Use of refined sample entropy and heart rate variability to assess the effects of wearable respiratory biofeedback

Technology advantages of body sensor networks (BSN) have shown great deal of promises in medical applications. In this paper we introduced a wearable device for biofeedback application based on the BSN platform we had developed. The biofeedback device we have developed includes the heart rate monitoring belt with conductive fabric and the biofeedback device with respiration belt. A wearable respiratory biofeedback system was preliminarily explored based on the BSN platform. Due to a large set of temporal scales, HRV cannot be completely characterized on a single time scale, and scaling techniques are required to deeply characterize its behavior. Therefore, refined sample entropy was proposed to assess our respiratory biofeedback effect. In-situ experiments showed that the biofeedback device worked as intended.