Characteristics of HRV patterns for different yoga postures - Pitale, Rahul; Tajane, Kapil; Phadke, Leena; Joshi, Aniruddha; Umale, Jayant (2014 Annual IEEE India Conference (INDICON), 2014)
Human heart rate fluctuates in a complex and non-stationary manner, due to continuous influences from autonomic nervous system and other factors (harmones, temp, etc) on the sinoatrial node (S.A) (Pacemaker of the heart). ANS dysfunction is known to be associated with various cardiovascular and lifestyle diseases. The importance of traditional ancient Indian practice like Yoga has increased significantly due to the observed beneficial effects of it in various lifestyle diseases. Preliminary studies have shown that yoga may have its beneficial effect by influencing autonomic nervous system. Heart rate variability (HRV) is a most promising predictive and prognostic marker of autonomic (ANS) activity. HRV is analyzed by time and frequency domain parameters (Fast Fourier Transform). Being linear parameters these are not able to extract full information regarding the non linear behavior of heart rate fluctuations. In this paper, we propose to analyze HRV by using linear as well as non-linear methods during different yogaasanas. These mathematical models will be useful to understand the underlying physiological mechanisms during different yogasanas.
Keywords: ECG; HRV; Poincare plot; Recurrence plot; Yogasanas

To study non linear features in circadian heart rate variability amongst healthy subjects - Tajane, Kapil; Pitale, Rahul; Phadke, Leena; Joshi, Aniruddha; Umale, Jayant (2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2014)
ECG signal is used for diagnosis of ailments of heart. HRV is used as a predictive and prognostic marker of autonomic dis-functioning. ANS is known to influence heart and any dis-functioning of this system leads to cardiac disorders. ANS has endogenous circadian rhythm. Circadian rhythms are responsible for physical, mental and behavioral changes that follow a roughly 24-hour cycle. Previous studies have shown large inter and intra individual differences in HRV which has lead to difficulties in establishing standard norms. Therefore the aim of our study is to establish a brief protocol for HRV analysis where we will be able to extract features in shorter duration of recording, representative of 24 hour fluctuations in HRV. In this paper we have studied different linear as well as non-linear techniques to analyze circadian HRV. 24 hour ECG recording of 15 subjects using Minimum Activity Protocol subjected for HRV analysis.
3rd International Conference on Advances in Computing, Communications and Informatics (ICACCI), New Delhi, INDIA, SEP 24-27, 2014
Keywords: Circadian Rhythm; Correlation Dimensions; DFA; ECG; HRV