A smartphone based cardiac coherence biofeedback system

Abstract

Cardiac coherence biofeedback training consist on slowing one's breathing to 0.1 Hz in order to simulate the baroreflex sensitivity and increase the respiratory sinus arrhythmia efficiency. Several studies have shown that these breathing exercises can constitute an efficient therapy in many clinical contexts like cardiovascular diseases, asthma, fibromyalgia or post-traumatic stress. Such a non-intrusive therapeutic solution needs to be performed on an 8 to 10 weeks period. Even if some heart rate variability based solutions exist, they presented some mobility constrain rendering these cardiac / respiratory control technologies more difficult to perform on a daily used. In this paper, we present a new simplified smartphone based solution allowing people to process efficient cardiac coherence biofeedback exercises. Based on photo-plethysmographic imaging through the smartphone camera, this sensor-less technology allows controlling cardiac coherence biofeedback exercises through a simplified heart rate variability algorithm.

Biofeedback for Everyday Stress Management: A Systematic Review

“…For multimodal biofeedback systems, the concurrent feedback of multi-channel bio-data requires the investment of more effort in visualization and interface design. For instance, different data can be mapped onto various visual elements of the interface (De Jonckheere et al, 2014) or distributed to different sensory modalities of the display (e.g., a combination of sound, light, and changes in physical shape in Adelbach et al, 2012).…”

“…Three main HRV indices are typically used for biofeedback in the context of stress management, namely cardiac coherence, the ratio of low-frequency to high-frequency power (LF/HF ratio) and SDNN (standard deviation of IBI data). Cardiac coherence score/value is the most common HRV feature used for biofeedback (McCraty et al, 2009;Henriques et al, 2011;Lemaire et al, 2011;De Jonckheere et al, 2014;Whited et al, 2014;Ratanasiripong et al, 2015;Sarabia-Cobo, 2015). Cardiac coherence describes the level of resonance between heart rate variations and the respiration cycle.…”

“…The biofeedback data are displayed on the screen of a personal computer (n = 24) or a mobile/portable device (n = 15). The ambient medium allows the users to receive biofeedback information through the surroundings in a physical Larkin et al, 1992;Goodie and Larkin, 2006;McCraty et al, 2009;Strunk et al, 2009;Cutshall et al, 2011;Henriques et al, 2011;Morarend et al, 2011;Edvardsson et al, 2012;Moraveji et al, 2012;Paul and Garg, 2012;Sanchez et al, 2012;Sutarto et al, 2012;Wells et al, 2012;Wu et al, 2012Wu et al, , 2015Prinsloo et al, 2013;Peira et al, 2014;Whited et al, 2014;Lewis et al, 2015;Pusenjak et al, 2015;Sarabia-Cobo, 2015;Meier and Welch, 2016;Munafò et al, 2016Animations Feijs et al, 2013Al Osman et al, 2016 Visual scene Bouchard et al, 2012;De Jonckheere et al, 2014;Gaggioli et al, 2014;Dillon et al, 2016;van Rooij et al, 2016 Virtual character Chittaro and Sioni, 2014;Arroyo-Palacios and Slater, 2016 Modified game Parnandi et al, 2013;Kotozaki et al, 2014 Ambient light Snyder et al, 2015 Auditory Musical expression Yokoyama et al, 2002;Morarend et al, 2011;Vidyarthi and Riecke, 2013;...…”

“…Most of the studies (n = 33) used a blank control group or condition, where the participants receive neither biofeedback nor other alternatives. In addition, biofeedback training can also be compared with other relaxation approaches, such as a watching a relaxing video (Sanchez et al, 2012), following a preset relaxation guidance (Adelbach et al, 2012;De Jonckheere et al, 2014;Snyder et al, 2015), receiving a fake biofeedback signal (Strunk et al, 2009), performing deep breathing (Parnandi et al, 2013), and doing meditation (van der Zwan et al, 2015), or physical exercise (Meier and Welch, 2016). Table 4 shows typical metrics used to assess the effectiveness of biofeedback for stress alleviation.…”

<p>Cardiac dysautonomia in depression – heart rate variability biofeedback as a potential add-on therapy</p>

“…It was reported to acquire ECG signals and transmit them to a server via a mobile device offering accurate HRVB measurement which is portable. In a preliminary efficiency study, a smartphone solution for cardiac coherence training was presented 148. It was based on a photopletysmographic imaging through the smartphone camera.…”