This document discusses how consumer wearable technology is driving innovation in health and medical devices. It notes that optical sensing, like PPG, has improved to the point where wearables can accurately measure biometrics. While consumer fitness trackers have issues with accuracy, studies show wearables can detect conditions like atrial fibrillation. The document argues successful medical wearables will require understanding both consumer and clinical markets and performing rigorous clinical validation of sensor accuracy and use cases before seeking FDA approval.

1. How some consumer wearable
technology is driving innovation in
health and medical devices
May 18, 2017
Ryan Kraudel

2. ©2016 Valencell. Inc
Heart Rate
Chest Straps
1980
Armband
Calorimetry
2000 2010
Mobile
Tracking Apps
Activity
Trackers
GPS
2006-09
Connected vital
signs monitors
(not wearable)
2012 2013
Wrist/arm
activity trackers
Integrated
solutions/
smart-
devices
2014 -16
Compelling
use cases
2017-18 2019-20
Health/medical
wearables
Wearables are trending towards familiar form-factors,
and more compelling use cases (including health)
Sensor
accuracy is
critical here

3. ©2016 Valencell. Inc
Optical sensing (PPG) is the leading biometric sensing technology
at the heart of consumer biometric wearables
Peak Amplitude
(Pulse Pressure)
RRi
(HRV, Cardiac Functioning)
Breathing Rate
(Metabolic Status)
Perfusion Variation
Heart Rate
Ideal PPG Waveform

4. ©2016 Valencell. Inc
”Some fitness trackers may fall short in
measuring heart rate accurately, study
finds”
“Activity trackers not always great for
monitoring exercise heart rate”
“Don't bank on heart rate accuracy from
your fitness tracker”
“Wrist-worn activity trackers
measure heart rates better at rest
than during exercise’
Creating accurate biometric wearables is difficult

5. ©2016 Valencell. Inc
Cadence
(Step Rate)
Time
Beats(Steps)/Min
Sensor inaccuracies can make fitness and health
assessments useless
Accurate HRM Mood Ring HRM
HRV
HR
Response
Peak HR/
VO2max
HR Recovery
Cardiac
Efficiency

6. ©2016 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

7. ©2016 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]

8. ©2016 Valencell. Inc
Disease management
Guided fitness training
Prevention
Sleep quality
Diet management
Stress Management
Health diagnostics
Wearable optical sensing (PPG) systems are now demonstrating
performance levels suitable for medical use cases

9. ©2016 Valencell. Inc
Atrial fibrillation identification has been demonstrated using
optical sensor systems embedded in audio earbuds & wristbands
Valencell OHRM
ECG
Valencell OHRM
ECG
Normal Poincaré Plot Atrial Fibrillation Detected

10. ©2016 Valencell. Inc
-40
-30
-20
-10
0
10
20
30
70 80 90 100 110 120 130 140 150 160 170
DiffSBP
Mean SBP
Bland-Altman SBP
-30
-25
-20
-15
-10
-5
0
5
10
15
20
40 50 60 70 80 90 100
DiffDBP Mean DBP
Bland-Altman DBP
70
80
90
100
110
120
130
140
150
160
170
70 80 90 100 110 120 130 140 150 160 170
BenchmarkSBP
Model SBP
SBP Regression Analysis
40
50
60
70
80
90
100
40 50 60 70 80 90 100
BenchmarkDBP
Model DBP
DBP Regression Analysis
Error = -0.1 ± 9 mmHg (mean ± SD) Error = 0.0 ± 8 mmHg (mean ± SD)
Systolic & diastolic blood pressure tracking has been demonstrated
via finger & earbud-based optical sensor systems
R2 = 0.7 R2 = 0.6

11. ©2016 Valencell. Inc
Commercial innovation in consumer biometric wearables is beginning
to outpace that of traditional medical monitors
$10,000 clinical biometric
data collection system
$500 consumer biometric data
collection system

12. ©2016 Valencell. Inc
Market pull for wearable biomedical sensors in 5 key categories
Personal
Health
(Prevention)
Clinical
Research
Disease
Management
Disease Diagnosis Therapeutics
Description General fitness
and wellness
sensors having
prevention-based
UX
Sensors for
measuring
biometrics and
activity used in
clinical research
Sensors for chronic
disease management,
such as COPD,
asthma, diabetes, and
cardiovascular
disease
Sensors for screening or
diagnosing diseases, such
as sensors for atrial fib,
arrhythmia, and hypoxia
Sensors that provide
active feedback for
controlling therapeutic
medical devices
Example
Products
Omron Wellness;
HealthKit
Actigraph
products;
BIOPAC products;
ResearchKit
Philips HealthSuite iRhythm atrial fibrillation
sensors; Omron
hypertension screening
Medtronic insulin pump
systems &
neurostimulators
FDA
Regulated
No Typically not Yes Yes Yes – very highly

13. ©2016 Valencell. Inc
Friction exists between consumer & medical wearables markets
Consumer fitness wearables
• Crowdfunded + light VC
• Glam marketing
• Accuracy not a top priority
• Loose on validation
• Style & branding are critical
• Looks for ways to avoid FDA
• 2-year timelines
Medical wearables
• Heavily venture-backed
• Conservative B2B marketing
• Accuracy is critical
• Heavy on validation
• Style and branding are irrelevant
• FDA approval is critical to success
• 7+ year timelines

14. ©2016 Valencell. Inc
FDA regulation is not the bottleneck with new medical wearables…
Use case validation is the key obstacle
Prototyping
(~2 - 5 weeks)
Feasibility Testing
(~1 - 2 weeks)
Use Case Validation
(~year)
Accuracy Validation
UX Validation
Independent
Clinical Validation
FDA Approval
(510K)

15. ©2016 Valencell. Inc
Success in biomedical wearables will require an understanding of
both consumer & medical markets & clinical validation

16. ©2016 Valencell. Inc
Key take-aways…
• Optical biometric sensor technology (PPG) has accelerated to the point where it is
accurate enough for at least some ambulatory medical applications
• In some ways biometric wearable technology is actually outpacing medical technology
• One point of friction is merging the rather chaotic exploration and rapid innovation of
fitness wearables with the methodical discipline of clinical validation
• Companies that can apply medical-style validation to these innovative wearable sensor
technologies, and that can understand both consumer and medical markets, are best-
poised to find success in the marketplace

17. Thank You!
Ryan Kraudel
kraudel@valencell.com
@kraudel