Integrating Optical Heart

Rate and Biometrics Into

a Wearable Device

Ryan Kraudel

VP, Marketing

©2016 Valencell. Inc

Photoplethysmography (PPG) – an ancient technology

recently revolutionized with wearable innovations

Late 1800s

1981

1990

2013

Real-time blood flow was 1st

assessed using early light bulbs

The first pulse oximeters were

launched for hospital use,

measuring pulse rate & blood

oxygen via 2 alternating LEDs

Sporadic motion artifact removal

was developed for finger pulse

oximeters in hospital settings

Continuous active motion artifact

removal was commercialized in

consumer PPG products (earbuds)

for use in everyday activities Late 1930s

The term

“photoplethysmography”

coined by scientists

2010Passive PPG monitoring

via consumer armbands

Revolutionary innovations have made PPG wearable:

• Optomechanics that effectively couple light to/from the body

• Tight-integration into consumer form-factors

• Active noise removal using noise references & advanced DSP

©2016 Valencell. Inc

Active Signal Characterization

Optical noise from skin motion, body

motion, & environmental noise (such as

sunlight) is actively removed from the

blood flow signals in real-time.

Motion tolerant optical heart rate sensing combines

advanced sensor design + active signal characterization

Highly Accurate

PPG Signal

PPG Sensor Systems

Years of R&D have resulted in advanced

optomechanical designs and integration

expertise that optimize sensor signal quality.

PerformTek vs. CSHRM

n = 40

R2 = 0.99

©2016 Valencell. Inc

Peak Amplitude(Pulse Pressure)

RRi(HRV, Cardiac Functioning)

Breathing Rate(Metabolic Status)

Perfusion Variation

Heart Rate

Highly accurate PPG is the foundation for

valuable derivative metrics

Active signal characterization

from PPG can accurately assess

numerous biometrics

• Heart Rate

• Breathing Rate

• Heart Rate

Variability (HRV)

• Cardiovascular

Fitness

• Blood Pressure

• Blood Oxygen

• Cardiac

Efficiency

©2016 Valencell. Inc

Power

Efficiency

Form Factor

Diversity

Accuracy

Biometric

Diversity

Validation in

Multiple Activities

ECGOptical/PPG

Three key technologies are currently employed in consumer

heart rate monitors

Bioimpedance

©2016 Valencell. Inc

Rich form-factor diversity in biometric

wearables using PPG

Armbands

©2016 Valencell. Inc

Top 5 Challenges in OHRM

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 Crossover Problem

©2016 Valencell. Inc

Cadence

(Step

Rate)

Time

Be

ats

(Ste

ps)/

Min

Accurate heart rate + cadence is critical

for important fitness and health assessments…

Accurate HRM Mood Ring HRM

HRV

HR

Response

Peak HR/

VO2max

HR Recovery

Cardiac

Efficiency

©2016 Valencell. Inc

Two key factors determine accuracy, reliability, & scalability…

and these cannot be designed independently

• Coupling

• Wavelengths

• Multiple form factors

• Multiple emitters

• Gross displacement

• Motion-tolerant

• Validation

• Performance

• Power management

• Scalable biometric

roadmap

OptomechanicsSignal Extraction

Algorithms

©2016 Valencell. Inc

Extensive testing is critical to success

•Testing protocols that match the use cases: resting,

lifestyle activities, mild exercise, aggressive

exercise, interval training, etc.

•Validation datasets on 30+ participants of multiple

physical habitus, gender, & skin tone

•Biometric analysis that includes regression

analysis (R2) & Bland-Altman analysis

•Diagnosis analysis that includes true positives,

false positives, true negatives, false negatives, &

total positives & negatives

•Ideally, there must be independent validation of

each metric

©2016 Valencell. Inc

Studying how biometrics change over time

• 6 week study of heterogeneous participant mix with varying fitness levels, skin

tones, genders, and BMI

• Standard assessment of VO2max & lactate threshold using indirect calorimetry

• 2 days/week of high-intensity circuit training

• 3 days/week of cardiovascular training on treadmill

• Specific 15-min warm-up prior to each treadmill session – allowing for

assessment of fitness changes from week-to-week

• Baseline sensors – CSHRM, indirect calorimetry, calibrated treadmill

• Device under test – Valencell earbuds reference design

©2016 Valencell. Inc

By tracking biometrics + activity, fitness outcomes can be identified

Resting HR

reduced by 10%Cardiac Efficiency

increased by 10%

VO2max

didn’t change much

HR recovery

rose & fell

©2016 Valencell. Inc

Accurate biometric sensor data can also support

accurate health assessmentsAssessment Definition What it means for fitness What it 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]

©2016 Valencell. Inc

Valencell BenchmarkTM Sensor System

• Best-in-Class PerformTekTM sensor

solution with state-of-the-art

algorithms.

• Based on flagship reference

designs, new features are first

released on this design.

• Designed with customer manufacturing

in mind.

• Ultrasonic weld rib on the lens for a

water tight seal.

• Power and Communication across a

standard 20 pin connector; I2C or

UART bus

Biometric Monitoring Design & Integration

Ear ModuleWrist Module

Operating supply

2.1V - 3.3V Vdd for sensor module and

1.8Vmcu, <2mA ave operating; 16uA

Standby current

ConnectionSolder pads on sensor; 0.4mm pitch

WLCSP

Data Interface UART or I2C options, POST, WAKE

pins

Sensor

Dimensions(11.8 x 4.7 x 5.6) mm

Sensor Weight 0.25 grams

Operating

supply

1.71 - 3.6V VDD, 3.1 – 5.0V VLED

<2.1mA average operating

current , <5uA standby current

Connector0.4mm pitch Hirose 20 pin FPC

receptacle

Data InterfaceUART or I2C options, POST,

WAKE pins

Module

Dimensions14.5 x 19.5 x 3.25 mm

Weight 0.85 grams

©2016 Valencell. Inc

Accelerate development and testing for

highly accurate wearables

• STM and Valencell have partnered to create a dev platform

for highly accurate wearables

• Combines ST’s SensorTile (www.st.com/sensortile) with

Valencell’s Benchmark optical biometric sensor system

• Kit includes everything needed to remotely sense and

measure biometric, motion, environmental and acoustical

parameters.

©2016 Valencell. Inc

Wearables dev kit features

SensorTile Development Kit for connectable sensor nodes

STEVAL-STLKT01V1

• STM32L476 – 32-bit ultra-low-power MCU with CortexM4F

• LSM6DSM – iNEMO inertial module: 3D accelerometer and

3D gyroscope

• LSM303AGR – Ultra-compact high-performance eCompass

module: ultra-low power 3D accelerometer and 3D

magnetometer

• LPS22HB – MEMS nano pressure sensor: 260-1260 hPa

absolute digital output barometer

• MP34DT04 – 64dB SNR Digital MEMS Microphone

• BlueNRG-MS – Bluetooth low energy network processor BT

4.1

• BALF-NRG-01D3 – 50 Ω balun with integrated harmonic

filter

• LD39115J18R – 150 mA low quiescent current low noise

LDO 1.8 V

• BLUEMICROSYSTEM2 STM32Cube expansion software

package, supporting different algorithms tailored to the on-

board sensors

• ST BlueMS: iOS and Android demo apps

• Compatible with STM32 ecosystem through STM32Cube

support

Included in kit package:

- Valencell BenchmarkTM sensor system integrated

to SensorTile

- 3 LED’s – 2 green, 1 yellow

- Photodetector

- STM LIS2DH accelerometer

- SMT32F401 processor

Software

- Valencell’s biometric signal processing algorithms

utilizing active signal characterization

- Valencell’s biometric assessment algorithms to

process heart rate, cardiac efficiency, VO2, RR

interval (heart rate variability), and much more.

©2016 Valencell. Inc

In Summary...

• The wearables market is exploding with opportunities

• Highly accurate optical heart rate sensor systems can support a wide variety of

use cases and form factors

• However, when designing a new product, the optomechanics, signal extraction

methodology, and clinical validation are critical

• If designed correctly, motion-tolerant OHRM can deliver a long list of insightful

biometrics that support current and future roadmap needs

Integrating Optical Heart

Rate and Biometrics Into

a Wearable Device

Ryan Kraudel

VP, Marketing

kraudel@valencell.com

919-747-3668