hassle free fitness monitoring

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Hassle Free Fitness Monitoring Hassle Free Fitness Monitoring David Jea, Jason Liu, David Jea, Jason Liu, Thomas Schmid, Mani Thomas Schmid, Mani Srivastava Srivastava

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Hassle Free Fitness Monitoring. David Jea, Jason Liu, Thomas Schmid, Mani Srivastava. Pervasive Health Care Systems. Fitness Monitoring is the most Fundamental Functionality of Pervasive Health Care Systems Provides 24X7 Fitness Monitoring Sensor devices are clipped on the body - PowerPoint PPT Presentation

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Page 1: Hassle Free Fitness Monitoring

Hassle Free Fitness MonitoringHassle Free Fitness Monitoring

David Jea, Jason Liu, David Jea, Jason Liu,

Thomas Schmid, Mani SrivastavaThomas Schmid, Mani Srivastava

Page 2: Hassle Free Fitness Monitoring

Pervasive Health Care SystemsPervasive Health Care Systems

Fitness Monitoring is the most Fundamental Functionality of Pervasive Fitness Monitoring is the most Fundamental Functionality of Pervasive Health Care SystemsHealth Care Systems

Provides 24X7 Fitness MonitoringProvides 24X7 Fitness Monitoring

Sensor devices are clipped on the bodySensor devices are clipped on the body

Proactively Record changes in vital signs such as weight and blood Proactively Record changes in vital signs such as weight and blood pressurepressure

Appropriate Medical Services provided on the basis of recorded dataAppropriate Medical Services provided on the basis of recorded data

Page 3: Hassle Free Fitness Monitoring

ChallengesChallenges

PrivacyPrivacy

SecuritySecurity

Finding a perfect balance between usability, privacy and securityFinding a perfect balance between usability, privacy and security

Page 4: Hassle Free Fitness Monitoring

ProblemsProblems

Large number of Devices hooked Large number of Devices hooked on the bodyon the body

Multiple type of sensorsMultiple type of sensors

Privacy concerns at workplacesPrivacy concerns at workplaces

Page 5: Hassle Free Fitness Monitoring

Security IssuesSecurity Issues

Network Security IssuesNetwork Security Issues

User authentication issuesUser authentication issues

Security problems related to stolen Security problems related to stolen palmtops or PDA’spalmtops or PDA’s

Page 6: Hassle Free Fitness Monitoring

The IdeaThe Idea

Build Fitness monitoring system for healthy individuals in a workplaceBuild Fitness monitoring system for healthy individuals in a workplace

Identification of the individual by only utilizing imprecise biometrics and Identification of the individual by only utilizing imprecise biometrics and existing informationexisting information

Maintaining the device’s original user interfaceMaintaining the device’s original user interface

No additional sensors incorporated in the systemNo additional sensors incorporated in the system

Page 7: Hassle Free Fitness Monitoring

Design GuidelinesDesign Guidelines

PrivacyPrivacy Recorded data cannot be used as hard evidence (in court) to Recorded data cannot be used as hard evidence (in court) to

pinpoint exactly who the user ispinpoint exactly who the user is

FeasibilityFeasibility The system is allowed to use existing informationThe system is allowed to use existing information

UsabilityUsability Restoring the original interface of the device so that people of all age Restoring the original interface of the device so that people of all age

groups know how to use itgroups know how to use it

Page 8: Hassle Free Fitness Monitoring

The DesignThe Design

Possible Candidates

Activity Information

Biometric Matcher

Context Reasoning

Imprecise Physiological

Info

Uncertainty Reduction

UserIdentity

Page 9: Hassle Free Fitness Monitoring

ImplementationImplementation

The system consists of a weight scale and a blood pressure monitorThe system consists of a weight scale and a blood pressure monitor

Both devices communicate with the laptopBoth devices communicate with the laptop

Software program installed on laptop continuously record data and attach a Software program installed on laptop continuously record data and attach a timestamp to weight and blood pressure readingstimestamp to weight and blood pressure readings

Facility for a user to input his/her name is also providedFacility for a user to input his/her name is also provided This step is to establish ground truth for the experimentThis step is to establish ground truth for the experiment

Page 10: Hassle Free Fitness Monitoring

Inference Engine ComponentsInference Engine Components

Biometric MatcherBiometric Matcher It implements a Bayes classifier that combines multiple sensor observationsIt implements a Bayes classifier that combines multiple sensor observations

It assumes that each observation is uniqueIt assumes that each observation is unique

This results in the identity of the subjectThis results in the identity of the subject

Context Reasoning Context Reasoning ItIt is based on Reified Temporal Logicis based on Reified Temporal Logic

It provides with the user’s contextIt provides with the user’s context

It uses two meta-Predicates to express when things are trueIt uses two meta-Predicates to express when things are true

Page 11: Hassle Free Fitness Monitoring

AnalysisAnalysis

UserUser Similarity in Physiological Similarity in Physiological InformationInformation

Seat in LabSeat in Lab Usage HabitUsage Habit

Weight Weight ScaleScale

BP BP MonitorMonitor

BothBoth

AA LightLight VV VV

BB They have similar weights.They have similar weights.

The differences in mean The differences in mean are less than 1.9 lbsare less than 1.9 lbs

VV VV VV

CC VV VV

DD VV VV

EE Their Difference in Their Difference in average weights is 1.1 lbsaverage weights is 1.1 lbs

VV VV

FF VV

GG Their Difference in Their Difference in average weights is 1.1 lbsaverage weights is 1.1 lbs

VV VV

HH VV VV

II HeavyHeavy VV

Page 12: Hassle Free Fitness Monitoring

Results for one Physiological InformationResults for one Physiological Information

Physiological Data for Classifier

Positive Match False Match

Weights 57.23% 45.7745.77

Systolic Blood Pressure 22.02% 77.9877.98

Diastolic Blood Pressure 43.90%43.90% 56.10%56.10%

Heartbeat Rate 25%25% 75%75%

Page 13: Hassle Free Fitness Monitoring

Results based on Multiple Sources

Biometric matcher that combines all 4

physiological sources.

Positive

Match

False

Match

Classification Results for partial or complete

data points.

77.9% 22.1%

Classification Results for complete data

points only.

87.3% 12.7%

Page 14: Hassle Free Fitness Monitoring

The accuracy of the context reasoning component

Context Reasoning Component Positive False Positive

The presence of a user based on

network activity

89.47% 10.53%

Page 15: Hassle Free Fitness Monitoring

Combining the biometric matcher with the context

reasoning.

Biometric Matcher only Biometric Matcher and Context

Reasoning

Accuracy 78.16% 83.80%

Page 16: Hassle Free Fitness Monitoring

ConclusionConclusion

Built a health monitoring system which is hassle freeBuilt a health monitoring system which is hassle free

Less privacy concernsLess privacy concerns

No extra sensors hooked on the bodyNo extra sensors hooked on the body

Easy to UseEasy to Use

Widely used by populationWidely used by population

How to handle uncertain usage?How to handle uncertain usage?