Tag Archives: blood pressure
Siva Raj was interested in lowering his blood pressure. With a family history of cardiovascular disease and heart attacks he was worried about slightly elevated blood pressure (pre-hypertension). As someone engaged with understanding and building fitness applications he thought he would be able to lower his blood pressure by staying on track with a regular exercise program that focused on cycling. Interestingly his blood pressure measurement didn’t respond to his constant exercise or weight loss. After reading more research literature about the link between fitness and cardiovascular health Siva decided to change his training to improve his fitness. He decided to incorporate a increased intensity into his routine. After a short period of time he had increases in this fitness and was able to observe the reduction in blood pressure he was looking for. In the video below, filmed at the Boston QS meetup group, Siva explains his methods and talks about how he was able to track his body’s response to different fitness routines.
Jamie Williams found himself with almost two years of self-tracking data including physical activity, blood pressure, and weight. Because of his interest in data visualization and coding he decided to learn how to access it the data and work on visualizing and understanding some of the trends and patterns. In this talk, presented at the QS St. Louis meetup group, he takes a deep dive into his activity and step data as well as his blood pressure data to learn about himself and what affects his behavior and associated data.
What Did Jamie Do?
Out of pure interest in seeing what the data would reveal, Jamie utilized a combination of devices to track his physical activity, blood pressure, heart rate, weight, numbers of drinks, and automobile travel. He then went on to explore ways in which he could pull down, integrate, visualize, and ultimately make sense of what he collected.
How Did He Do It?
In order to obtain his data on a minute-level resolution, Jamie had to email FitBit for a specialized use of their API. He then employed Mathematica to develop a number of (beautiful) visualizations of his activity – along with other key moments in his life (moving to St. Louis, changing job location, preparing for a Half Marathon, etc.). Jamie was able to compare his data not only to his peers through FitBit, but also to others of his demographic in the U.S. using the publicily available NHANES data set.
What Did He Learn?
Through Jamie’s Quantified Self collection and analysis efforts, he learned a lot not only about the patterns and changes in his activity, but why they were the case. He also presented great feedback about one’s mindset when comparing to peers vs. the general population.
Withing Blood Pressure Cuff
Thank you to QS St. Louis organizer, William Dahl, and Jamie for the original posting of this talk!
Chatellier, ‘Feasibility Study of N-of-1 Trials With Blood Pressure
Hypertension, 25 (2): 294 – Hypertension
I measure blood pressure at home. Unfortunately, it is easy to become bored with this procedure, and neglect it. In fact, it is more fun to wonder why measuring blood pressure is so boring than actually measuring blood pressure, so of course that’s what I’ve been spending some of my time on lately. My guess is that part of the problem is that home blood pressure measurements vary a lot. I’ve had single sessions in which my systolic ranged 11 points and my diastolic 16 points. This measurement range is larger than the likely effect of any intervention I’m going to be making. Therefore, a single measurement session doesn’t give me the feeling that I’m adding any information. It’s frustrating and stupid. Damn measurements.
Of course a good way to track measurements with a lot of random error is to use a moving average. So here’s the question: how many blood pressure measurements does it take to get results that accurate enough to discern the effects of treatment? Here is a graph from a paper published in Hypertension that suggests an answer. I won’t break down the method here. There is a link to the paper at the bottom of the graph and you can explore it for yourself. The quick version is that researchers compared the difference between two series of measurements taken at home, varying the number of measurements in the series, and watched the difference decrease as the number of measurements went up. The graph shows a nice, smooth decrease in variation. You achieve 80% of the total drop in variation after 15 measurements.
In other words, if you take three measurements per day, you can get a decent baseline for blood pressure experiments in five days. This seems like good news.