The document discusses aging in place technologies and summarizes several National Science Foundation (NSF) and National Institutes of Health (NIH) funded projects in this area. It notes that the US population is aging, with 25% over age 55, and the census predicts a 71% increase in those over 60 by 2020. NSF and NIH are collaborating through programs like the Smart and Connected Health Inter-Agency program to fund research developing technologies that allow older adults to live independently at home and age in place. Several example projects are described that create assistive robots, smart home sensors for health monitoring, and socially assistive technologies like exercise coaches.

1. Wendy Nilsen, PhD
Program Director, Smart and
Connected Health
CISE/NSF
AGING IN PLACE
NRI PI WORKSHOP

2. Aging in the United States
From the US Census

3. Aging in Place is described as
technologies to assist older adults and
people with chronic diseases to live
independently. The US is aging (25%
over age 55) and the census predicts a
71% spike in the number of adults over
age 60 by 2020.
Assess the state of aging in place
technologies and identify challenges in
the development and application of
technologies for in-home care.
2014 Workshop Sponsored by:
• National Institutes of Health (host)
• Computer Research Association (sponsor)
• National Science Foundation (collaborator)
BACKGROUND

4. Aging in Place concept originally
conceived based on the idea that
technology could be enhance
health outside of hospitals and
nursing homes.
•Improve and sustain health and increase
the quality of life
•Allow people to live at home longer
•Reduce healthcare costs:
Hospitalizations/rehospitalizations
•Reduce strain on the healthcare
workforce
•Reduce caregiver burden
DRIVERS

5. Personalization and Adaptation
•Recognizing that multiple approaches
are needed to address needs of people
who are most ill, managing chronic
diseases and sustaining health and
wellness.
•Creating more personalized technology
to serve diverse populations, while
creating evidence-based, generalizable
solutions from which to adapt.
•Creating solutions with the principles of
‘future’ proofing.
•Designing technologies to empower
patient, caregivers and providers with
timely and actionable information.
•Ensuring technology does not create a
‘digital’ divide or disadvantages among
groups.
PERSONALIZATION
& ADAPTATION

6. Evidence
• Validating the effectiveness and
reliability of technologies by
developing methods of rapidly
generate evidence.
• Developing ‘testbeds’ to
efficiently, economically and
systematically explore the use of
technologies and involve the
community in the research.
• Thinking about technologies more
broadly.
•Creating new robust methods of
analysis and sensing-driven
decision analysis to create
predictive, personalized models of
health.
EVIDENCE

7. Changing Cultures
•Organizing opportunities for the various
disciplines to transform aging in place
from translation of home health care to
smart homes that support health.
•Changing the current mind-set so that
technology in the home is an alternative
to care and not just an add-on to care.
• Change the disciplinary lens that that
describes technology researchers as
technicians and researchers as clinicians.
•Ensuring we do not develop a “health
care at home” system.
CHANGING
CULTURE

8. NSF Solicitation: NSF-13-543
NIH Notice Number: NOT-OD-13-041
SMART & CONNECTED
HEALTH
INTER-AGENCY PROGRAM
NATIONAL SCIENCE
FOUNDATION/
NATIONAL INSTITUTES OF
HEALTH

9. Clinic-based
Data
Patient-based
Data
Exchange
Health
care
System
Medical
Team
Decision
Support
Needs
Patient data
• Concerns
• Patient Reported Outcomes
• Risk modeling
• Diagnostic support
• Treatment selection
• Guideline adherence
• Error detection/correction
• Situational awareness
• Population health
• Continuity of care
• Identify side effects
• Inform discovery
Clinic/sensor data
• Clinical measures
• Laboratory findings
• Sensor data
Assessment
• Diagnosis
• Categorical reporting
• Prognosis/Trajectory
Plan
• Treatment planning
• Self-care planning
• Post treatment
• Community
• Surveillance
Patient &
Family
Smart and Connected Health:
People, Technology, Process
Medical
Researcher
Community

10. Smart & Connected Health
Joint National Science Foundation/National Institutes of Health Initiative
•Integration of EHR, clinical and patient data
•Access to information, data harmonization
•Semantic representation, fusion, visualization
Digital Health
Infrastructure
Informatics and Infrastructure
•Data-mining and machine learning
•Inference, cognitive decision support system
•Bring raw image data to clinical practice
Data to Knowledge to
Decision
Reasoning under uncertainty
•Systems for empowering patient
•Models of readiness to change
•State assessment from images video
Empowered Individuals
Energized, enabled,
educated
•Assistive technologies embodying computational intelligence
•Medical devices, co-robots, cognitive orthotics, rehab coaches
Sensors, Devices, and
Robotics
Sensor-based actuation

11. SCH EXP: Collaborative Research:
A Formalism for Customizing the Control of Assistive Machines
Technical Approach:
•A formalism that customizes how users share control with
intelligent autonomous assistive devices, based on user ability
and preference.
•Customization to the user and task, and based on the
confidence that the user's goal has been predicted correctly.
•Customization by the autonomy and by the user.
Brenna Argall, Northwestern University
Siddhartha Srinivasa, Carnegie Mellon University
NSF Grant # 1R01EB019335-01
Motivation:
For those with severe upper limb motor impairments,
caregivers are still relied on for manipulation tasks like meal
preparation or personal hygiene.
Robotic arms hold much promise, however traditional
devices for teleoperation like joysticks become tedious or
untenable to control these higher degrees of freedom systems.
Transformative:
•Customizable and intuitive control, currently unavailable out-
of-the-box on any commercial assistive arms.
•Broad and rapid dissemination via simple interfacing with
control devices already used to drive powered wheelchairs.
Broader Impacts:
•Increasing the independence of those with motor
impairments and/or paralysis.
•National Robotics Week exhibit at the Museum of
Science & Industry in Chicago.
•Industrial collaboration plan with Kinova Robotics.
Contacts:
•PI Brenna Argall, Northwestern University
and the Rehabilitation Institute of Chicago
•PI Siddartha Srinivasa, Carnegie Mellon University
Progress:
•Year 1 will develop the technical components.
•In subsequent years user studies with high Spinal Cord
Injury subjects will evaluate the importance of customizing
the control sharing function, the autonomy behaviors and
confidence measures.
Customiziation of control sharing
functions to the user (U) and task (T)

13. Crafting a Human-Centric Environment to Support Human Health Needs
Technical Approach:
• We perform real-time activity recognition
smart home sensor data “out of the box”
• Machine learning techniques map activity
parameters to assessment values
• Activity forecasting drives
activity prompting intervention
Diane J. Cook and Sajal K. Das
Washington State University
NSF Grant #I1064628
Motivation:
 Design smart environment technologies to perform
automated health assessment and intervention
Transformative:
• Our team combines expertise from machine learning,
pervasive computing, and clinical neuropsychology
• We are designing and clinically validating methods to
perform automated functional assessment and intervention
Broader Impacts:
• Data collected in the smart homes is cleaned,
anonymized, visualized, and disseminated
• Half of the students and faculty involved in this
project are women or from underrepresented groups
• Research was integrated into a multi-disciplinary
Gerontechnology class
Contacts:
• Diane J. Cook
Washington State University, cook@eecs.wsu.edu
• Sajal K. Das
Missouri S&T, sdas@mit.edu
• http://ailab.wsu.edu/casas
Progress:
• We collected sensor data in 40 homes with older adults
• We observe a statistically significant correlation (r=0.79)
using supervised machine learning and (r=0.57) using
unsupervised learning between smart home sensor and
clinical scores for n=179 older adult participants.

14. Socially Assistive Human-Machine Interaction for Improved Compliance and Health Outcomes
Technical Approach:
• Affective feedback, praise, encouragement, and
relationship building in SAR exercise coach and buddy
systems
• Personalization of motivational character backstory
• Use of deviation (cheating) detection for user engagement
PI: Maja J Matarić,
University of Southern California,
NSF Grant #1117279
Motivation:
Our approach is focused on socially assistive robotics (SAR)
and is motivated the following domains:
 Poststroke rehabilitation
 Physical and cognitive exercise for older adults
 General exercise encouragement
Transformative:
•Design principles for SARbased therapeutic interventions
•Statistically significant large-scale study demonstrating
preferences of physical robots over screen-based coaches
•Insights regarding the impact of agent embodiment on user
engagement in human-robot interaction contexts
•Novel methods for autonomous exercise coaching and
encouragement
Broader Impacts:
• Promoting wellness and longevity in the aging
population
• Implementing and testing real-world socially
assistive robots (SAR)
• K-12 outreach activities: annual open house and
robotics workshops for students and educators,
impacting over 2000 K-12 students each year
Contacts:
•Principal Investigator: Maja J Matarić
•Partners: Rancho Los Amigos National Rehabilitation
Center, be.group
•Project URL:
http://robotics.usc.edu/interaction/?l=Research:Projects:well
ness:index
Progress:
•Evaluated SAR exercise system for older adults and
developed spatial language framework for natural language
interaction with older adults
•Evaluated effect of socialcomparative feedback given by a
SAR in the post-stroke domain
•Evaluating SAR exercise buddy system for overweight and
obese youth

15. Collaborative Aging (in Place)
Research Using Technology
(CART) (U2C)
NIH RFA-16-021
THE PURPOSE OF THIS, INTER-AGENCY
FUNDING OPPORTUNITY ANNOUNCEMENT IS
TO DEVELOP AND VALIDATE THE
INFRASTRUCTURE FOR RAPID AND
EFFECTIVE CONDUCT OF FUTURE RESEARCH
UTILIZING TECHNOLOGY TO FACILITATE
AGING IN PLACE, WITH A SPECIAL EMPHASIS
ON PEOPLE FROM UNDERREPRESENTED
GROUPS.

16. Wendy Nilsen
Telephone: 703-292-2568
Email: wnilsen@nsf.gov
THANK YOU!