제 12 회 정보통신응용기술워크숍 Future IT Revolution 프로액티브 라이프케어...
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Transcript of 제 12 회 정보통신응용기술워크숍 Future IT Revolution 프로액티브 라이프케어...
제 12 회 정보통신응용기술워크숍Future IT Revolution
프로액티브 라이프케어 기술
2007 년 4 월 11 일
경희대학교 동서의료공학과
김 태 성
동서신의학 u-라이프케어 연구센터동서신의학 u-라이프케어 연구센터
동서신의학 u- 라이프케어 연구센터
East-West Neo Medical u-Lifecare Research Center2
건강한 삶
즐거운 삶 행복한 삶
질 높은 삶
u- 라이프케어
u- 라이프케어 비전
동서신의학 u- 라이프케어 연구센터
East-West Neo Medical u-Lifecare Research Center3
Aging in Place
동서신의학 u- 라이프케어 연구센터
East-West Neo Medical u-Lifecare Research Center4
Smart Homes/Smart Care
How Can Technologies Help ?
Question: Can smart home systems anticipate the needs of residents or patients to improve the quality of life?
동서신의학 u- 라이프케어 연구센터
East-West Neo Medical u-Lifecare Research Center5
Proactive Lifecare
Proactive Lifecare: innovations in sensors (i.e., motes), software, and wireless technologies that allow vital information about human health to be tracked remotely.
Ross et al., 2004, IEEE Spectrum
동서신의학 u- 라이프케어 연구센터
East-West Neo Medical u-Lifecare Research Center6
Proactive System
• Proactive system must anticipate a user’s needs in prior to the user’s requests.– Activity tracking for status monitoring
– Task sampling for status monitoring
– Health maintenance
– Cognitive support for Alzheimer patients
– Enhanced communication with the outside
– Access to information and stimulation
동서신의학 u- 라이프케어 연구센터
East-West Neo Medical u-Lifecare Research Center7
• Initiated in 2002.
• Lead by Eric Dishman, Senior Research Scientist
• Intel’s goal: make people more proactive about their own health and wellness needs, long before they have an exhausting, expensive medical catastrophe that drives them to an emergency room
• Make technology more proactive by anticipating people’s health-related needs and take whatever action that is appropriate on their behalf
• Proactive Computing, a concept developed by David Tennehouse, Intel’s Vice President of Research
Intel’s Proactive Health Effort
동서신의학 u- 라이프케어 연구센터
East-West Neo Medical u-Lifecare Research Center8
• Biological and Behavioral Sensors– Gather real-world data– Monitoring and localization– Motion, contact, magnetic, RFID, motes, etc.
• Sensor Networks– Reliable, secure, wireless network of sensors– Plug and play – Context tracking
• Statistical Inference Engines– Transform that data into medically meaningful, contextual information– Determine the types or patterns of activities– Compare life-long database and current measures
• Behavior Tracking and Recognition– Activity tracking and recognition
• Home Networks and Display– Smart appliances: digital home technologies from PCs to TVs to cell
phones – Connect everything (TV, clock, telephone, PC, PDA, etc.)– Reminder: display technology
Proactive Health Technologies
동서신의학 u- 라이프케어 연구센터
East-West Neo Medical u-Lifecare Research Center9
Major Research Areas at u-LCRC
Bio MEMS 구조체 기술
SoC 기반 스마트 센서모듈 기술
u- 라이프케어 프로액티브 컴퓨팅 기술
건강 지원 스마트 오브젝트 기술
u- 라이프케어 플랫폼 기술
uLCRC연구내용
동서신의학 u- 라이프케어 연구센터
East-West Neo Medical u-Lifecare Research Center10
Bio-sensors
• Analytical devices which use biological interactions to provide either qualitative or quantitative measurements
• Bio-receptor is a chemical/biological molecular recognition element (ex. Antibody, enzymes, DNA, cells, tissue, or whole organ)
• Transducer converts the recognition event into a electrical signal (ex. Electrodes, pH electrode, thermistor, photon counter, piezoelectric device)
Bio-Sensor & SOC
동서신의학 u- 라이프케어 연구센터
East-West Neo Medical u-Lifecare Research Center11
Bio-SOC Bio-Sensor & SOC
동서신의학 u- 라이프케어 연구센터
East-West Neo Medical u-Lifecare Research Center12
Body Sensor Network (BSN)
Camera
SpO2
EKG
EEG
BPGPS
Mp3PDA/Gateway
Motion Sensor
Bio-Sensor & SOC
동서신의학 u- 라이프케어 연구센터
East-West Neo Medical u-Lifecare Research Center13
Challenges in BSN
• Application-driven Challenges– Data fusion (aggregate and filter)
• Erroneous sensor readings• Missing values• Feature selection• Source recovery• Distributed inference• Activity recognition
– Support of multiple data rates– Security and privacy at low energy cost– Localization
• Networking Challenges• Challenges for Sensor Nodes
– Low-complexity / low-power designs– Smart sensors
• Integration of BSN
Sensed Signal Mixture
Recovered Sources
Source Recovery using ICA
Bio-Sensor & SOC
동서신의학 u- 라이프케어 연구센터
East-West Neo Medical u-Lifecare Research Center14
Human Activity Human Activity
동서신의학 u- 라이프케어 연구센터
East-West Neo Medical u-Lifecare Research Center15
Human Activity Tracking & Recognition
TRACKINGTRACKING
Spatial Segmentation
Spatial Segmentation
Particle FilteringParticle Filtering
RECOGNITIONRECOGNITION
TemporalSegmentation
TemporalSegmentation
ANN, Hidden MarkovModels (HMM)
ANN, Hidden MarkovModels (HMM)
joint anglesjoint
anglesvideovideo skill
namesskill
names
Human Activity
동서신의학 u- 라이프케어 연구센터
East-West Neo Medical u-Lifecare Research Center16
Activity Tracking
• Particle Filters for Motion Tracking
Human Activity
동서신의학 u- 라이프케어 연구센터
East-West Neo Medical u-Lifecare Research Center17
Activity Recognition
VideoActivityModelsA,B,C
VideoActivityModelsA,B,C
Feature ExtractionSegmentation
Feature ExtractionSegmentation
LearningLearning
ANN/HMMANN/HMM
MotionVector
sequence
MotionVector
sequence
SegmentedContours
SegmentedContours
activitymodel Aactivitymodel A
activitymodel Bactivitymodel B
activitymodel Cactivitymodel C
LearnedANN/HMMLearned
ANN/HMMvideovideoActivity NamingActivity Naming
Learn
ing
Recogn
ition
Human Activity
동서신의학 u- 라이프케어 연구센터
East-West Neo Medical u-Lifecare Research Center18
Activity Recognition (Ex.)
• Active Contour-based Segmentation
Sitting
Standing
TrainingData Set
Testing
Human Activity
동서신의학 u- 라이프케어 연구센터
East-West Neo Medical u-Lifecare Research Center19
Proactive Computing for Lifecare
Bio Sensor Daily DB
Daily Activity DB
A Priori Knowledge- Models, Patterns- 치매 패턴 , 징후
Active Proactive Lifecare
Passive Proactive Lifecare
CBIRCBIR
Analysis and Processing for Dangerous Activity, Diseases
Proactive Lifecare- Warning- Diagnostics- Prognostics
Proactive Lifecare
동서신의학 u- 라이프케어 연구센터
East-West Neo Medical u-Lifecare Research Center20
Content-based Information Retrieval
• Spatiotemporally Unstructured Data Mining
• Content-based Information Retrieval (CBIR)– Daily DB 로부터 content-based
information retrieval 기술– Digital Still Images, Video, Audio– ECG, EEG, EMG, Medical Images
• Independent Component Analysis-based Content-based Information Retrieval
Proactive Lifecare
동서신의학 u- 라이프케어 연구센터
East-West Neo Medical u-Lifecare Research Center21
Constrained ICA-based CBIR
• No use of metadata where text labeling is used
• We consider the database as mixed data and the query image acts as a reference for the cICA algorithm.
• Constrained Independent Component Analysis (cICA) is used for extracting information from database.
Image Database
ProjectedDatabase
ConstrainedICA
Reference
Data
Extracted Information
Query Image
Proactive Lifecare
동서신의학 u- 라이프케어 연구센터
East-West Neo Medical u-Lifecare Research Center22
동양의학 Proactive Lifecare
한의학의 정량적 데이터
수집가능한 ,해석가능한 데이터
( 설진 데이터 ) 한의학적정성적 지식 모델
2. 온톨로지 모델 설계 - 세부과제 및 전체과제의 요구분석을 위한
연구 선행 - Task 온톨로지 구축을 위한 연구3. 온톨로지에 대한 질의 방법 및 API 개발 연구
1. 특정 Context 에서의 정량적 데이터와 한의학 정성적 지식의 융합을 위한 알고리즘 연구
한의지식 온톨로지 및 추론 엔진
Proactive Lifecare
동서신의학 u- 라이프케어 연구센터
East-West Neo Medical u-Lifecare Research Center23
홈 네트워크
프로액티브 컴퓨팅 / 추론
행위 / 생체 DB
RFID 센서 행위 추적
맥파
설진 당뇨MEMS
스마트침대수면정보
SoC
센서모듈
동서신의학 라이프케어 시스템 Proactive Lifecare
동서신의학 u- 라이프케어 기술연구
East-West Neo Medical u-Lifecare Research Center24
동서신의학 u- 라이프케어 Proactive Computing
u- 라이프케어
서비스 정보
East-West Neo Medical uLCRC
동서신의학 기술에 기반한 u- 라이프케어 연구센터
센
서
데
이
터
생체 센서생체 센서데이터데이터
행위 센서행위 센서데이터데이터
환경 센서환경 센서데이터데이터
행위DB
생체DB
동양의학KB
서양의학KB
개인 이력DB
데이터베이스 (DB)
및 지식베이스 (KB)
수면 환경 …운동
설진 맥파 … …혈액정보
추론엔진추론엔진
행위 추적 및
인식
동양의학 기반생체정보
서양의학 기반생체정보
영양
Proactive Lifecare