Nuria Oliver, PhD Researcher Microsoft Research. 2 New opportunities for wearable health and...

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Nuria Oliver, PhD Researcher Microsoft Research

Transcript of Nuria Oliver, PhD Researcher Microsoft Research. 2 New opportunities for wearable health and...

Page 1: Nuria Oliver, PhD Researcher Microsoft Research. 2 New opportunities for wearable health and wellness continuous monitoring devices.

Nuria Oliver, PhDResearcherMicrosoft Research

Page 2: Nuria Oliver, PhD Researcher Microsoft Research. 2 New opportunities for wearable health and wellness continuous monitoring devices.

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New opportunities for wearablehealth and wellness

continuous monitoring devices

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Zillions of gadgets to monitor various physiological and environmental signalsTypically proprietary data transmission protocols Typically capture on-board and off-line processing of the data after downloading to a PCVery difficult if not impossible to combine signals from different gadgetsLack of real-time on-board processing of the information to deliver value to the user

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Continuous monitoring and understanding of multiple physiological and environmental signalsFinding correlations between lifestyle and wellness/healthIdentifying trends and deviations from those trendsDeveloping new interesting and fun applicationsEmpowering users

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Audiovox 5600 GSM mobile phone

Alivetec Alive ECG and

Accelerometer sensorBlood oximeter

HealthGear MPTrain

Automatically Monitor and Detect Sleep Apnea Events Music and Physiology-based

Personal Trainer

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Real-time, wearable physiological monitoring system on a mobile phonePhysiological sensors wirelessly connected via Bluetooth to a mobile phoneContinuous recording of blood oximetry, heart-rate and plethysmographic signalReal-time analysis and presentation of physiological data to the userUsage scenario: Sleep monitoring and automatic sleep apnea detection

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Underdiagnosed but common conditionAffects children and adults4% in men and 2% in women (higher for elderly)Untreated causes $3.4 billion of medical costs40 million undiagnosed Americans

Periods of interrupted breathing (apnea) and periods of reduced breathing (hypoapnea)Leads to

Hypoxia, asphyxia and awakeningsIncreased heart-rate, high blood pressureExtreme fatigue, poor concentrationCompromised immune systemCardio/cerebrovascular problems

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Nocturnal Polysomnography (PSG)In sleep center for 1-2 nightsContinuous, simultaneous multi-channel measurements of 8 physiological signals Very expensive, cumbersome, time consuming, just one sample and subject to manual scoring and human error

Pulse oximetry Useful as screening toolOne simple, light-weight sensor on finger, toe or earlobe

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20 volunteers80% male, ages 25-6530% healthy, 70% with sleep apnea or suspected

Filled out pre-sleep and post-sleep questionnairesWore HealthGear for one or two full nights in their own homes

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3 long-term (2-3 weeks at a time) sleep studies1 long-term (2.5 months) study with MIT’s PlaceLabInvestigated correlations between quality of sleep and lifestyle factors

Alcohol and caffeine intakeDietExerciseStress levels

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New hardware board!!More long-term sleep studies(MIT, Univ. Virginia)Study on drivers that have apnea (Univ. Iowa)Study on aircraft pilotsSummits of Canada expedition

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Audiovox 5600 GSM mobile phone

Alivetec Alive ECG and

Accelerometer sensor

HealthGear MPTrain

Automatically Monitor and Detect Sleep Apnea Events Music and Physiology-based

Personal Trainer

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Music ProvidesPacing AdvantageDistractionPositive Mood

Music Positively ImpactsEndurancePerformance PerceptionExertion Perception

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Target HR zones recovery, weight management, aerobic,anaerobic, over-exertion

Used to measure effort

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PHR reserve =(maxHR - restHR)*P + PHR reserve =(maxHR - restHR)*P + restHRrestHR

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Next Action Module

BPM(t) = Current Heart BPM(t) = Current Heart raterate

SPM(t) = Current paceSPM(t) = Current pace

DBPDBPM(t)M(t)

>0

>0

<0

Slow Slow down down useruser

Keep Keep same same speedspeed

Speed Speed up up

useruserDBPM(t) = DBPM(t) = BPM(t) – Ideal BPM(t)BPM(t) – Ideal BPM(t)

Sensor data (Bluetooth)

Feedback (Music)

Transceiver Mobile phone

Sensors

Digital MusicDatabase

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Runner study with 18 runners to test a few new features of the system

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Real-time collection and analysis of physiological and environmental signals on a mobile phone (Smartphone)Big opportunity for

Constant monitoring of usersReal-time feedback to usersFinding correlations between lifestyle and health/wellnessIdentifying trends and deviations from those trendsNew applications and services 25

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High impact on the societyImproving Quality of Life of UsersAging, chronic disease management, exercise, wellness, entertainment, affective and social computing, disease prevention, pro-active medicine, stress reduction, etc..

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More [email protected]://research.microsoft.com/~nuria/healthGear/healthGear.htmhttp://research.microsoft.com/~nuria/MPTrain/MPTrain.htm

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© 2007 Microsoft Corporation. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.

The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after

the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

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Microsoft Research Faculty Summit 2007