Respiration and heart rate during meditation and reading

 ECG, heartbeat, respiration  Comments Off on Respiration and heart rate during meditation and reading
Aug 102015
 

To explore the physiology of zazen, we began by recording respiration and heart rhythms using a respiration monitor and an electrocardiographic (ECG) sensor.

Eight subjects participated in the study. Some had training in zazen; others had experience with other meditative traditions (Vipassana, Yogic). Electrocardiogram and respiration data were collected for both meditative (counting the breath) and non-meditative (reading) conditions. Sessions were about 20 minutes long.

A Cardiorespiratory Viewer computer program was developed to aid in the display and analysis of the breath and heart data.

Cardiorespiratory Viewer

Program for displaying and analyzing ECG and respiration signals

Results were as follows:

breathing rates for meditative vs. non-meditative conditions

Breathing rate among eight subjects for meditative vs. non-meditative conditions. Rates during reading were typically double or greater compared to meditation.

At least among these eight subjects, trained in Zen, Vipassana and Yoga, breath rate was substantially slower (by at least a factor of two) during meditation than during reading. This is not surprising, given that these ancient traditions have a common origin.

 

In addition, we noted that heart rate did not vary appreciatively between the meditation condition and non-meditative reading. Again, this is expected as our heart rate is not usually under our conscious control and it is generally not part of meditation training.

heart rates for counting vs. reading

Heart rate among eight subjects under meditative and non-meditative conditions. Rates were not significantly different during counting, following the breath or reading.

 

Jul 172015
 

The plots below show electrocardiogram and respiration signals for a 20-second segment of meditation.

Heartbeat and respiration

Heartbeat and Respiration during meditation. Note the increase in amplitude of the ECG signal during exhalations.

During exhalations, the amplitude of the waves in the upper plot (the sharp spikes in the electrocardiogram, known as R-waves) increase while they decrease during inhalations.

A comparison of ECG signals for a novice and an experienced meditator are shown below.

novice meditator

Heartbeat and respiration for Subject 8, a relatively inexperienced meditator. Amplitude of R-wave increases by ~10% during exhalations.

 

experienced meditotor

Heartbeat and respiration for a highly trained meditator. Amplitude of R-wave increases by ~50% during exhalations.

 

For novice meditators, this effect was small (roughly 10% change in R-wave amplitude, as shown in the upper figure, above). For highly trained meditators the effect was quite pronounced (roughly 50% as shown in the lower figure, above).

The amplitude of the R-wave is an indicator of the strength of the signal from the heart when the left ventricle is forcing blood out to the rest of the body. The electrical resistance of the body between the heart and the ECG electrode on the surface of the skin changes as the lungs fill with air and then collapse. After consulting with a cardiorespiratory expert (an anesthesiologist), I have concluded that this dramatic change in R-wave magnitude reflects the deeper breathing of the trained meditator—as the intrathoracic cavity collapses during exhalation, the gap between the heart and the outer surface of the body (where the ECG signal is measured) shrinks, thereby reducing electrical resistance and resulting in an increased amplitude of the R-wave.

Jun 162015
 

In September 2014 I enrolled in an online course Exploring Neural Data offered by Brown University via coursera.org. The basic premise of the course was that students would be able to access data coming from various neuroscience labs around the country and learn techniques for analyzing that data, forming hypotheses and testing them. Participation in the course required learning the Python programming language. It sounded like an opportunity I couldn’t pass up. I had already completed two coursera online courses, Duke University’s Medical Neuroscience and Hebrew University of Jerusalem’s Synapses, Neurons and Brains, which gave me a bit of orientation to neuroscience (my background is physics and astronomy). I also discovered some good online tutorials on Python, so I could start familiarizing myself with a new language.

The final project for the Exploring Neural Data course was to apply some of our programming skills to a new data set. I chose to collect respiration and and electrocardiogram (ECG) data for subjects during meditation and reading. I chose to develop a new application I called the Cardiorespiratory Viewer. Written in Python, using the Anaconda Spyder programming environment, it imports program modules from the Tkinter, numpy, scipy and matplotlib libraries. The application reads data files generated by the LabQuest recorder, displays simultaneous plots of EKG voltage and breath pressure, and enables the user to specify time segments and signal threshold levels for analysis.

Cardiorespiratory Viewer

Program for displaying and analyzing ECG and respiration signals

PDF for final project, Exploratory Investigation of Cardiorespiratory System during Meditation

 

Jun 132015
 

A few years ago I realized that during Zen meditation, while paying attention to my breath, I was also aware of my heart beating. I started counting heartbeats during my inhalations and exhalations and found that during an inhalation, there were about four beats and during the exhalation roughly 8-10 beats. I thought it would be interesting to match a fixed number of beats, say ten with each exhalation, and maintain the synchronization during the meditation period. The synchronized rhythm felt pleasurable—having both the heart and lungs involved seemed to help me to maintain a clear mind. This experience was my motivation for recording an electrocardiogram (ECG) of heart rhythm simultaneously with respiration.

Questions: