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SVHealth2.0 Wearables Symposium - August 2018


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Join us for an insightful and provocative discussion on what it takes to build successful wearables. Our panelists represent three leaders whose technologies make it possible for our devices do all the cool stuff we love.

Karl Etzel, Business Development Consultant, Firstbeat: the leader in heart-rate algorithms. Got a Garmin that tells you when to train hard and when to recover? Thank Firstbeat! In understanding fitness metrics, VO2max is a great place to start. Learn more at

Ryan Kraudel, VP Marketing, Valencell: creator of the world's most accurate biosensor systems, found in leading brands including Jabra, Bose and Suunto. Here's a great webinar on Valencell's work in the fast-growing hearable product category:

Yao Lu, Americas Sales Director, Ambiq Micro: their low-power semiconductors help companies like Spire, Huawei and Misfit (Fossil) reduce or eliminate the need for batteries, reduce overall system power and maximize industrial design flexibility. Here's a webinar from Ambiq CTO Scott Hanson on low power consumption and its impact on wearables and use cases:

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SVHealth2.0 Wearables Symposium - August 2018

  1. 1. Wearable Design Symposium August 2018 – SVHealth Meetup Plug and Play, Sunnyvale, CA
  2. 2. Agenda • Start w end in mind: A use case, not a measurement • Keys to success: Actionable, personalized, contextualized • Power management • Sensors • UX/analytics • Examples in medical, sport, and the intersection
  3. 3. First Phase Wearables Focused on general activity tracking, step counting, calorie counting, and reaching movement goals.
  4. 4. The Next Phase of Wearable Growth Value Drivers: • Deeper individual insights • Broad population insights • Guidance and prediction • Shifting healthcare delivery Biometrics driving deeper insights into personal health, fitness, and wellness.
  5. 5. Wearable + medical solutions are in the “forming” stages and will move towards increasing public health impact User Interface Health Screening Medical Device Replacement New Medical Solutions Description Wearables as a new UI for existing health and medical devices Using sensors in wearables for screening of chronic health conditions or risks, such as COPD, asthma, diabetes, etc. Wearables worn outside medical facilities to make existing medical devices more wearable or higher compliance Completely new systems that address previously unsolvable problems Examples Dexcom partnerships with Fitbit and Apple Cardiogram and Apple Watch screening for atrial fibrillation iRhythm atrial fibrillation sensors; Blood pressure readings from mobile phone Predicting the onset of a COPD attack, migraine, cardiac event, etc; Therapeutic solutions Time to Market Impact Now 1-3 years 1-3 years 3-5 years Public Health Impact Easier to view data Potentially saves money via early diagnosis and prevention Potentially saves money by lower-cost equipment, higher compliance, and less hospital visits Addresses completely unmet needs and may substantially lower medical costs
  6. 6. Start With The End in Mind
  7. 7. Start With The End in Mind: General Health Monitor Questions answered: • Am I active enough? • Am I getting enough sleep? • Am I qualifying for an insurance benefit? Technical requirements: • Accurate HRM • Low power consumption • Insightful analytics on the data
  8. 8. Ambiq Micro: The World’s Most Energy- Efficient Solutions 8 Confidential and Proprietary
  9. 9. 9 • Founded in 2010 to provide ultra-low power solutions for the IoT • Unmatched ultra-low power timing products, MCUs and wireless SoCs • Core technology (SPOT) based on sub-threshold circuit operation • SPOT Technology Roadmap to put AI everywhere The World’s Most Energy Efficient Solutions
  10. 10. 2006 2010 2012 2015 2016 2017 2014 Neural networks deployed on SPOT products 2nd generation MCU launched 1 MILLIONTH MCU PART SOLD 1st SPOT MCU launches >10X lower power First commercial Real Time Clock products launched Ambiq Micro founded First SPOT processor built @ University of Michigan 1 MILLIONTH REAL TIME CLOCK SOLD 25 MILLIONTH PART SOLD 3nd generation SoC launched 2018 Ambiq Micro History 10
  11. 11. The Battery-Powered Internet of Things 11 The future of IoT is exciting – but not if we need to replace billions of batteries per day/month/year [Image source: Cisco]
  12. 12. Battery Strain in Wearables • Segment display • Basic watch functions • Multi-year battery life 12 • High res color display • Basic watch functions • Motion/activity tracking • Heart rate monitoring • GPS tracking • Altimeter • Thermometer • Bluetooth radio • Days/weeks battery life
  13. 13. Battery Strain in Wearables • Segment display • Basic watch functions • Multi-year battery life 13 • High res color display • Basic watch functions • Motion/activity tracking • Heart rate monitoring • GPS tracking • Altimeter • Thermometer • Bluetooth radio • Days/weeks battery life Smaller, thinner industrial designs New functions (cellular radios, new biosensors, more sensor analysis, etc.) New use cases (e.g., smart clothing with 1+ year life)
  14. 14. No Easy Solution with Batteries 14 Batteries just aren’t improving fast enough!
  15. 15. The Other Side of the Energy Equation 15 Component Power Consumption Display 10-100mW MCU/CPU 0.1-10mW Radio 10-30mW Heart Rate Monitor 0.1-1mW GPS Receiver 10-100mW Power Management 10-20% of system power MCU Radio Display Sensor PMIC 370mWh battery 24h/day * 7 days = 2.2mW average power for 1 week life 675mWh battery 24h/day * 14 days = 77µW average power for 1 year life 24h/day * 365 days
  16. 16. Addressing the IC Energy Problem (1/2) 16 Moore’s Law has been one of the strongest drivers of energy efficiency gains [Dreslinski et al., Proc. of the IEEE, 2010]
  17. 17. Addressing the IC Energy Problem (2/2) 17 0 Volts 1.2 Volts 0 Volts 0.3 Volts Energy ~ (Voltage)2 Conventional Circuit Design Sub-threshold Circuit Design Sub-threshold design was first conceived >30 years ago, but Ambiq was the first to build a comprehensive platform
  18. 18. 18 Extreme Sensitivity to Temperature Extreme Sensitivity to Voltage Extreme Sensitivity to Manufacturing Variations Sub-threshold design has conventionally been viewed as impossible due to exponential sensitivities – until Ambiq developed the SPOT Platform Subthreshold: A delicate balancing act
  19. 19. We’ve Come a Long Way 19 Texas Instruments MSP430 Ambiq Micro Apollo3 Improvement Launch Date 2003 2018 -- Processor Core 16b Proprietary Core 32b ARM Core -- Max Speed 8 MHz 48 MHz Boost mode 96MHz 6X – 12X Flash 60 kB 1 MB 17X RAM 2 kB 384 kB 192X Power Consumption Per Clock Cycle 440 µW/MHz 26 µW/MHz 17X Power Consumption Per Unit of Work 400 µW/Coremark 10 µW/Coremark 40X Today’s best in class processor is 40X more energy efficient than the best in class processor in 2003
  20. 20. 20 Leading Mobile Phone Brand Top Animal Tracking Firm EU Govt Smart Meter Vendor Top 5 Wearable Brand Top 3 Smartcard Vendor Top US Watch Vendor Solving the Hardest Energy Problems Today
  21. 21. 21 True Always-Listening Voice Control Radio Analog & Sensor Interfaces Battery Management Cache MCU Digital Interfaces RAM Ultra-low power footprint keyword detection, voice assistant integration, and command recognition Always-on and always-listening voice activation and commands for battery-powered and mobile applications. Highly efficient algorithm processing maintains high quality and the best user experience at ultra-low power
  22. 22. © 2018 Valencell, Inc Valencell provides biometric sensors for more wearables than any other company in the world VALENCELL CONFIDENTIAL INFORMATION, PATENTS & PATENTS PENDING Valencell Sensor Technology
  23. 23. ©2018 Valencell. Inc Audio Earbuds Wrist Devices Armbands/Patches Valencell made photoplethysmography (PPG) truly wearable and suitable for virtually any activity and form-factor PPG before Valencell • Accurate only in hospitals or low activity settings • Didn’t work outdoors (sunlight contamination) • Not part of what people already wear PPG after Valencell • Accurate during virtually any activity • Accurate indoors and outdoors • Integrated within popular consumer form-factors
  24. 24. ©2018 Valencell. Inc Top 5 Challenges in wearable PPG Source: “Optical heart-rate measurement’s top 5 challenges” Dr. Steven LeBoeuf; EDN Magazine; 8-25-15 Optical Noise Skin Tone Blood Perfusion Sensor Location/Form- Factor Crossover Problem
  25. 25. © 2018 Valencell, Inc What‘s even more important is knowing when the data is wrong Time (s) SystolicBloodPressure(mmHg) Blue dots represent 100% confidence Less than 100% confidence
  26. 26. © 2017 Valencell, Inc Peak Amplitude (Pulse Pressure) RRi (HRV, Cardiac Functioning) Breathing Rate (Metabolic Status) Perfusion Variation Heart Rate Highly accurate PPG can be used to accurately assess numerous biometrics •Breathing Rate •Heart Rate Variability (HRV) •Cardiovascular Fitness •Blood Pressure •Blood Oxygen •Cardiac Efficiency •Blood Perfusion
  27. 27. ©2018 Valencell. Inc Accurate biometric sensor data has been proven and validated for health and medical assessments Assessment Definition What is means for fitness What is means for health VO2max Aerobic capacity – primary measure of chronic change to cardiovascular fitness Higher VO2max is correlated with better performance during aerobic activities Higher VO2max is correlated with lower mortality & improved recovery from a cardiac event [Anderson, Jetté, Kodama, Lee] Resting Heart Rate (HRrest) HR during an awake period of no exertion Decreasing Resting HR is correlated with increasing fitness Steadily increasing Resting HR is correlated with the progression of cardiovascular disease [Arnold, Fox, Nauman] HR Recovery HR over 1-mintute after intense exercise Higher HR Recovery implies better exercise endurance Higher HR Recovery implies better cardiovascular health[Ching, Cho, Lipinski, Nishime] HR Response HR over 1-mintute at the start of exercise Higher HR Response can imply low cardiac readiness for exercise Higher HR Response paired with “chronotropic incompetence” can predict carotid atherosclerosis [Falcone, Jaqoda, Jae, Maddox, Myers] Cardiac Efficiency Average cadence divided by average heart rate (at steady state): Cavg/HRavg The higher cardiac efficiency, the less heart beats are needed for all physical activities Steadily declining cardiac efficiency is correlated with the onset of hypertension [Laine, Sung] HRV Heart rate variability -- statistical variability of RR- intervals HRV can diagnose psychosocial stress & overtraining in exercise HRV can predict atrial fibrillation & arrhythmia [Chon, Hohnloser, McManus, Park, Valkama]
  28. 28. • Karl Etzel US Account Representative Analytics and the Wearable User Experience
  29. 29. Challenges, Opportunities “Novelty data” – even if accurate, so what?
  30. 30. • We differ in our physiology. We also differ in our lifestyle, demands and challenges. • “Performance” means different things in different settings • Wearables are valuable only if they deliver changes, whether for behaviors, training, or recovery • The same heartbeat data from different users, in different contexts, can have vastly different meanings Body Analytics for Sports and Well-Being MANAGE STRESS ENHANCE RECOVERY EXERCISE RIGHT
  31. 31. • Professional Sports More than 22 000 professional athletes and 800 teams worldwide use Firstbeat solutions to improve performance. • Consumer Products Firstbeat’s heartbeat analytics are integrated into over 70 wearables to provide meaningful insights for fitness and lifestyle. • Wellness Services 250 000 people around the world have undergone the Firstbeat Lifestyle Assessment to improve their personal well-being & performance. Personalized Insights for Health and Performance
  32. 32. Multiple Dimensions to Personalization • Long term goal - Max performance vs. staying healthy • Short term goal – Loading, peaking or recovering?
  33. 33. Context Matters • Temperature • Humidity • Time of day • Wind
  34. 34. Many Inputs to the Body’s Stress Response
  35. 35. Stress is BAD! (Except when it’s not) Pilot or passenger? Seeing that you are stressed out, is stressful
  36. 36. Neither X nor Y but X vs. Y
  37. 37. Messaging – Know Your Audience
  38. 38. Variety of Consumers for Data • Each 1-MET (3.5 ml/kg/min of VO2) higher increment in fitness was associated with a $1,592 annual reduction in health care costs. • If VO2max is less than 26 ml/kg/min, all cause mortality risk is increased by 70% compared with VO2max above 38 ml/kg/min
  39. 39. Selecting Accurate and Relevant Data Points
  40. 40. Battery Life and Use Case • 6 days, but no wireless, or GPS • Optimized for continuous tracking, periodic measurement, with human in loop feedback
  41. 41. Parting Thoughts • Work backwards from the question – what decision will the user make differently based on the data? • Can you clear the “go back for it” threshold • Think multi-sensor • Think multi-consumer