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. Making Sense of my Bio-SignalsMaking Sense of my Bio-Signals Fu-Chieh Hsu, Ph.D.
- 2. Who am I • retired technology geek (i.e., speed freak) – top manager at IDT, MoSys, TSMC • passion and curiosity to measure, quantify and understand oneself
- 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. 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. What I Did • Wired myself up with EEG, ECG, Motion and Posture Sensors • Getting on with my normal day, and night • Study and compare the “stories” told by various sensors
- 6. How I did it (1) • Miniature wireless bio-sensor like this
- 7. How I did it (2) • On these body locations
- 8. How I did it (3) • Data streams like this
- 9. How I did it (4) • Checking on others Sigma peak @ 11.2Hz, 12.2Hz, 29Hz? Alpha anomalies too
- 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. What I Learned (2) • Quality is more important than quantity • Explore, experience, discern and form your own well-informed decision • on What-to-Track and Why
- 12. The Details, Please • Outrageous, you are attacking everyone!
- 13. The Myth: EEG (1) • Are these really my brainwaves? – if you are still, not making faces, no muscle activity, no tension or stress, … then maybe
- 14. The Myth: EEG (2) • How to identify artifacts? – Movement artifacts at low frequency – Muscle artifacts at high frequency
- 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 widely spaced
- 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. The Myth: EEG (4) • Do Beta and Gamma waves have broad bandwidth? – ONLY as calculated from FFT – They often contain small random sharp spikes (pulses) very closely spaced
- 18. The Myth: EEG (5) • Do most people conform to textbook bands? – ONLY after the non-conforming ones are filtered out – Highly varied Alpha band, many are weak or none – Occasional oddly placed Sigma band
- 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. The Myth: ECG/HRV (1) • Do most people conform to textbook bands? – ONLY after the non-conforming breathing ones are filtered out (highly modulated by deep breathing) – LF/HF highly sensitive to natural breathing rate
- 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. 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. The Myth: Activity (1) • Can Activity tells a good Sleep story? – NO WAY
- 24. The Myth: Activity (2) • Can Activity tells a good day story? – Well… – Posture is better (on body trunk, not limb)
- 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 understanding the data
- 27. What I Learned • Quality is more important than quantity • Explore, experience, discern and form my own well-informed decision • on What-to-Track and Why
- 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