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Eldercare Research
Cognitive Computing for Aging Society
Hiro Takagi
STSM, IBM Research - Tokyo
Aging Strategic Initiative lead, IBM Research
Human Computer Interaction area lead, IBM Research
Academy of Technology member
62 87
28%
27%
Dementia 15% + MCI 13%
estimation by Japanese Government, 2012
of people over the age of 65 are
at risk of dementia.
People over the age of 65, 2017.
70%of people want to work over the
age of 70 (and forever).
Life expectancy of women in
1950 and 2015.
* numbers in Japan
2017
We need a new model for
active life-long society.
©	2016	IBM	Corporation
2003
“Elderly Vision
Simulator”
2007
Eclipse.org
Open source
2011
Official tool for
JIS (Japanese Industrial Standard)
2011
Japanese Government
Science Grant
“IT for Active Aging Society”
2009
Open Collaborative Research
University of Tokyo
“Elderly Accessibility”
2013
Japanese Government
Pilot Grant
“Remote community
collaboration”
2015
Sekisui House
JDA
2017
Japan Post Official Service
“Conversation as Sensors”
GTO 2016 Demographic Shift
2015
Japan Post
Announcement
2015 – 2016
Japan Post Pilot
“Voice QA”
2005 2010 2015 2016 2017
Tokyo Research Aging Research History
Research
Aging Strategic Initiative2014
KDDI
“Senior Smartphone”
Government and University projects Customer projects Internal activities
Power of IT – Five Long-term Focus Areas
Social
Intelligent assist
Sensing
Accessibility
Brain
Social
Intelligent assist
Sensing
Accessibility
Brain
Use case barrier
Psychological barrier
User interface
barrier
Price Barrier
Small fonts, small buttons
Don’t know how to operate
Fear, uncertainty
Cannot imagine use cases
Barriers for Senior Citizens to Start Using
Information Technologies
Target Actual
(average)
Fingertip angle + Parallax
Landed on
Took off
(px)
(px)
Touch duration + Tremor
Unintentional Motion
Accessibility: Touching a target location
Gesture Analysis for Novice Elderly Assist (2014)
Press	release	&	images (Japanese	only)
IBM	Japan	Press	Release:	http://bit.ly/1gavLuN
KDDI	R&D	Labs	Press	Release:	http://bit.ly/1hK1B2K
KDDI	Corporation	Press	Release:	http://bit.ly/1f5zbTx
Provided	appropriate	guidance	to	
users	based	on	user's	level	of	
smartphone	operation	
proficiency	(skill	and	operational	
misstep)	by	analyzing	
smartphone	operation	logs	with	
mathematical	analysis	
technology
Improved
confidence
and
subjective
operation
speed
33 0 3 -- 7 0 -6 067 ,3
-- 7
6 067 ,3
2 7 - 2 1
172 17
You entered
“one-hundred
thousand” yen
Accessibility: Voice-over Effectiveness
Social
Intelligent assist
Sensing
Accessibility
Brain
Elderly Skill Matching System – J-scouter
Senior profile
datasets
(Free-form text)
Job / Activity
Descriptions
(Free-form text)
Find best
persons
Find best
jobs/activities
A Prime minister initiative
“Work-style transformation.”
“Senior workforce” is one of
focuses.
A senior worker with rich
experience in legal compliance is
working as an advisor in a start up
company
Supported by
Japan Science and Technology Agency
Senior HR company
10,000 seniors registered
from TV BS11
By Kyodo News
“Reimagining
Life”
“Target 5 million users.”
http://www-03.ibm.com/press/us/en/pressrelease/46740.wss
2015
Japan Post Project
• Pilot with 1000 elderlies completed (Oct. 2015 – Oct. 2016)
• Medicine reminders, video phones, shopping assist, photo sharing, etc.
Video
Global Apple+IBM
Apps for Elder
Services
Support
Worker
Elder
at
Home
Family /
Loved
Ones
Social
Intelligent assist
Sensing
Accessibility
Brain
)
( )
(
-
- (-
(
( )
)
-
( -
-
-
(
Understand
ambiguous
questions
Pick up
appropriate
answers
Learn
user
feedback
- -
Video
Social
Intelligent assist
Sensing
Accessibility
Brain
IBM Accessibility Research
IoT, Health and Aging
Ecosystem Partners /
Enriched Data
Watson IoT & Health Platform
Sensors &
Devices
Client’s
Data
Personality Insights &
Social Interaction Data
Other Data Sources
Applications
Data &
Platforms
01
0110
0010
001001
Cognitive Services for Elders
Empowered Living
Empowered Social
Empowered Care
Knowledge	
Reactor
“Infrastructure
Providers”
• Voice-base natural user interface for daily watchover
• Analyze life patterns, feelings, interests and issues from daily conversation (e.g. cognitive decline detection)
• Share information with families and care givers
• Provide support that can keep the elderly self-sufficient
Conversation as Sensors
©	2014	IBM	Corporation
Video
Intent	of	Each	Questionnaire
Questionnaire Intent
“What did you have last night?” Dementia (Neuro Cognitive Disease) Risk
Assessment
“Did you go out today?” Activity checking
“You mentioned about gardening in diary. Are you
interested in community gardening?”
Recommendation of activities
”Which city do you want to travel?” Marketing
“The shop, you mentioned last week, is now on sale!” Promotion
“We delivered a package, but you were not there.
Please contact post office"
Notification (business related)
25
Emotion and Physical Condition Recognition
Voice data Features
988 acoustic features
for emotion recognition.
Intensity
Loudness
12 MFCC
Pitch (F0)
Probability of voicing, F0
envelope,
8 LSF,
Zero-Crossing Rate
Labeled
voice
dataset
ML-based
Regression
Estimation
Feeling good
or bad
40
0
100
Physical
condition
Ex: Good night
*Each circle represents one greeting.
*One participant data
Emotion
NegativePositive
Confusion FrustrationDelight Flow
Physical Condition
Emotion
Yorktown – Speech team
Tokyo Research
Happy
Sad
Dashboard for Family and Care Givers
27
Condition
Emotion (voice sound analysis)
Personality analysis (Watson
personality insights)
Daily activities
Eating habits
Dementia questionnaire scores
Dashboard Visualization Examples
28
“what did you do today?” = Variety of daily activities.
practice, songs, poems, musical instruments,
sessions, friends, music hall, …. House (largest), cleaning, washing, room,
study…..
Smaller variety and words are not so active.Wider variety, and words are active.
“what did you have today?” = Variety of nutrition
Wider variety, and healthy meals
Vegetables, salad, radish, juice, natto, miso, eggs,
….
Rice (largest), bento, sandwich, ….
Smaller variety and ready-made meals
Feature extraction of gait
• Gait speed & its variability
• Step frequency
• Stride time variability
• Step-length & its variability
• Foot swing velocity
• Stance and stride time
Detection
• Motor function
• Fall risks
• Cognitive decline
• Episodic memory
• Executive function
• Diseases
• Parkinson disease
• MCI
• Alzheimer’s disease
Gait and Cognitive Decline
Video
Social
Intelligent assist
Sensing
Accessibility
Brain
Brain Simulation: Understanding Cognitive Deficit
(2016)
Video
Power of IT – Five Long-term Focus Areas
Social
Intelligent assist
Sensing
Accessibility
Brain

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Eldercare Research: Cognitive Computing for an Aging Society

  • 1. Eldercare Research Cognitive Computing for Aging Society Hiro Takagi STSM, IBM Research - Tokyo Aging Strategic Initiative lead, IBM Research Human Computer Interaction area lead, IBM Research Academy of Technology member
  • 2. 62 87 28% 27% Dementia 15% + MCI 13% estimation by Japanese Government, 2012 of people over the age of 65 are at risk of dementia. People over the age of 65, 2017. 70%of people want to work over the age of 70 (and forever). Life expectancy of women in 1950 and 2015. * numbers in Japan
  • 4. We need a new model for active life-long society.
  • 5. © 2016 IBM Corporation 2003 “Elderly Vision Simulator” 2007 Eclipse.org Open source 2011 Official tool for JIS (Japanese Industrial Standard) 2011 Japanese Government Science Grant “IT for Active Aging Society” 2009 Open Collaborative Research University of Tokyo “Elderly Accessibility” 2013 Japanese Government Pilot Grant “Remote community collaboration” 2015 Sekisui House JDA 2017 Japan Post Official Service “Conversation as Sensors” GTO 2016 Demographic Shift 2015 Japan Post Announcement 2015 – 2016 Japan Post Pilot “Voice QA” 2005 2010 2015 2016 2017 Tokyo Research Aging Research History Research Aging Strategic Initiative2014 KDDI “Senior Smartphone” Government and University projects Customer projects Internal activities
  • 6. Power of IT – Five Long-term Focus Areas Social Intelligent assist Sensing Accessibility Brain
  • 8. Use case barrier Psychological barrier User interface barrier Price Barrier Small fonts, small buttons Don’t know how to operate Fear, uncertainty Cannot imagine use cases Barriers for Senior Citizens to Start Using Information Technologies
  • 9. Target Actual (average) Fingertip angle + Parallax Landed on Took off (px) (px) Touch duration + Tremor Unintentional Motion Accessibility: Touching a target location
  • 10. Gesture Analysis for Novice Elderly Assist (2014) Press release & images (Japanese only) IBM Japan Press Release: http://bit.ly/1gavLuN KDDI R&D Labs Press Release: http://bit.ly/1hK1B2K KDDI Corporation Press Release: http://bit.ly/1f5zbTx Provided appropriate guidance to users based on user's level of smartphone operation proficiency (skill and operational misstep) by analyzing smartphone operation logs with mathematical analysis technology
  • 11. Improved confidence and subjective operation speed 33 0 3 -- 7 0 -6 067 ,3 -- 7 6 067 ,3 2 7 - 2 1 172 17 You entered “one-hundred thousand” yen Accessibility: Voice-over Effectiveness
  • 13. Elderly Skill Matching System – J-scouter Senior profile datasets (Free-form text) Job / Activity Descriptions (Free-form text) Find best persons Find best jobs/activities A Prime minister initiative “Work-style transformation.” “Senior workforce” is one of focuses. A senior worker with rich experience in legal compliance is working as an advisor in a start up company Supported by Japan Science and Technology Agency Senior HR company 10,000 seniors registered from TV BS11 By Kyodo News
  • 14. “Reimagining Life” “Target 5 million users.” http://www-03.ibm.com/press/us/en/pressrelease/46740.wss 2015
  • 15. Japan Post Project • Pilot with 1000 elderlies completed (Oct. 2015 – Oct. 2016) • Medicine reminders, video phones, shopping assist, photo sharing, etc. Video
  • 16. Global Apple+IBM Apps for Elder Services Support Worker Elder at Home Family / Loved Ones
  • 18. ) ( ) ( - - (- ( ( ) ) - ( - - - ( Understand ambiguous questions Pick up appropriate answers Learn user feedback - -
  • 19. Video
  • 21. IBM Accessibility Research IoT, Health and Aging Ecosystem Partners / Enriched Data Watson IoT & Health Platform Sensors & Devices Client’s Data Personality Insights & Social Interaction Data Other Data Sources Applications Data & Platforms 01 0110 0010 001001 Cognitive Services for Elders Empowered Living Empowered Social Empowered Care Knowledge Reactor “Infrastructure Providers”
  • 22.
  • 23. • Voice-base natural user interface for daily watchover • Analyze life patterns, feelings, interests and issues from daily conversation (e.g. cognitive decline detection) • Share information with families and care givers • Provide support that can keep the elderly self-sufficient Conversation as Sensors
  • 25. Intent of Each Questionnaire Questionnaire Intent “What did you have last night?” Dementia (Neuro Cognitive Disease) Risk Assessment “Did you go out today?” Activity checking “You mentioned about gardening in diary. Are you interested in community gardening?” Recommendation of activities ”Which city do you want to travel?” Marketing “The shop, you mentioned last week, is now on sale!” Promotion “We delivered a package, but you were not there. Please contact post office" Notification (business related) 25
  • 26. Emotion and Physical Condition Recognition Voice data Features 988 acoustic features for emotion recognition. Intensity Loudness 12 MFCC Pitch (F0) Probability of voicing, F0 envelope, 8 LSF, Zero-Crossing Rate Labeled voice dataset ML-based Regression Estimation Feeling good or bad 40 0 100 Physical condition Ex: Good night *Each circle represents one greeting. *One participant data Emotion NegativePositive Confusion FrustrationDelight Flow Physical Condition Emotion Yorktown – Speech team Tokyo Research Happy Sad
  • 27. Dashboard for Family and Care Givers 27 Condition Emotion (voice sound analysis) Personality analysis (Watson personality insights) Daily activities Eating habits Dementia questionnaire scores
  • 28. Dashboard Visualization Examples 28 “what did you do today?” = Variety of daily activities. practice, songs, poems, musical instruments, sessions, friends, music hall, …. House (largest), cleaning, washing, room, study….. Smaller variety and words are not so active.Wider variety, and words are active. “what did you have today?” = Variety of nutrition Wider variety, and healthy meals Vegetables, salad, radish, juice, natto, miso, eggs, …. Rice (largest), bento, sandwich, …. Smaller variety and ready-made meals
  • 29. Feature extraction of gait • Gait speed & its variability • Step frequency • Stride time variability • Step-length & its variability • Foot swing velocity • Stance and stride time Detection • Motor function • Fall risks • Cognitive decline • Episodic memory • Executive function • Diseases • Parkinson disease • MCI • Alzheimer’s disease Gait and Cognitive Decline
  • 30. Video
  • 32. Brain Simulation: Understanding Cognitive Deficit (2016) Video
  • 33. Power of IT – Five Long-term Focus Areas Social Intelligent assist Sensing Accessibility Brain