Measurement of human emotions is a challenging task. The presentation in front of some of the best in the field of physiology and bio-chemistry at (AIIMS Rishikesh for the World Chronomedicine Congress) focused on methods to understand the impact of negative emotions through the parameters of the physical body. In other words, we need to measure the impact in a very objective manner (and not through just a subjective survey). The work we do (Regression therapy, hypnotherapy, sound healing and also Neuro-Linguistic-Programming/NLP) deals with emotions and emotional also play a role in various aspects of our life ranging from decision making, food choices, choices of our action and so on.
The goal of the presentation is to propose a methodology (based on data of 24 hour holter device) to understand (a) if individuals who have chronic disease show a negative impact on the nervous system and (b) during specific activities, based on the notes of the individual, can we correlate states of negative emotions with negative parameters of autonomic nervous system. Based on the findings, we can understand and influence the balance of our autonomic nervous system and drive better afferent (heart-to-brain) pathways to improve our nervous system and thereby minimize negative impact on endocrine system, inflammation/circulatory and immune system.
Modulating Autonomic Effects: A novel way to measure Stress Index based on Holter Data
Gunjan Y Trivedi, Banshi Saboo
Society for Energy & Emotions, Wellness Space, Ahmedabad
Diabetologist & Chairman, DiaCare, Ahmedabad
Lifestyle choices, along with negative emotions, are major risk factors in metabolic syndrome and chronic diseases. Stress or persistent negative emotions’ impact on emotional, social, cognitive and psychosocial well-being of the individual is well documented. However, most studies use subjective measures of stress and there is also an opportunity to understand how day-to-day emotions play a role in overall mood and physiology.
This study explored a Holter based heart rate variability (HRV) analysis method to evaluate the stress levels of different individuals in 20s and 30s (based on Baevskey’s Stress Index). The stress data during various activities (e.g. supine, awake) in a 5-minute intervals was compared to the norms to identify how and when the individual felt the most stress. This data was shared with the subject to validate the findings. The findings provide useful insights for possible expansion of this methodology to not only measure stress but also to study and interpret HRV parameters for individuals with metabolic syndrome or chronic disease to make the right intervention for a better quality of life and disease management. Finally, the ideas based on literature review and early experiments on reducing stress and enhancing HRV are presented.
Key words: Chronic disease, Stress Index, HRV, Autonomic function
Some slides & visuals captured below:
The visual below indicates a huge reduction in HRV (RMSSD: Root Mean Square of Standard Deviation of RR intervals) and a big increase in stress index (Ref: Baevskey method) for individuals with T1 Diabetes or subjects with some imbalance in their autonomic nervous system or endocrine system.
RMSSD and Stress index data show a clear trend in various individuals (Below)
The visual below shows how various activities map on the high/low range of stress index (lower the better) and RMSSD (higher the better)