Biofeedback therapeutic effects on blood pressure levels in hypertensive individuals: A systematic review and meta-analysis

Vital, José Edimosio Costa; Nunes, Adriele de Morais; York, Beatriz Souza de Albuquerque Cacique New; Sousa, Barbara Dayane Araujo de; Nascimento, Micaele Farias; Formiga, Magno F.; Fernandes, Ana Tereza N.S.F.

doi:10.1016/j.ctcp.2021.101420

Cited by 11 publications

(7 citation statements)

References 24 publications

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“…Cardiovascular biofeedback: detects heart rate (HR) and its variability (HRV), respiratory sinus arrhythmia (RSA), and blood flow volume (blood volume pulse, BVP) and is used in the treatment of asthma, chronic obstructive pulmonary disease (COPD) coronary artery disease, depression, fibromyalgia/chronic fatigue syndrome, post-traumatic stress disorder (PTSD), anxiety, chronic pain, and hypertension ( Rosaura Polak et al, 2015 ; Thabrew et al, 2018 ; Fahrenkamp and Benore, 2019 ; Taghizadeh et al, 2019 ; Reneau, 2020 ; da Costa Maynart et al, 2021 ; Vital et al, 2021 ).…”

Section: Biofeedbackmentioning

confidence: 99%

“…-Respiratory biofeedback: measures respiratory rate and pattern, as well as blood carbon dioxide levels, and is used in the treatment of asthma, chronic obstructive pulmonary disease (COPD), anxiety, and hypertension (Landman et al, 2013;Aritzeta et al, 2017;Georga et al, 2019;Kaja et al, 2020). -Cardiovascular biofeedback: detects heart rate (HR) and its variability (HRV), respiratory sinus arrhythmia (RSA), and blood flow volume (blood volume pulse, BVP) and is used in the treatment of asthma, chronic obstructive pulmonary disease (COPD) coronary artery disease, depression, fibromyalgia/ chronic fatigue syndrome, post-traumatic stress disorder (PTSD), anxiety, chronic pain, and hypertension (Rosaura Polak et al, 10.3389/fnins.2024.1358481 Frontiers in Neuroscience 03 frontiersin.org 2015;Thabrew et al, 2018;Fahrenkamp and Benore, 2019;Taghizadeh et al, 2019;Reneau, 2020;da Costa Maynart et al, 2021;Vital et al, 2021). -Neuromuscular biofeedback: provides a measure of muscle tension with surface electromyography (sEMG) and is used to treat fibromyalgia/chronic fatigue syndrome, repetitive strain injury, tinnitus, arthritis, diabetes, pediatric migraine, anxiety, chronic pain, temporomandibular junction disorders, and adult tension headache (Blume et al, 2012;Šečić et al, 2016;Baumueller et al, 2017;Lazaridou et al, 2023).…”

Section: Biofeedbackmentioning

confidence: 99%

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Integrated use of biofeedback and neurofeedback techniques in treating pathological conditions and improving performance: a narrative review

Tosti,

Corrado,

Mancone

et al. 2024

Front. Neurosci.

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In recent years, the scientific community has begun tо explore the efficacy оf an integrated neurofeedback + biofeedback approach іn various conditions, both pathological and non-pathological. Although several studies have contributed valuable insights into its potential benefits, this review aims tо further investigate its effectiveness by synthesizing current findings and identifying areas for future research. Our goal іs tо provide a comprehensive overview that may highlight gaps іn the existing literature and propose directions for subsequent studies. The search for articles was conducted on the digital databases PubMed, Scopus, and Web of Science. Studies to have used the integrated neurofeedback + biofeedback approach published between 2014 and 2023 and reviews to have analyzed the efficacy of neurofeedback and biofeedback, separately, related to the same time interval and topics were selected. The search identified five studies compatible with the objectives of the review, related to several conditions: nicotine addiction, sports performance, Autism Spectrum Disorder (ASD), and Attention Deficit Hyperactivity Disorder (ADHD). The integrated neurofeedback + biofeedback approach has been shown to be effective in improving several aspects of these conditions, such as a reduction in the presence of psychiatric symptoms, anxiety, depression, and withdrawal symptoms and an increase in self-esteem in smokers; improvements in communication, imitation, social/cognitive awareness, and social behavior in ASD subjects; improvements in attention, alertness, and reaction time in sports champions; and improvements in attention and inhibitory control in ADHD subjects. Further research, characterized by greater methodological rigor, is therefore needed to determine the effectiveness of this method and the superiority, if any, of this type of training over the single administration of either. This review іs intended tо serve as a catalyst for future research, signaling promising directions for the advancement оf biofeedback and neurofeedback methodologies.

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Section: Biofeedbackmentioning

confidence: 99%

Section: Biofeedbackmentioning

confidence: 99%

Integrated use of biofeedback and neurofeedback techniques in treating pathological conditions and improving performance: a narrative review

Tosti,

Corrado,

Mancone

et al. 2024

Front. Neurosci.

View full text Add to dashboard Cite

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“…Комбинированный температурно-миографический тренинг при терапии гипертонической болезни позволяет добиться снижения уровня артериального давления и снизить риск дальнейшего развития заболеваний сердечно-сосудистой системы [15,19,29].…”

Section: гипертоническая болезньunclassified

“…После анализа результатов исследований было показано, что применение методов БОСтерапии при лечении гипертонической болезни значительно улучшает контроль артериального давления (Z = 2,15; p = 0,03), в большей степени влияя на диастолическое АД, снижает уровень стресса и способно облегчить контроль над другими факторами риска сердечно-сосудистых заболеваний. Кроме того, методы БОС могут быть использованы в качестве адъювантной терапии артериальной гипертензии [29].…”

Section: гипертоническая болезньunclassified

The use of biofeedback techniques in clinical practice

Ruzinova,

Dolgopolova,

Petelin

et al. 2023

Medicinskij sovet

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In the past decades, biofeedback has become a widely adopted non-pharmacological option in the management of a variety of somatic, neurological, and psychiatric conditions. The biofeedback method is based on the associations between one’s vegetative and mental functions; during a session with the device, information about the change in his/her condition over time is “returned” to the patient as accessible audial or visual stimuli. The efficacy of biofeedback treatment may primarily be attributed to improvements in the state of the patients based on establishing an individual model of his/her best psychophysiological state, enabling effective rehabilitation activities at a rate suitable for each patient along with ensuring better awareness of the patient of his/her body functions; such an intervention is stepwise and helps sustain the patient’s motivation for success, thus affecting the pathological condition. This review describes the historical prerequisites for the development of biofeedback techniques and the principal mechanisms of their action; a brief summary of studies looking at the efficacy of this method in various somatic, neurological, and psychiatric conditions is also provided. The presented data clearly indicate that the use of biofeedback results in a decreased medication load in patients suffering from conditions such as arterial hypertension, epilepsy, ADHD, chronic pain, anxiety disorders, autism etc. while there are practically no contraindications for this method, except for acute psychosis, photosensitive epilepsy, and severe cognitive impairment. In this connection, clinical implementation of biofeedback techniques should be intensified in a variety of conditions.

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“…Approximately 40% of US adults in 2021 reported symptoms of depression and anxiety that significantly impact daily functioning and quality of life (Vahratian et al., 2021) Heart rate variability biofeedback (HRVB) is a promising, evidence‐based adjunctive intervention that can make a clinically significant contribution to treating these mental health symptoms (Alayan et al., 2018; Burlacu et al., 2021; Costa Vital et al., 2021; Fournié et al., 2021; Goessl et al., 2017; Lehrer et al., 2020; Pizzoli et al., 2021). This study enables digital HRVB with machine‐learning‐based biofeedback by validating a real‐time algorithm and by characterizing individual differences relevant to improving the equity, accuracy, and personalization of digital HRVB.…”

Section: Introductionmentioning

confidence: 99%

Real‐time heart rate variability biofeedback amplitude during a large‐scale digital mental health intervention differed by age, gender, and mental and physical health

Aschbacher,

Mather,

Lehrer

et al. 2024

Psychophysiology

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Heart rate variability biofeedback (HRVB) is an efficacious treatment for depression and anxiety. However, translation to digital mental health interventions (DMHI) requires computing and providing real‐time HRVB metrics in a personalized and user‐friendly fashion. To address these gaps, this study validates a real‐time HRVB feedback algorithm and characterizes the association of the main algorithmic summary metric—HRVB amplitude—with demographic, psychological, and health factors. We analyzed HRVB data from 5158 participants in a therapist‐supported DMHI incorporating slow‐paced breathing to treat depression or anxiety symptoms. A real‐time feedback metric of HRVB amplitude and a gold‐standard research metric of low‐frequency (LF) power were computed for each session and then averaged within‐participants over 2 weeks. We provide HRVB amplitude values, stratified by age and gender, and we characterize the multivariate associations of HRVB amplitude with demographic, psychological, and health factors. Real‐time HRVB amplitude correlated strongly (r = .93, p < .001) with the LF power around the respiratory frequency (~0.1 Hz). Age was associated with a significant decline in HRVB (β = −0.46, p < .001), which was steeper among men than women, adjusting for demographic, psychological, and health factors. Resting high‐ and low‐frequency power, body mass index, hypertension, Asian race, depression symptoms, and trauma history were significantly associated with HRVB amplitude in multivariate analyses (p's < .01). Real‐time HRVB amplitude correlates highly with a research gold‐standard spectral metric, enabling automated biofeedback delivery as a potential treatment component of DMHIs. Moreover, we identify demographic, psychological, and health factors relevant to building an equitable, accurate, and personalized biofeedback user experience.

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Biofeedback therapeutic effects on blood pressure levels in hypertensive individuals: A systematic review and meta-analysis

Cited by 11 publications

References 24 publications

Integrated use of biofeedback and neurofeedback techniques in treating pathological conditions and improving performance: a narrative review

Integrated use of biofeedback and neurofeedback techniques in treating pathological conditions and improving performance: a narrative review

The use of biofeedback techniques in clinical practice

Real‐time heart rate variability biofeedback amplitude during a large‐scale digital mental health intervention differed by age, gender, and mental and physical health

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