제 12 회 정보통신응용기술워크숍 future it revolution

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



Aging in Place



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?



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



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



• 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



• 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



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



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



Bio-SOC Bio-Sensor & SOC



Body Sensor Network (BSN)

Camera

SpO2

EKG

EEG

BPGPS

Mp3PDA/Gateway

Motion Sensor

Bio-Sensor & SOC



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



Human Activity Human Activity



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



Activity Tracking

• Particle Filters for Motion Tracking

Human Activity



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



Activity Recognition (Ex.)

• Active Contour-based Segmentation

Sitting

Standing

TrainingData Set

Testing

Human Activity



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



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



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



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



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


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

제 12 회 정보통신응용기술워크숍 future it revolution

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