The control of thought, attention and emotion is a difficult problem. Thinking of nothing or rather not thinking of something, is the most difficult challenge faced by every human being at different stages of life. An accomplished football player, a singer, musician, physicist or a medical surgeon: the performance of all of them depends only on their ability to focus or concentrate. This concentration, in turn, is largely dependent on their ability to resist distraction and controlling of their impulses and emotions. Meditation often involves an internal effort to self-regulate the mind in some way. Meditation, though for a long time was avoided as a scientific theme due to its complex nature and religious connotations, is studied with different neuro-scientific experimental tools, in the recent times. Moreover, it is often said to be influencing stress-dependent diseases such as anxiety, hypertensive disorders, tension headaches etc. Heart rate variability data before and during meditation, analysed for multifractal spectral width and Visibility degree parameters revealed significant differences between the pre and meditation states confirming that meditation has a direct impact on human heart. Chaos theory tells us that there is a natural background of chaos in our body—a loss of chaos can lead to an abnormal function—and in this respect meditation with a wider multifractal spectra or a higher Visibility Graph parameter leads to better functions of the body and thus confirming the increase of degree of complexity which could be a parameter for quantification of well being and hence an improved meditational therapy. Similar analysis should be done for other types of data for offering a benchmark in the assessment of cardiac states in a quantitative manner during different types of Yoga or meditation. This is a first of a kind quantitative assesment of heart rate dynamics during meditation with further validation this can help in measuring the effects of meditation.

Authors: Anirban Bhaduri and Dipak Ghosh
Frontiers in Physiology (Probable Impact Factor: 4.134 (Second most cited Journal in Physiology))
DOI: 10.3389/fphys.2016.00044
Front. Physiol. 7:44. doi: 10.3389/fphys.2016.00044
Status :Published
Area : Biomedical Data analysis