Boosting Heart Rate Variability Biofeedback Adaptability in Cardiac Rehabilitation with Cognitive Model

Abstract

Cardiovascular diseases have emerged as a serious threat to global human health. Cardiac Rehabilitation (CR) is increasingly known as a crucial component in the continuum of care for patients with cardiovascular. Heart Rate Variability Biofeedback (HRVB) facilitates the modulation of the patient's Autonomic Nervous System (ANS) non-invasively by enabling Resonance Frequency (RF) breathing of patients, and realizes the treatment of cardiovascular diseases, which provides support to the development of CR. However, it heavily depends on the manual selection of RF and face-to-face guidance of doctors through the traditional therapies of HRVB, which results in the great constraint of HRVB in widespread application and development in home-based CR. Herein, we proposed a remote human-computer collaborative HRVB system that enabled the independent adjustment of RF, which is named "FreeResp". It gets rid of the requirement of manual adjustment of RF by utilizing a simplistic cognitive computational model. Moreover, wearable technology and the Internet of Things (IoT) were integrated to make remote treatments for patients at home possible. FreeResp exhibited commendable consistency with conventional HRVB methods in determining RF values (22/24) among 24 valid training samples. In addition, the results of the one-month home-based RF breathing training test that used FreeResp demonstrated a significant enhancement in the participants' Heart Rate Variability (HRV) (p < 0.05). Therefore, the FreeResp, as a novel healthcare system, offers timely and precise interventions for home-based patients, providing a fresh perspective for the advancement of home-based CR, and pioneering new therapeutic approaches for long-term cardiovascular health management.