Category Archives: fitness

Testing the Finger Tap Test

testing finger tap test cns tap test by measured meFor the past several months I have been testing the CNS Tap Test, a mobile phone adaptation of the Finger Tap test often used by neuropsychologists and fitness professionals to measure the status of the central nervous system. The objective of this measurement experiment was to see if I could use this app to measure more objectively my physical and psychological health (I currently use subjective scales). The results were interesting but not sufficiently conclusive to include this test in my self-tracking inventory.

Tinke – My First Impressions

tinke review by measured meI recently purchased Tinké sensor, and have been using it for the past couple of weeks. The full review will be coming later (I still need to accumulate enough data), but so far I LOVE IT! My first impression is: it is extremely easy to use! Just plug the sensor into your mobile phone, launch the app and tap on the screen. It also provides a lot of interesting metrics, which I hope to use in my self-tracking experiments and projects. Here is a quick breakdown.

My Lifestream Dashboard is Now Up!

My Quantified Summer lifestream is now up! I plan to update it every 7-10 days. Check it out here or by clicking MY LIFESTREAM on the main menu of my blog.

My Walking Experiment: Comparing Runkeeper and Bodymedia

walking experiment runkeeper vs bodymediaI have been using RunKeeper to keep track of my walks and bike rides for a while now. In addition to distance and pace, RunKeeper offers an estimate of calories burned that is most likely derived based on my weight/age and distance information. Last month I had an idea to compare these estimates with those provided by my Bodymedia tracker, and to do that, I had to conduct an experiment, which lasted for about two weeks. The estimates provided by both trackers turned out to be very close. 

My Quantified Self Projects and Self-Experiments in March

measured me experiments in marchThe March is almost over, so I thought it is a good time to tell what kind of things I am have been tracking and what self-experiments I have been conducting this month. As usual, at the end of the month I will export data from my rTracker log , analyze it and will share any interesting insights and findings with you.

Wrap-Up of My January/February Self-Tracking Projects

january quantified self projectsIf you have not noticed yet, the “modus operandi” for this blog and my self-tracking efforts is a bit different this year. The month of January was spent collecting data, testing apps and services, and blogging about various QS issues, and month of February was dedicated to analyzing collected data, reviewing tools, and sharing insights and recommendations. So I thought it would be helpful if I summarized briefly what I learned during the last two month, in one post.

Health Hacks: How A Simple Heart Rate Test in the Morning Can Predict Your Day

quantified self fitness orthostatic testI continue crunching my January data, and in today’s post, will discuss a simple heart rate test that I have been performing last month every morning in order to evaluate its predictive power. It’s called orthostatic test, and it is widely used by athletes to assess their physical condition after the training. All you need is a stopwatch or a heart rate measuring app (I personally used Azumio’s Instant Heart Rate app).  Here is how you perform the test. The moment you wake up, try to stay still in bed and take your pulse measurement. That would be your resting heart rate (RHR). Then get out of bed and after standing for approximately 15-30 seconds without making any sudden movements, measure your standing heart rate (SHR). Now calculate the orthostatic heart rate (OHR): OHR = SHR – RHR. If you track your OHR for several weeks, you will notice that most of the times its values stay around the same, but occasionally will go higher. Those “spikes” in OHR happen the night after you overtrain at the gym, or if you don’t get a good night rest, get sick or because of some other disturbance in your autonomic nervous system. My theory was that since OHR measures the “recovery” of the body, perhaps, by looking at OHR in the morning, I would be able to predict how I will feel later that day. My self-tracking data partially confirmed that hypothesis: the morning OHR numbers can predict physical and mental performance later in the day. 

Gym Hacks: How I Compared Three Fitness Classes Using Self-Tracking Data

quantifiedself fitness gym hacks by measured meThis year I decided to “outsource” my gym workout, and instead of experimenting with various workout routines from fitness magazines and blogs, joined my gym’s “Total Body Conditioning” classes. The classes are completely free and are held every Monday, Wednesday, and Friday between 12:30 p.m. and 1:15 pm. Each class is led by a different trainer, and as a result, the routines and pace of the workout considerably vary across the days. For example, on Wednesdays, the focus is more on weights and core training, whereas on Mondays and Fridays it is mostly plyometrics and cardio. Curious to see if classes differ in terms of efficiency, I turned to Bodymedia and my own self-tracking data. Which class burns more calories and brings me closer to my six pack abs? The answer was just a couple of calculations away.

A Quick Peek at My Quantified Self Experiments and Projects in January

measured me blog quantified self personal analytics self experimentation personal informatics life optimization self improvement self development blogI am very excited to start this year with some new awesome self-tracking projects and experiments! For now, the major emphasis remains on areas like sleep, fitness, diet, cognition, and psyche, but I will be covering a bit productivity and finance, too. Here is a quick preview of what I am tracking (and working on) this month.

My #Fitsperiment Update (End of Week 4)

measured me blog fitness and diet abs fat loss self-experiment using BodymediaMy #fitsperiment challenge update:

Current stats (end of week 4):

Body Fat = 9.5% (Target = 8%)

FlexiScore = 100 (Target = 100)

Days Left = 0

And this concludes my #fitsperiment challenge! About a month ago, I challenged myself to: