Connected mental health (CMH), referring to the use of technology for mental health care, has become an established field of research. CMH provides access to many technology-based therapeutic solutions for mental health. Biofeedback is one of the approaches used in CMH solutions, which is mainly based on the analysis of physiological indicators for the assessment and management of the psychological state. Biofeedback is an approach recommended by many therapists, and was used for psychological issues’ management including depression, insomnia and anxiety. Anxiety is a common mental issue associated with several physiological symptoms, including muscle tension and breathing issues, which makes the inclusion of biofeedback in CMH interventions a useful approach for anxiety detection and management.
The aim of this study is to investigate the use of biofeedback approaches in CMH interventions addressing anxiety, by identifying interventions using biofeedback as a part of their process for anxiety management, and investigating their perceived effectiveness.
A systematic literature review (SLR) of publications presenting empirically evaluated biofeedback-based interventions for anxiety was conducted. The SLR was based on publications retrieved from the sources: IEEE Digital Library, PubMed, ScienceDirect, and Scopus. A preliminary selection of papers was identified, which was examined and filtered to include only relevant publications. Studies in the final selection were classified and analyzed to extract data on the modalities of use of biofeedback, the types of collected and analyzed physiological data and the sensors used to collect them. In addition to extracting the processes and outcomes of the conducted empirical evaluations.
Thirteen publications presenting different interventions were investigated. The interventions addressed either primarily anxiety disorders or anxiety associated with other health issues like migraine, Parkinson’s disease, and rheumatology. The identified solutions combined biofeedback with different techniques including virtual reality, music therapy, games, and relaxation practices, and used sensors like cardiovascular belts, wrist sensors and resistor/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 CMH solutions for anxiety using biofeedback. However, certain unfavorable outcomes were reported in studies addressing patients with specific physical health issues. Those outcomes included the interventions not having an effect on anxiety and the patients’ preference of traditional therapy.
Use of biofeedback in CMH interventions for the treatment and management of anxiety, allows a better screening and understanding of both psychological and physiological state of the patients, as well as the association between the two. Inclusion of biofeedback could improve the outcome of the interventions and boost their effectiveness. However, when used with patients suffering from certain physical health issues, suitability investigations are needed.


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