Which factors influence by sleep.
Caffeine, bedtime start, sickness, vitamin D3 and negative emotions statistically significantly and independently influence my sleep in restorative phases. I'll lower my caffeine intake, will go sleep earlier, take D3 every other morning, and try to reduce stress. Detailed analysis is here.
Outdated: The later i'm going to sleep, the less total sleep time i'll get. My optimal sleep time around 21:30 - 22:30 and will stick to it. Explained here.
Outdated: Average intake of 68 mg of caffeine between 8:30 and 13:00 is enough to destroy ~30 minutes of my sleep in restorative phases. Explained here
Increasing Deep Sleep
Pink noise stimulations increase my Deep sleep by ~11 minutes per night. Additional ~1h20m of DEEP sleep per week seems to be a significant effect. Explained here
Physical activity increases mood
Physical activity significantly increases my positive emotions and decrease negative emotions. 1 hour training / 10k steps is enough to get a valuable effect. Explained here
Tracking body temperature
Oura ring temperature seems to be accurate and reliable proxy to core body temperature and sensitive to body temperature spikes caused by sickness. Explained here
HRV and sickness
Standing RMSSD seems to be a useful tool which provides insights about illness onset and recovery and helps make a decision of resuming physical activity. Explained here
Increasing HRV with physical activity
Increase in physical activity leads to increase in HRV. Weekly standing HRV more sensitive to physical activity. Explained by weekly and daily analysis.
I've checked my body temperature circadian rhythm with iButton and it seems to be strong enough. Fitbit Charge 4 wrist temperature data also was accurate enough to reveal diurnal changes. Also i've found and measured power of resting HR diurnal changes.
Comparison to healthy population my sleep is fairly good. But i need to focus on lowering awake time during night.
Fitbit Charge 5 and 4 have a low agreement for absolute heart rate values, but their trends are pretty consistent. Both devices agree pretty well on steps.
Oura sleep staging seems to be in weak agreement compared to EEG device.
Withings Sleep staging have a moderate agreement and impressive long term averaged values.
Fitbit Charge 4 sleep staging have a moderate agreement (better than Oura / Withings) and shows impressive long term averaged values.
Fitbit Charge 5 sleep staging looks same as Charge 4.
Manual assessment seems to be a good estimate of total sleep time.
Data already collected, just need to finalyse.
- Sleep stages Fitbit Charge 4 vs Dreem 2 EEG agreement (done)
- Vitamin D and sleep (done)
- Vitamin B12 and sleep (done)
- Compare Fitbit Charge 5 vs 4
- Sleep stages Fitbit Charge 5 vs Dreem 2 EEG agreement
- Subjective sleep diary vs objective (Dreem 2, Oura, Fitbit Charge 5 and 4, Withings)
- Time in bed and Total sleep time agreement (Dreem 2, Oura, Fitbit Charge 5 and 4, Withings)
- Glucose response to different foods measure by CGM (Freestyle Libre)
- Physical activity and weight / body composition
- Physical activity and waist / hip circumference
- Food intake and weight / body composition
- Food intake and waist / hip circumference
- Postprandial RHR analysis as attempt to catch allergy
- Excessive food intake after poor sleep
- Check myself for HRV saturation phenomenon
- RHR and sickness
- RHR and physical activity
- Blood Pressure and physical activity
- Blood Pressure and food intake
- Blood Pressure and sleep
- Gwern Branwen blog. QS and QS Sleep sections. Meta science section explains problems of analysing data.
- Herman de Vries blog. Oura ring analysis and body composition posts looks interesting. But take into account that Oura ring is not accurate for sleep staging and TST.
- Measured.me. Oura ring post analysis looks interesting, but again, take into account that most of oura sleep data is inaccurate  . There is R Script for easy import oura raw data .
- Seth Roberts blog. Simple Arithmetic task looks interesting and i'm using it right now. Sleep, Vitamin D and other experiments worth reading, but data analysis raises questions. Pictures are broken - just rightclick them to open in new tab and remove "blog." from http address.
- QS Show & Tell. From here i've found intresting and implemented some of examples. Right now i'm using a CGM    and i've tried iButton for measuring my body temperature circadian rhythm 
- QS Forum contain some interesting topics. Just using search to find interesting things.
- Plews & Prof blog contains interesting posts about CGM  , fat burn during exercise. Interesting case of reducing visceral fat.
- QuantifiedScientist very good review of tracking devices.
- Michael Lustgarten is correlating his blood biomarkers with food intake and doing interesting review of longevity changes in blood chemistry.
- Andrew Flatt twitter worth reading to understand practical appliance of HRV
- Community Calls log worth searching for interesting topics.
- beepb00p. Some interesting examples of self data analysis and managment  
- lifehacky.net, post about Dreem and Oura looks solid
- https://github.com/woop/awesome-quantified-self for a list of interesting resources
Take into account that most QS experimenters doesnt bother with checking accuracy of their devices, blinding, statistical significance, confidence intervals, data distribution analysis, adjusting p-values for multiple comparisons, prone to observer/confirmation bias and other biases. So just add tonn of salt to the QS stories.
General health and longevity
If you want to know how to improve decision making and account for cognitive biases, increase rationality
Data collection in progress
In addition to wearables i'm using:
- Food intake and different blood biomarkers
- NBack and sleep
- Mental math, Seth Roberts method
- Tracking productivity
- Subjective sleep metrics
- MRI (brain, spine)