Library, PubMed, ScienceDirect, and Scopus. A preliminary selection of papers was identified, examined, and filtered to include only relevant publications. Studies in the final selection were classified and analyzed to extract the modalities of use of biofeedback in the identified interventions, the types of physiological data that were collected and analyzed and the sensors used to collect them. Processes and outcomes of the empirical evaluations were also extracted. Results: After final selection, 13 publications presenting different interventions were investigated. The interventions addressed either primarily anxiety disorders or anxiety associated with health issues such as migraine, Parkinson disease, and rheumatology. Solutions combined biofeedback with other techniques including virtual reality, music therapy, games, and relaxation practices and used different sensors including cardiovascular belts, wrist sensors, or stretch sensors to collect physiological data such as heart rate, respiration indicators, and movement information. The interventions targeted different cohorts including children, students, and patients. Overall, outcomes from the empirical evaluations yielded positive results and emphasized the effectiveness of connected mental health solutions using biofeedback for anxiety; however, certain unfavorable outcomes, such as interventions not having an effect on anxiety and patients' preferring traditional therapy, were reported in studies addressing patients with specific physical health issues. Conclusions: The use of biofeedback in connected mental health interventions for the treatment and management of anxiety allows better screening and understanding of both psychological and physiological patient information, as well as of the association between the two. The inclusion of biofeedback could improve the outcome of interventions and boost their effectiveness; however, when used with patients suffering from certain physical health issues, suitability investigations are needed.

Original languageEnglish
Article numbere26038
JournalJMIR mHealth and uHealth
Issue number4
Publication statusPublished - Apr 1 2021


  • Anxiety
  • Biofeedback
  • Connected health
  • Digital health
  • EHealth
  • MHealth
  • Mental health
  • Systematic literature review

ASJC Scopus subject areas

  • Health Informatics


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