The University of Tokyo, School of Engineering Living Environment Laboratory Assistant Professor Guillaume Lopez
New Healthcare Society Supported by Wearable Sensors and - - PowerPoint PPT Presentation
New Healthcare Society Supported by Wearable Sensors and - - PowerPoint PPT Presentation
New Healthcare Society Supported by Wearable Sensors and Information Mapping based Services Technology for Technology for Collection, Transmission, and Exploitation Collection, Transmission, and Exploitation The University of
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PROJECT sponsored by JST/CREST
Core Research for Evolutional Science and Technology Core Research for Evolutional Science and Technology ☆ ☆
(strategic research fund) (strategic research fund)
- Field
Field: : A Advanced dvanced Integrated Integrated Sensing Technologies Sensing Technologies
- Theme
Theme:「 :「Development of a P
Development of a Phys hysiological and Environmental Information iological and Environmental Information Processing Platform, and its Application to the Processing Platform, and its Application to the Metabolic Syndrome Metabolic Syndrome Measures Measures」
」
- Project Leader
Project Leader: :Prof.
- Prof. I.
- I. YAMADA
YAMADA The University of Tokyo The University of Tokyo
- Members
Members
– – U. Tokyo (Eng.)
- U. Tokyo (Eng.):
: S. Warisawa, M. Shuzo, G. Lopez – – U. Tokyo (Med.)
- U. Tokyo (Med.) :
: N. Yahagi, Y. Imai, S. Yanagimoto – – U. Tokyo (
- U. Tokyo (Psy
Psy.) .) : : K. Yokosawa, M. Asano – – Olympus Olympus: : Y. Iba, A. Kosaka, S. Tatsuta – – NTT NTT: :J. Nakamura, M. Nakamura – – U. Tokyo (RCAST)
- U. Tokyo (RCAST) :
: H. Morikawa, M. Minami, Y. Kawahara
- Period
Period: :2007 2007.10 .10~ ~2013 2013.3 .3
Since March 2009
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Research Plan
1. 1. Backgrounds & Focus Backgrounds & Focus 2. 2. Health Information Processing Platform Health Information Processing Platform
a.
Architecture for collection and storage
- New possibilities from
New possibilities from wearable sensing wearable sensing b.
Information system for data accumulation and sharing
- Unification of usual medical & health
Unification of usual medical & health-
- related information
related information
- Meta
Meta-
- Database
Database for information description & sharing for information description & sharing c.
Practical use of accumulated data
- Analysis Technologies (signal analysis, Data
Analysis Technologies (signal analysis, Data-
- mining)
mining)
- User Interface
User Interface for adapted information representation for adapted information representation
3. 3. Healthcare Services Healthcare Services
a.
Image of the type of healthcare services
- Disease
Disease prevention prevention support services support services
- Improved quality
Improved quality treatment treatment of lifestyle diseases
- f lifestyle diseases
- Health education events support services
Health education events support services
- Virtual healthcare communities
Virtual healthcare communities for motivation keeping for motivation keeping b. b.
Field Experiments w/ healthcare Field Experiments w/ healthcare-
- related partner organizations
related partner organizations
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- Int. Workshop on Web Intelligence & Virtual Enterprises --
- Guillaume Lopez
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Research Plan
1. 1. Backgrounds & Focus Backgrounds & Focus 2. 2. Health Information Processing Platform Health Information Processing Platform
a.
Architecture for collection and storage
- New possibilities from wearable sensing
New possibilities from wearable sensing b.
Information system for data accumulation and sharing
- Unification of usual medical & health
Unification of usual medical & health-
- related information
related information
- Meta
Meta-
- Database for information description & sharing
Database for information description & sharing c.
Practical use of accumulated data
- Analysis Technologies (signal analysis, Data
Analysis Technologies (signal analysis, Data-
- mining)
mining)
- User Interface for adapted information representation
User Interface for adapted information representation
3. 3. Healthcare Services Healthcare Services
a.
Image of the type of healthcare services
- Disease prevention support services
Disease prevention support services
- Improved quality treatment of lifestyle diseases
Improved quality treatment of lifestyle diseases
- Health education events support services
Health education events support services
- Virtual healthcare communities for motivation keeping
Virtual healthcare communities for motivation keeping b. b.
Field Experiments w/ healthcare Field Experiments w/ healthcare-
- related partner organizations
related partner organizations
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- Int. Workshop on Web Intelligence & Virtual Enterprises --
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- 1. Increasing patients w/ lifestyle-related disease
- 1. Increasing patients w/ lifestyle-related disease
◇ Government appealing to citizens on preserving health ◇ Company managing and encouraging employees’ health
- 2. Growing awareness and interest in healthcare
- 2. Growing awareness and interest in healthcare
◇
“Myself Health”, “Family Members’ Health”, get the 2nd and 3rd position for 3 consecutive years in public opinion polls about daily life worry and anxiety.
- 3. Information on each individual’s health, is straggling in various places
- 3. Information on each individual’s health, is straggling in various places
◇ All these health information should be available in a unified way for
management and practical use by individual’s intention.
Growing demand for a new organization of the whole medical system that would support daily health management Growing demand for a new organization of the whole Growing demand for a new organization of the whole medical system that would support medical system that would support daily health daily health management management
Social Background & Trend
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Healthy Life Prevention of Lifestyle-related Disease Community Clinic
Health Management Health Management & & Preventive Medicine Preventive Medicine Residential Nursing Emergency Care
Skilled Nursing Facility Nursing Home Specialized Hospital Regional Hospital ICU 1 10 100 1,000 10,000
Cost per Day (US$) Quality of Life
Low High
Cost / QoL Evaluation
In JAPAN
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Not yet implemented
Medical Services’ Evolution w/ IT
Wearable Sensors (tiny & light) Designed for home use (Portable) Any (Big)
Medical Devices Available (size)
health management (lifestyle support) Nursing prevention (elderly) basic ~ high-risk patients
Care Level
Anytime, Anywhere Any individual’s home Limited to Medical Organizations
Care place
High (preventive medicine) Medium (regular monitoring) Low (treatment medicine)
Cost / Performance Ubiquitous Health Monitoring Home Care Treatment at Medical Organizations Treatment Type
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Technological Process Outline
Representation Representation Healthcare Services Healthcare Services Accumulation Accumulation & Sharing & Sharing Network Organization Network Organization for Healthcare for Healthcare Wearable Biological Wearable Biological and Environmental and Environmental Sensing Sensing Users Physical / Data-link Network / Transport Internet Presentation Application Field Field Experiments Experiments
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20 20’ ’s s 30 30’ ’s s 40 40’ ’s s 50 50’ ’s s 60 60’ ’s s 70 70’ ’s~ s~
Lifestyle-related Disease: Metabolic Syndrome
(Ministry of Health, (Ministry of Health, Labour Labour and Welfare and Welfare investigation in 2004) investigation in 2004)
More than half of More than half of middle and old age men middle and old age men
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Bio-Env Information and Metabolic Syndrome
Metabolic Syndrome
H Heart disease eart disease, , Cerebrovascular disease, Cerebrovascular disease, Diabetes Diabetes… …
(30% of Japanese’s cause of death)
Irregular lifestyle ・Lack of exercise ・Stress ・Irregular meal ・Lack of sleep
Hypertension in Japan Hypertension in Japan for over 30 for over 30’ ’s: s:
- man 51.7% ,
man 51.7% ,
- women 39.7%
women 39.7%
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Guillaume Lopez 11 11 2009/10/16 生体・環境情報処理基盤の開発とメタボリック症候群対策への応用
- とる・ためる・みる技術
- 11
Detailed Process Image
Representation Representation Healthcare Services Healthcare Services Accumulation Accumulation & Sharing & Sharing Network Organization Network Organization for Healthcare for Healthcare Wearable Biological Wearable Biological and Environmental and Environmental Sensing Sensing Users Presentation Technology Based on Presentation Technology Based on Psychological Approach Psychological Approach ○○ ○○-
- type
type Blood Pressure Blood Pressure sensor sensor ○○ ○○-
- type
type Eating Habits Eating Habits sensor sensor ○○ ○○-
- type
type Stress Level Stress Level sensor sensor UT UT Hospital Hospital Bio Bio-
- Env
Env Info Accumulation & Sharing System Info Accumulation & Sharing System w/ High Level Security and Quality w/ High Level Security and Quality Wake Wake-
- up Wireless Interface
up Wireless Interface Data Data-
- sets
sets Provision Provision Healthcare Healthcare Partnerships Partnerships Multi Multi-
- Sensor Network Organization
Sensor Network Organization Next Important Issues Next Important Issues Issues Issues in Progress in Progress Give Targets Technological Issues Technological Issues Global Organization Global Organization Field Field Experiments Experiments
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Research Plan
1. 1. Backgrounds & Focus Backgrounds & Focus 2. 2. Health Information Processing Platform Health Information Processing Platform
a.
Architecture for collection and storage
- New possibilities from
New possibilities from wearable sensing wearable sensing b.
Information system for data accumulation and sharing
- Unification of usual medical & health
Unification of usual medical & health-
- related information
related information
- Meta
Meta-
- Database for information description & sharing
Database for information description & sharing c.
Practical use of accumulated data
- Analysis Technologies (signal analysis, Data
Analysis Technologies (signal analysis, Data-
- mining)
mining)
- User Interface for adapted information representation
User Interface for adapted information representation
3. 3. Healthcare Services Healthcare Services
a.
Image of the type of healthcare services
- Disease prevention support services
Disease prevention support services
- Improved quality treatment of lifestyle diseases
Improved quality treatment of lifestyle diseases
- Health education events support services
Health education events support services
- Virtual healthcare communities for motivation keeping
Virtual healthcare communities for motivation keeping b. b.
Field Experiments w/ healthcare Field Experiments w/ healthcare-
- related partner organizations
related partner organizations
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- Int. Workshop on Web Intelligence & Virtual Enterprises --
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BP Monitoring Issues
Ex.) Stress, emotions, speech, etc.
Short –term variability
Ex.) dipper, non-dipper, riser, etc.
circadian blood pressure
Image of blood pressure time series graph Image of blood pressure time series graph
We need 24h blood pressure measurement with event record.
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Wearable Blood Pressure Sensing
- Objective .
Objective .
- 1. Even during exercises
- 2. Daily life continuous measuring
- 3. Measured by wearable device
- Technical Point .
Technical Point .
・BP value estimation technique by correlation w/ Pulse wave Transit Time (PTT) ・ECG, Pulse, Body motion information collected from tiny wireless sensors
⎟ ⎟ ⎟ ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎜ ⎜ ⎜ ⎝ ⎛ ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛− + = α Δ ρ α
2 PTT 2 S
1 2 ln 1 c T c x P
New Formula New Formula
Current Tech. Current Tech.
- 1. Static position required
- 2. Every to 15 minutes
- 3. On desk device
ECG Pulse blood vessel
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Guillaume Lopez 15 15 PPG sensor PPG sensor ECG sensor ECG sensor ABPM Device ABPM Device Cuff for measure with Cuff for measure with stethoscope stethoscope
Wearable Blood Pressure Sensing
- Advances
Advances
- Next Issues
Next Issues
① Experiments in daily life ② Service design and implementation for test at hospital
・dimensions (mm) 65×129×20 ・weight 130g
脈波
(Pulse)
心電 + 加速度
(ECG + Acceleration)
Wearable Wearable Blood Pressure Blood Pressure Monitoring Device Monitoring Device Prototype Prototype
Can follow Can follow short short-
- term variations
term variations
「 「rest rest」 」 「 「exercise exercise」 」 「 「rest rest」 」
Experimental Protocol Experimental Protocol
Ausculatory Ausculatory Estimated from PTT Estimated from PTT
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D Dietary ietary H Habit abit Monitoring Monitoring
Eating Drinking Speaking
Doctor
Measurement system Measurement system
The number of chewing The number of chewing times before swallow times before swallow Food type Food type
Data Center Data Center Inside-body Sound in daily life
User User Guidance
1,2,3・・・
Bone Conduction Bone Conduction Mic Mic. . & & Condenser Mic. Condenser Mic. integrated in an integrated in an Earphone Earphone-
- like sensor
like sensor
Meal timing and length Meal timing and length
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Dietary Habits Sensing Technology
- Objective:
– Implementation of a autonomous dietary habits analysis and report system, and its extension to daily mental status fluctuations extraction.
- Tech. Point: Lifestyle analysis from sound information
– Investigate how much qualitative information could we get about dietary habits (i.e. chewing, meal timing, food texture…) using only sound information, and determine to what extent it could be used for mental status extraction.
- Advances:
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Meal Time Activities Classification
60% 80% 75% 53%
speak eat eat & speak brush
Mealtime 76%
Classification result for each meal-related behavior (eat 33%) (eat 47%)
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Meal Time Activities Extraction
First Step Second Step meal
sleep
sleep Meal meal meal train elevator train bus elevator
walk
発 話 食 べ る 発 話 食 べ る 歯磨き 発 話 食 べ る
[meal time: 13:05 [meal time: 13:05~ ~13:40, 35 minutes] 13:40, 35 minutes]
8:00 12:00 18:00 16:00 22:00 7:00 20:00
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- Int. Workshop on Web Intelligence & Virtual Enterprises --
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Research Plan
1. 1. Backgrounds & Focus Backgrounds & Focus 2. 2. Health Information Processing Platform Health Information Processing Platform
a.
Architecture for collection and storage
- New possibilities from wearable sensing
New possibilities from wearable sensing b.
Information system for data accumulation and sharing
- Unification of usual medical & health
Unification of usual medical & health-
- related information
related information
- Meta
Meta-
- Database
Database for information description & sharing for information description & sharing c.
Practical use of accumulated data
- Analysis Technologies (signal analysis, Data
Analysis Technologies (signal analysis, Data-
- mining)
mining)
- User Interface for adapted information representation
User Interface for adapted information representation
3. 3. Healthcare Services Healthcare Services
a.
Image of the type of healthcare services
- Disease prevention support services
Disease prevention support services
- Improved quality treatment of lifestyle diseases
Improved quality treatment of lifestyle diseases
- Health education events support services
Health education events support services
- Virtual healthcare communities for motivation keeping
Virtual healthcare communities for motivation keeping b. b.
Field Experiments w/ healthcare Field Experiments w/ healthcare-
- related partner organizations
related partner organizations
09 09-
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Oct-
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- Int. Workshop on Web Intelligence & Virtual Enterprises --
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Required Information Processing Platform
IP Network IP Network Common Authentication Platform Common Authentication Platform Real Real-
- time Transfer
time Transfer Event Notification Event Notification Data Accumulation Data Accumulation Various services delivered from 3 basic shared functions Various services delivered from 3 basic shared functions IP network IP network
Service A Service B Service C
IP network IP network Middleware Service
UBIQUITOUS HEALTH UBIQUITOUS HEALTH MONITORING MONITORING Single Single-
- functionality
functionality platform platform Absence of common Absence of common authentication system authentication system Conventional Conventional System System
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Approach Based on NGN/IMS Approach Based on NGN/IMS
(Next Generation Network/IP Multimedia Subsystem) (Next Generation Network/IP Multimedia Subsystem)
Service stratum Transport stratum
Applications (Server/contents) IP Network ADSL FTTH
Wireless LAN 3G/3.5G
・・・ IMS
(Service control function) (Packet transfer function)
Video Audio Data
User-Network Interface Application-Network Interface
NGN
Terminal Authentication Alert Control
Support access from various
networks (Ensure a broad network connectivity)
VoIP,IPTV…
Various Services w/ QoS constraint
Using NGN/IMS functions, requisites for authentication environment, broad network connectivity, and real-time transfer are filled
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Application Application Server Server
Subjects Subjects Observers Observers
Bio Bio-
- Environmental Info Processing Platform
Environmental Info Processing Platform
- implementation with generic components
implementation with generic components -
- Design Based on IMS Architecture
Design Based on IMS Architecture
Sensor Sensor IMS IMS Client Client
IMS components IMS components
HSS HSS
(Home Subscriber Server) (Home Subscriber Server)
SIP SIP signaling signaling
(Signal Information Processing) (Signal Information Processing) XCAP / XCAP / SIP SIP
RTP RTP
(Real (Real-
- time Transfer Protocol)
time Transfer Protocol) SUBSCRIBE SUBSCRIBE / / NOTIFY NOTIFY
XDMS XDMS
(XML Document (XML Document Management Server) Management Server)
IMS IMS Client Client
IP IP Multimedia Multimedia Subsystem Subsystem IP IP Multimedia Multimedia Subsystem Subsystem
CSCFs CSCFs
(Call/Session Control Function) (Call/Session Control Function)
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IMS Core Components IMS Core Components
Medical professionals Medical professionals
Meta Meta-
- Database Prototype
Database Prototype
Event Event notification notification
DB
Real Real-time transfer time transfer Analysis Analysis
Data Data accumulation accumulation Subjects Subjects Observers Observers
Application server IMS Client UCT IMS Client RF-ECG sensor
Acceleration ↓ Activity
Open IMS Core & XDMS
- UCT IMS Client
- IMS test bed using Open IMS
Core
- XDMS built-up on IBM DB
2.9 extension
- Application Server built-up
- n UCT IMS Client extension
- Application Server built-up
- n UCT IMS Client extension
XQuery XQuery available XDMS available XDMS:
- 1. XDMS extension to execute
execute XQuery XQuery into SIP into SIP event framework.
- 2. Changes in vital data can be
notified, without breaking NGN/IMS secured framework.
Patient (user) Patient (user)
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Bio Bio-
- Environmental Information Meta
Environmental Information Meta-
- Database
Database
raw raw Sensor Sensor data data
rest rest work work meal meal
- ne’s lifestyle
- ne
- ne’
’s lifestyle s lifestyle
home home University University Ginza Ginza
location location location emotion emotion emotion
stress stress
exercise / activity exercise / activity exercise / activity
walk walk walk walk
Meta-database with annotations from various points of view Bio-environmental information accumulated in a DB, which resources definition form is designed on REST architecture style (DB technology of WEB 2.0), to allow information to be open to the public in a scalable and flexible way Bio-environmental information accumulated in a DB, which resources definition form is designed on REST architecture style (DB technology of WEB 2.0), to allow information to be open to the public in a scalable and flexible way
Construction of a meta Construction of a meta-
- database to accumulate annotation information
database to accumulate annotation information integrated with bio integrated with bio-
- environmental data
environmental data
- Technology for Accumulation
Technology for Accumulation -
- excitement
excitement
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<?xml version="1.0" encoding="UTF-8"?> <vitaldata date="2008/10/27"> <properties> <name> <first>ALICE</first> <last>CARROLL/last> </name> <sex>FEMALE</sex> <age>23</age> </properties> </vitaldata>
Being a standard component of IMS, it can be used as the shared DB
from several Associated Servers, and simplifies the cross-utilization between various services.
Uses very flexible XML data.
XML is stored without scheme, so that even if vital data category used with increases, you only need to add new element and attributes.
XDMS
UPLOAD
AS AS AS
Advantages of XDMS for Vital Data Storage
REQUEST COLLECTION
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Data is represented by time series, using timestamp tag, together w/ integrated annotations on any daily lifestyle events.
issued for each new record Filled w/ time series sensor data and annotations ※reference by file path for data recorded on specialized binary std such as X-ray, etc. Root Tag Properties Area name sexe age Data Area
・ ・ ・
<?xml version="1.0" encoding="UTF-8"?> <vitaldata date="2008/10/27"> <properties> <name> <first>ALICE</first> <last>CARROLL</last> </name> <sex>FEMALE</sex> <age>23</age> </properties> <data> <t_hour hour=“14” ecg_graph=“http://xdms.ims2.mlab.t.u- tokyo.ac.jp/waveforms/ecg/2008102714.ecg”> <t_min min="08"> <t_sec sec="58" tmp=“36.6"/> <t_sec sec="59" tmp=“36.6"/> <ecg status="OK" /> </t_min> <t_min min="09"> <t_sec sec="00" tmp=“36.7"/> <t_sec sec="01" tmp=“36.8"/> </t_min> </t_hour> </data> </vitaldata>
- User profile info.
- Manage interoperability
w/ HL7 std format for EHR
XDMS Data Structure
hour min sec
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Research Plan
1. 1. Backgrounds & Focus Backgrounds & Focus 2. 2. Health Information Processing Platform Health Information Processing Platform
a.
Architecture for collection and storage
- New possibilities from wearable sensing
New possibilities from wearable sensing b.
Information system for data accumulation and sharing
- Unification of usual medical & health
Unification of usual medical & health-
- related information
related information
- Meta
Meta-
- Database for information description & sharing
Database for information description & sharing c.
Practical use of accumulated data
- Analysis Technologies (signal analysis, Data
Analysis Technologies (signal analysis, Data-
- mining)
mining)
- User Interface
User Interface for adapted information representation for adapted information representation
3. 3. Healthcare Services Healthcare Services
a.
Image of the type of healthcare services
- Disease prevention support services
Disease prevention support services
- Improved quality treatment of lifestyle diseases
Improved quality treatment of lifestyle diseases
- Health education events support services
Health education events support services
- Virtual healthcare communities for motivation keeping
Virtual healthcare communities for motivation keeping b. b.
Field Experiments w/ healthcare Field Experiments w/ healthcare-
- related partner organizations
related partner organizations
09 09-
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Oct-
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- Int. Workshop on Web Intelligence & Virtual Enterprises --
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Adaptable Data Representation / Display
Not Complicated This U.I. Easier to catch-up !! Not Not Complicated Complicated This U.I. This U.I. Easier to Easier to catch catch-
- up !!
up !!
9/1 9/1 Steps Count
5268 steps
3,318m
Calories Consumption
171 171 kcal
Fat Burning Amount
9.5 9.5 g
Continuous Steps
0 step
Continuous walking
0 h 0 0 min
health health-
- Tunes
Tunes
1 Month view 1 Month view steps + weight + calories input steps + weight + calories input 2008/8/1 2008/8/1 -
- 2008/8/31
2008/8/31 Walking Walking Support Support Diet Diet Advice Advice Eating Habits Eating Habits Support Support Today Today’ ’s report: s report:
5268 steps 70.6 kg Graph Display
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Info Display Based on Psychological Approach
- Objective:
– Considering user diversity, information display adaptation to personality/mentality, to improve healthcare “menu” continuity and results.
- Approach:
– The key to succeed in disease prevention and treatment, is to keep user motivated.
- Advances:
– We defined 4 types of user personality category based on 2 axes [Postponing tendance] and [Perfection searching] – By survey results analysis, we could define for each personality category which are the best goal definition, planning, info display, feedback methods.
- Next Issues:
– Countermeasure for “quick abandon” – Framework and roles definition/evaluation for social support environment by relatives, doctors, or virtual communities Healthcare support adapted to personality Healthcare support adapted to personality
Display example for Display example for 「 「postpone: high, perfection: low postpone: high, perfection: low」 」 searching searching postponing postponing tendance tendance perfection perfection
low low high high low low high high Today Today’ ’s result s result Week result Week result Today Today
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09 PRO'VE 09 PRO'VE 09 --
- Int. Workshop on Web Intelligence & Virtual Enterprises
- Int. Workshop on Web Intelligence & Virtual Enterprises --
- Guillaume Lopez
Guillaume Lopez 31 31
Research Plan
1. 1. Backgrounds & Focus Backgrounds & Focus 2. 2. Health Information Processing Platform Health Information Processing Platform
a.
Architecture for collection and storage
- New possibilities from wearable sensing
New possibilities from wearable sensing b.
Information system for data accumulation and sharing
- Unification of usual medical & health
Unification of usual medical & health-
- related information
related information
- Meta
Meta-
- Database for information description & sharing
Database for information description & sharing c.
Practical use of accumulated data
- Analysis Technologies (signal analysis, Data
Analysis Technologies (signal analysis, Data-
- mining)
mining)
- User Interface for adapted information representation
User Interface for adapted information representation
3. 3. Healthcare Services Healthcare Services
a.
Image of the type of healthcare services
- Disease
Disease prevention prevention support services support services
- Improved quality
Improved quality treatment treatment of lifestyle diseases
- f lifestyle diseases
- Health education events support services
Health education events support services
- Virtual healthcare communities
Virtual healthcare communities for motivation keeping for motivation keeping b. b.
Field Experiments w/ healthcare Field Experiments w/ healthcare-
- related partner organizations
related partner organizations
09 09-
- Oct
Oct-
- 09
09 PRO'VE 09 PRO'VE 09 --
- Int. Workshop on Web Intelligence & Virtual Enterprises
- Int. Workshop on Web Intelligence & Virtual Enterprises --
- Guillaume Lopez
Guillaume Lopez 32 32
Bio-Env Information Meta-DB Bio Bio-
- Env
Env Information Meta Information Meta-
- DB
DB
We plan to create real healthcare services that can play a role as countermeasures for metabolic syndrome.
Targeted Healthcare Services
Physiological Information Monitor
- signal viewer
- status report
Physiological Information Physiological Information Monitor Monitor
- signal viewer
signal viewer
- status report
status report
Fast walk: 1.5m/s Burned: 475kcal HR:105bpm Temp:37.0 ℃
Central Server Central Server Wearable Bio-Env Sensor Wearable Bio Wearable Bio-
- Env
Env Sensor Sensor Physiological Information Open Resource
- diagnosis support tool
- data-mining
- new knowledge extraction
Physiological Information Physiological Information Open Resource Open Resource
- diagnosis support tool
diagnosis support tool
- data
data-
- mining
mining
- new knowledge extraction
new knowledge extraction Physician Physician Nutritionist Nutritionist Health-related Habits Education Health Health-
- r
related elated Habits Education Habits Education Children Children Professional Services Professional Services Private Services Private Services Virtual Health Adviser Virtual Health Adviser Virtual Health Adviser Public Services Public Services
Work load Work load : Lv. 2 Tension Tension: Lv. 4 BP BP: 162mmHg
Virtual Stress Checker Virtual Stress Checker Virtual Stress Checker
09 09-
- Oct
Oct-
- 09
09 PRO'VE 09 PRO'VE 09 --
- Int. Workshop on Web Intelligence & Virtual Enterprises
- Int. Workshop on Web Intelligence & Virtual Enterprises --
- Guillaume Lopez
Guillaume Lopez 33 33
Terminal
Sensing device
Prevention & Treatment Service @UT Hosp.
1. 1.Metabolic discovery & Metabolic discovery & prevention prevention
Effects:
☆Able to catch BP sudden variations in various daily life situations, which is key to early detection of hypertension risk ☆Automatic tagging of situations, events affecting BP.
HR HR 160 160 BP BP 1 150 50
Heart Overloa d
② doctor side ・More accurate exercise menu control ・Detailed following of exercise menu results
2. 2.Patient treatment quality improve Patient treatment quality improve
Effects:
☆More safety execution of exercise menu ☆Treatment quality improvement ☆Monitoring efficiency improvement
Exercise menu controlled by Heart Load Index Heart Load Index
Heart Load Index = HR × × BP BP
Daily life exam:
■1week real life BP data, automatically
measured at specified time and interval
■1/day send electronic BP-Activity report
①doctor side ・Quantitative monitoring available ・Detailed understanding of BP variations in daily life ①patient side ・less burden ・safer exercise condition ②patient side ・less burden ・real status quantitatively measured
09 09-
- Oct
Oct-
- 09
09 PRO'VE 09 PRO'VE 09 --
- Int. Workshop on Web Intelligence & Virtual Enterprises
- Int. Workshop on Web Intelligence & Virtual Enterprises --
- Guillaume Lopez
Guillaume Lopez 34 34
Virtual Healthcare Communities
User’s family, relatives, neighbors, insurance
Data Data A Accumulation ccumulation
DB
Concerned parties Community
Nursing
Web Community Display, Actions Display, Actions Support, recommendations Support, recommendations
Emergency
Real Real time transfer
time transfer Reporting/monitoring services Reporting/monitoring services
data-mining diagnosis support tool
Event Event notification notification
Sensing/Feedback Services Sensing/Feedback Services Analysis Analysis, , Knowledge Knowledge
Health Preservation Challenge Health-twitter …
Professionals Community Bio Info Bio Info Open Resources Open Resources