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Smart Health and Wellbeing Misha Pavel

National Science FoundationComputer & Information Science & Engineering Directorate

Information and Intelligent Systems Division&

Oregon Health and Science UniversityDepartment of Biomedical Engineering

Any opinion, finding, and conclusions or recommendations expressed in this material; are those of the author and do not necessarily reflect the views of

the National Science Foundation

Information and communication technologies are poised to be key

components in transforming healthcare …

preventing the onset of diseases, improving diagnoses and treatments,

enhancing the quality of health care delivery, and empowering us to participate in our own

health and well-being

Related Federal Plans and Reports• PCAST: Realizing the Full Potential of Health Information Technology to

Improve Healthcare for Americans: The Path Forward, Dec 2010

• PCAST: Designing a Digital Future: Federally Funded Research and Development in Networking and Information Technology, Dec 2010

• NRC: IOM Learning Health System Series of Reports

• ONC: Federal Health Information Technology Strategic Plan 2011-2015, Office of the National Coordinator for Health Information Technology 2011.

• National Prevention Strategy, National Prevention Council, U.S. Department of Health and Human Services, Office of the Surgeon General, 2011

• HHS: National Strategy for Quality Improvement in Health Care, U.S. Department of Health and Human Services, Interagency Working Group on Health Care Quality, 2011.

• NSTC: Trustworthy Cyberspace: Strategic Plan for the Federal Cybersecurity Research and Development Program, NSTC, 2011.

Family

Caregiver

Coach

Clinician

Devices

Use

r In

terf

aces

Infe

renc

e A

sses

smen

t

New Vision Patient-Centered Framework for Health and Wellness

Payers Employers LegalEnvironment Privacy

Self-carePatient

Physical FunctionCognitive Function

Chronic DiseaseSocialization

Physio Sensors

Activity Sensors

Mobile Sensors

EHR, PHR

Mobile Health

NIT: Networks, DB, API Software, EHR, PHR

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Some Research Challenges in Health

• Safe and secure distributed home healthcare ▫ Fool-proof application even under cognitive decline

• Mental health and cognitive decline• Behavior modification

▫ Obesity, smoking, exercise• Networked wireless cooperative medical devices• Assistive robots and prosthetics• Augmented human:

▫ Integrated sensory, cognitive and mobility assist

Smart Health Research Thrusts• Continuous accrual and integration of EHR, pharma and

clinical research data in a distributed but federated system

• A foundation for evidence-based, patient-centric practice & research

Digital Health Information

Infrastructure Informatics and Infrastructure

• Cognitive support systems spanning clinical to lay decision making

• Data mining, machine learning, discovery from massive longitudinal and individual data

Data to Knowledge to Decision

Reasoning under uncertainty

• New models of distributed and home-centered healthcare provision

• Technologies that aide in modifying self and group behavior

Empowered IndividualsEnergized, enabled,

educated

• Assistive technologies embodying computational intelligence

• Medical devices, co-robots, cognitive orthotics, rehab coaches

Sensors, Devices, and Robotics

Sensor-based actuation

Causes of Premature Mortality

7

30%

5%

15%

40%

10%

Genetic

Environmental Exposure

Social Circumstances

Behavioral

Medical Care Deficiency

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Smart Health and Wellbeing ProgramProposals

•Have the potential to transform healthcare delivery and/or improve quality of life

•Advances in at least one core scientific area ▫Engineering, e.g., sensor technology, signal

processing, optimization, complex systems analysis, etc.

▫Computer Science and Engineering, new inference algorithm, mathematical modeling,

▫Social, Behavioral and Economics, e.g. behavior change, psychology, social psychology, systems science, and others

Proposal Review Criteria

Return

Intellectual Merit

Broader Impacts

SHB Programmatic Criteria

Intellectual Merit Criteria

NSF’s Panelist System and your Reviews

▫ To what extent does the proposal suggest and explore creative, original and potentially transformative concepts?

▫ How important is the proposed activity to advancing knowledge and understanding within its own field and/or across fields?

▫ What will be the significant contribution of the project to the research and knowledge base of the field?

▫ How well conceived and organized is the proposed activity?

▫ How well qualified is the team to conduct the proposed activity?

▫ Is there sufficient access to resources; equipment, facilities, requested support (budget)?

Return

Standard NSF Evaluation Criteria: Broader Impacts

• Implicit – new knowledge, field, benefits to society

• Explicit – societal impact, technology transfer, results dissemination

• Integration of Research and Education – teaching, training, and learning

▫ Development of curriculum

▫ Development of education experiences through student involvement in emerging research and technology areas

▫  

• Broadening participation of underrepresented groups including gender, ethnicity, disability, geographic, etc.

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Return

SHB Requirements

• Impact on a key health and wellbeing problem

• Significance of the fundamental contribution to engineering, computer and information sciences, or social, behavioral and economic sciences.

• Collaboration Plan – Demonstrate that the participating investigators will work synergistically to accomplish the project objectives

• Data Management Plan – The definition of “data” may include, but not limited to data, publications, samples, physical collections, software and models

• Postdoctoral Training – A description of the mentoring activities for the postdocs including collaboration with researchers from diverse backgrounds and disciplines

Suggestions for Proposers•Find the most appropriate directorate and program•Look at the current and past funded projects•Become a reviewer•Write for the reviewers including the Project Summary•Focus on the innovative, transformative aspects of

your proposal•Double-check that your proposal has ALL the parts

required by the solicitation•Have your colleagues read it•Pay attention to details, e.g. speling•Submit it to FastLane

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spelling

Useful Website: www.nsf.gov

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A examples of currently SHB-funded projects• Predictive modeling and patient-centered detection and prediction

▫ Novel Computational Techniques for Cardiovascular Risk Stratification mHealth

▫ Assistive Cloudlet-based Mobile Computing for the Cognitively Impaired

▫ Self-care Management: Patient-Centered Diabetic Wound Care Using Smart Phones

▫ From the Ground Up -- Mobile Tools for Grassroots Programs in Public Health)

• Inference of activities and states

▫ Quantitative Observational Practice in Family Studies: The case of reactivity

• Robotics, co-robots, smart prosthetics and orthotics

▫ Socially Assistive Human-Machine Interaction for Improved Compliance and Health Outcomes

▫ An Assistive, Robotic Table [ART] Promoting Independent Living

• Social computing – empowering individuals, coaching

▫ Matchmaking for health: Facilitating Mentoring in Peer Health Communities through Social Matching

• Monitoring and Inference – home care

▫ Crafting a Human-Centric Environment to Support Human Health Needs (Cook, WU)

▫ Computational Algorithms for Predictive Health Assessment Multi-Patient Fall-Risk Monitoring in Health Care Facilities

Currently Funded Wireless by NSF Organizations

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CBET

CCF

CMMI

CNS

DBI

DMS

DUE

ECCS

IIP

IIS

OISE

SBE

0 5 10 15 20 25 30 35 40

Currently Funded mHealth by NSF Organizations

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AGS

ANT

BCS

CBET

CCF

CMMI

CNS

DEB

DMR

DUE

ECCS

IIP

IIS

OCE

OCI

OISE

SES

0 5 10 15 20 25 30 35 40

Sample of Organizational Challenges

•Organizing transdisciplinary teams▫Learn each others language▫Acculturation: Merging technology and

clinical/behavioral domains•Recognizing innovative ideas

▫Experts are frequently wrong in their prediction▫Few of us like transformative ideas when they see

them for the first time•Finding good problems and focus areas

▫Important health and wellbeing problem▫Contribution to fundamental science

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Sample of Scientific Challenges Ahead•Raw data processing and cleaning

▫Harmonizing▫Synchronizing▫Maintaining data integrity

•Computational Predictive Modeling ▫Relating observable to variables of interest▫Maximizing statistical efficiency▫Modeling individuals

•Analytic issues▫Missing data▫Big data▫Detecting anomalies▫Rapidly changing technology

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Extraction of Knowledge and MeaningHarmonizing/Coherence: Invariant Decisions

Transform

NIT (ICT) Network Layer, Databases, EHR, PHR, XHR

Decisions

Transform Transform Transform

Decisions Decisions Decisions

Heterogeneous Sources/Sensors

Adaptation, Calibration & Fusion

Gait

Sensors

Multiscale Modeling: From sensors to brain functionshould include behavioral and cognitive factors

• Unobtrusive measurement of gait characteristics

• Model relationship between the sensory inputs and gait characteristics

• Infer sensory-motor, perceptual and cognitive functions

Cognition

Perception

SensoryMotor

Inferenceof Gait Parameters

Cognition

Perception

SensoryMotor

Inferenceof Brain Function

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Missing Data:

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Missing Data: Missing Not at Random

110 120 130 140 150 160 170 180 190154

156

158

160

162

164

166

168

170

172

174

Time [Days]

We

igh

t [lb

]

Subject 2

Philips

HealthBuddy

Weight Monitoring: Congestive Heart Failure Patient

Modeling Individuals not Populations

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Speed of Dialing [#/second]

Nu

mb

er o

f E

rro

rs

S1 S2 S3 S4

Take home messages

Healthcare needs a disruptive changeWireless Technology is likely to play a key role but …

•We need to build transdisciplinary teams to focus on key health/wellbeing problems

•There us a need for more/new science•Computational modeling is needed to

▫Connect observable measures to aspects of health▫Predict and detect▫Use data efficiently

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Thank You