Making sense of my bio signals v2

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Presenter: FC Hsu
http://www.op-innovations.com
http://www.bioshare.info

Presentation from first Quantified Self Taiwan on Data Weekend held by CodeforTomorrow.org

http://www.meetup.com/qs-taiwan/events/119278852/
http://registrano.com/events/dataweekend02/

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Making sense of my bio signals v2

  1. 1. Making Sense of my Bio-SignalsMaking Sense of my Bio-SignalsFu-Chieh Hsu, Ph.D.
  2. 2. Who am I• retired technology geek (i.e., speed freak)– top manager at IDT, MoSys, TSMC• passion and curiosity to measure, quantifyand understand oneself
  3. 3. Who am I– apply latest tech capability– wonderful 2-year journey of learning & un-learning– build tools and SHARE– Raspberry Pi of Bio-sensors
  4. 4. My Story to Share• Not about the tools• All about the data– quantity of data is a good start– quality of data tells the real story– real story leads to real understanding– real understanding leads to real improvement(need for quality data => drives tools)
  5. 5. What I Did• Wired myself up with EEG, ECG, Motionand Posture Sensors• Getting on with my normal day, and night• Study and compare the “stories” told byvarious sensors
  6. 6. How I did it (1)• Miniature wirelessbio-sensor like this
  7. 7. How I did it (2)• On these body locations
  8. 8. How I did it (3)• Data streams like this
  9. 9. How I did it (4)• Checking on othersSigma peak @11.2Hz, 12.2Hz, 29Hz?Alpha anomalies too
  10. 10. What I Learned (1)• Don’t believe everything you read from“…” (textbook, news, ads, …)• Don’t believe everyone is the same• Don’t believe those “scores”
  11. 11. What I Learned (2)• Quality is more important than quantity• Explore, experience, discern and formyour own well-informed decision• on What-to-Track and Why
  12. 12. The Details, Please• Outrageous, you are attacking everyone!
  13. 13. The Myth: EEG (1)• Are thesereally mybrainwaves?– if you are still,not makingfaces, nomuscle activity,no tension orstress, …then maybe
  14. 14. The Myth: EEG (2)• How toidentifyartifacts?– Movementartifacts atlowfrequency– Muscleartifacts athighfrequency
  15. 15. The Myth: EEG (3A)• Are Delta waves slow moving?– ONLY after the fast moving parts are filtered out– They often contain large spikes (pulses) more widelyspaced
  16. 16. The Myth: EEG (3B)• Are Delta waves slow moving?– ONLY after the fast moving parts are filtered out– They often contain large spikes (pulses) more widely spaced
  17. 17. The Myth: EEG (4)• Do Beta and Gamma waves have broadbandwidth?– ONLY as calculated from FFT– They often contain small random sharp spikes(pulses) very closely spaced
  18. 18. The Myth: EEG (5)• Do most people conform to textbookbands?– ONLY after the non-conforming ones arefiltered out– Highly varied Alpha band, many are weak ornone– Occasional oddly placed Sigma band
  19. 19. The Myth: EEG (6)• Can EEG tells a good Sleep story?– ONLY after artifacts removed, energy bands calibrated– and supplemented by posture, movement data– Still can’t reliably tell between REM and (calmly) Wake
  20. 20. The Myth: ECG/HRV (1)• Do most people conform to textbook bands?– ONLY after the non-conforming breathing ones arefiltered out (highly modulated by deep breathing)– LF/HF highly sensitive to natural breathing rate
  21. 21. The Myth: ECG/HRV (2)• Do 5min ECG/HRV test tells a good ANS story?– LF/HF highly sensitive to movements and arousal– Wide variations over daily (24Hrs) cycle
  22. 22. The Myth: ECG/HRV (3)• Can ECG/HRV tells a good Sleep story?– Maybe, but NOT quite– YES with EEG, posture, movement data– Clear indicator for REM (if not active Wake)
  23. 23. The Myth: Activity (1)• Can Activity tells a good Sleep story?– NO WAY
  24. 24. The Myth: Activity (2)• Can Activity tells a good day story?– Well…– Posture is better (on body trunk, not limb)
  25. 25. Activity+Posture+EEG
  26. 26. What I Learned• Read with curiosity from “…” (textbook,news, ads, …), but THINK afterwards• Know I (and everyone else) am unique• Accept “score” only after understandingthe data
  27. 27. What I Learned• Quality is more important than quantity• Explore, experience, discern and form myown well-informed decision• on What-to-Track and Why
  28. 28. Thank You• Fu-Chieh Hsu, Ph.D.,OP-Innovations, Ltd.• fhsu@op-innovations.com• www.op-innovations.com• www.bioshare.info• Hsinchu, Taiwan, Republic of China

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