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DERIVING MEANING FROM
WEARABLE SENSOR DATA
SAMEERA PODURI
@sameerapoduri
1530 pocket watch
wrist watch1810
digital watch1969
1530 pocket watch
wrist watch1810
digital watch1969
mobile phone1973
smartphone2008
2016 ?
• batteries shrinking
• small + low-power sensors, compute, comms
24/7 sensor data platforms!
DATA SCIENCE FOR WEARABLES:
PERCEPTION & PERSONALIZATION
• Hardware is maturing
• Sensor data is growing exponentially
• Unlocking potential requires deriving meaning from data
BEAUTY + ENGINEERING IN SERVICE OF A BETTER LIFE
Measure steps, sleep states, workouts, heart rate
DynamoDB
Kinesis
Eventing Data
JB server
User Data
Platform
Redshift
Processing
DATA INFRASTRUCTURE
DETECTING ACTIVITY & SLEEP
PEDOMETER
PEDOMETER
theory
real data
GOT DATA?
1. Deploy a model
2. Collect data
3. Retrain model
4. A/B Test
5. Repeat
PEDOMETER
Classifier
SLEEP DETECTION
SIGNALS Raw, rich Partly compressed, rich Compressed
CONTEXT Limited Sensor fusion
History, population,
weather, etc
USERS Single Single Aggregate
WHERE TO DEPLOY?
DATA PRODUCTS FOR HARDWARE
LATENCY Seconds Minutes
Minutes
+ Network delays
COMPUTE Limited Powerful
DEPLOYMENT Months Weeks Hours
WHERE TO DEPLOY?
Version 0
Most common workout 58% Accuracy
Version 1
Last workout 15% lift
Version 2
WORKOUT CLASSIFICATION
PERSONALIZED INSIGHTS
• How can I understand this data?
• How should I feel about what it tells me?
• What action should I take in response?
Smart Coach Remembers
Remember how you took 45,365 steps on July 4?
Smart Coach remembers! On your health journey,
don't forget to stop and celebrate.
Step Update
Smart Coach noticed a surge in activity. In fact,
you surpassed 9,690 steps, your typical
5:00pm average.
Last night you had 35m of REM sleep, less than
the 1h9m that is typical for your age group. One
way to improve your chances for more REM is to
try an earlier bedtime than last night's 12:35am.
You can set a bedtime Reminder for 11:35pm to
help.
REM TimeLong Journey?
Looks like you've been traveling recently, which
can throw off your routine. Try setting a bedtime
reminder for tonight to help you adjust.
Your daily average of 17,543 steps places you
in the top 3% of UP females in their 30s.
Bravo, Angela.
Welcome to the 3%
DynamoDB Redshift
User Facts
Insights
HEART RATE
“Your heart rate is 85 beats per minute.”
CONTEXT MATTERS
This morning’s resting heart rate was higher
than 61bpm, your 30-day average.
Dehydration may be the cause. If you think
you were dehydrated last night, make up for
it today with 8 glasses of water.
Start with Hydration
BEHAVIOR CHANGE
BEHAVIOR CHANGE
Commitment and
Consistency
Source: Cialdini, R. B. (2009). Influence: Science and
practice (5th edition). Boston, MA: Pearson Education.
BEHAVIOR CHANGE
Commitment and
Consistency
Foot In The Door
Technique
Source: Freedman, J.L. & Fraser, S.C. (1966). Compliance
without pressure: The foot-in-the-door technique. Journal of
Personality and Social Psychology, 4, 195-202.
BEHAVIOR CHANGE
Commitment and
Consistency
Foot In The Door
Technique
Goldilocks Tasks
Source: Pink, Daniel (2009). Drive: The Surprising Truth
About What Motivates Us. New York, NY: Riverhead Books.
BEHAVIOR CHANGE
Commitment and
Consistency
Foot In The Door
Technique
Goldilocks Tasks
Source: Carpenter, Chris. (2013) A meta-analysis of the
effectiveness of the "but you are free" compliance-gaining
technique
Reactance
BEHAVIOR CHANGE
72%Increased likelihood to go to
bed early enough to hit their
sleep goal
23mMinutes earlier to bed,
compared to if they didn’t
receive a TIW
BEHAVIOR CHANGE
DATA STORIES
HUNDREDS OF MILLIONS
NIGHTS OF SLEEP
TRILLIONS OF
STEPS
HUNDREDS OF MILLIONS
FOOD ITEMS
“The fact that the tracker
measured my sleep and my
activity level was a big part of
my recovery. I had this way to
‘metric’ my body as I went
through this. Sleep is so
important in brain function
anyway, and when you're
recovering from a brain injury,
it's even more important.”
PARTING THOUGHTS…
• Wearables will help us live healthier
• Health data at unprecedented scale and granularity
• Data Science can play a critical role in unlocking their potential
by deriving meaning from this sensor data
• Sensor and Accelerometer data

• > 1GB/sec aggregated across users

• Compacted on band into code-words
UP Band Phone
{
steps: 12,
hr: 78,
ts: 1455741797
…..
….
}
• Phone adds context to band signals 

• Collects eventing and logging data from app

• Eventing/Logging passes through Kinesis 

• User data is stored in the appropriate DB
Kinesis
Eventing Data
JB server
User Data
Phone Server
Platform
• Run batch ETL jobs using
Elastic MapReduce to
clean and process data.

• Choose the appropriate
processing framework
depending on type of job
(Hadoop/Spark)

• Store cleaned and
anonymized data in
Redshift.
Server Warehouse
Kinesis
Platform
Redshift
Processing
Aggregations
New tables of
interest
ETL Pipeline
Analyze Fields
Redshift
Add columns
Load
Kinesis
Extract
Aggregations
New tables
of interest
Transform
Create config
ANALYSIS AND EXPLORATION
WEARABLES FOR BETTER HEALTH
Chronic disease care is 86% of US healthcare cost
• Diabetes affects 12.3% population, costs $245B
• Obesity affects 36% population, costs

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DataEngConf SF16 - Deriving Meaning from Wearable Sensor Data

  • 1. DERIVING MEANING FROM WEARABLE SENSOR DATA SAMEERA PODURI @sameerapoduri
  • 2. 1530 pocket watch wrist watch1810 digital watch1969
  • 3. 1530 pocket watch wrist watch1810 digital watch1969 mobile phone1973 smartphone2008 2016 ?
  • 4. • batteries shrinking • small + low-power sensors, compute, comms
  • 5. 24/7 sensor data platforms!
  • 6. DATA SCIENCE FOR WEARABLES: PERCEPTION & PERSONALIZATION • Hardware is maturing • Sensor data is growing exponentially • Unlocking potential requires deriving meaning from data
  • 7.
  • 8. BEAUTY + ENGINEERING IN SERVICE OF A BETTER LIFE Measure steps, sleep states, workouts, heart rate
  • 9. DynamoDB Kinesis Eventing Data JB server User Data Platform Redshift Processing DATA INFRASTRUCTURE
  • 13. GOT DATA? 1. Deploy a model 2. Collect data 3. Retrain model 4. A/B Test 5. Repeat
  • 16. SIGNALS Raw, rich Partly compressed, rich Compressed CONTEXT Limited Sensor fusion History, population, weather, etc USERS Single Single Aggregate WHERE TO DEPLOY?
  • 17. DATA PRODUCTS FOR HARDWARE
  • 18. LATENCY Seconds Minutes Minutes + Network delays COMPUTE Limited Powerful DEPLOYMENT Months Weeks Hours WHERE TO DEPLOY?
  • 19. Version 0 Most common workout 58% Accuracy Version 1 Last workout 15% lift Version 2 WORKOUT CLASSIFICATION
  • 21. • How can I understand this data? • How should I feel about what it tells me? • What action should I take in response?
  • 22. Smart Coach Remembers Remember how you took 45,365 steps on July 4? Smart Coach remembers! On your health journey, don't forget to stop and celebrate. Step Update Smart Coach noticed a surge in activity. In fact, you surpassed 9,690 steps, your typical 5:00pm average. Last night you had 35m of REM sleep, less than the 1h9m that is typical for your age group. One way to improve your chances for more REM is to try an earlier bedtime than last night's 12:35am. You can set a bedtime Reminder for 11:35pm to help. REM TimeLong Journey? Looks like you've been traveling recently, which can throw off your routine. Try setting a bedtime reminder for tonight to help you adjust. Your daily average of 17,543 steps places you in the top 3% of UP females in their 30s. Bravo, Angela. Welcome to the 3%
  • 24. HEART RATE “Your heart rate is 85 beats per minute.”
  • 26.
  • 27.
  • 28.
  • 29. This morning’s resting heart rate was higher than 61bpm, your 30-day average. Dehydration may be the cause. If you think you were dehydrated last night, make up for it today with 8 glasses of water. Start with Hydration
  • 32. Commitment and Consistency Source: Cialdini, R. B. (2009). Influence: Science and practice (5th edition). Boston, MA: Pearson Education. BEHAVIOR CHANGE
  • 33. Commitment and Consistency Foot In The Door Technique Source: Freedman, J.L. & Fraser, S.C. (1966). Compliance without pressure: The foot-in-the-door technique. Journal of Personality and Social Psychology, 4, 195-202. BEHAVIOR CHANGE
  • 34. Commitment and Consistency Foot In The Door Technique Goldilocks Tasks Source: Pink, Daniel (2009). Drive: The Surprising Truth About What Motivates Us. New York, NY: Riverhead Books. BEHAVIOR CHANGE
  • 35. Commitment and Consistency Foot In The Door Technique Goldilocks Tasks Source: Carpenter, Chris. (2013) A meta-analysis of the effectiveness of the "but you are free" compliance-gaining technique Reactance BEHAVIOR CHANGE
  • 36. 72%Increased likelihood to go to bed early enough to hit their sleep goal 23mMinutes earlier to bed, compared to if they didn’t receive a TIW BEHAVIOR CHANGE
  • 38. HUNDREDS OF MILLIONS NIGHTS OF SLEEP TRILLIONS OF STEPS HUNDREDS OF MILLIONS FOOD ITEMS
  • 39.
  • 40.
  • 41.
  • 42.
  • 43. “The fact that the tracker measured my sleep and my activity level was a big part of my recovery. I had this way to ‘metric’ my body as I went through this. Sleep is so important in brain function anyway, and when you're recovering from a brain injury, it's even more important.”
  • 44.
  • 45.
  • 46.
  • 47. PARTING THOUGHTS… • Wearables will help us live healthier • Health data at unprecedented scale and granularity • Data Science can play a critical role in unlocking their potential by deriving meaning from this sensor data
  • 48.
  • 49.
  • 50.
  • 51.
  • 52. • Sensor and Accelerometer data • > 1GB/sec aggregated across users • Compacted on band into code-words UP Band Phone { steps: 12, hr: 78, ts: 1455741797 ….. …. }
  • 53. • Phone adds context to band signals • Collects eventing and logging data from app • Eventing/Logging passes through Kinesis • User data is stored in the appropriate DB Kinesis Eventing Data JB server User Data Phone Server Platform
  • 54. • Run batch ETL jobs using Elastic MapReduce to clean and process data. • Choose the appropriate processing framework depending on type of job (Hadoop/Spark) • Store cleaned and anonymized data in Redshift. Server Warehouse Kinesis Platform Redshift Processing Aggregations New tables of interest
  • 55. ETL Pipeline Analyze Fields Redshift Add columns Load Kinesis Extract Aggregations New tables of interest Transform Create config
  • 57. WEARABLES FOR BETTER HEALTH Chronic disease care is 86% of US healthcare cost • Diabetes affects 12.3% population, costs $245B • Obesity affects 36% population, costs
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