1. Cloud Service for Elderly Care
Subject 4
Daily Activity Recognition for Elderly Care
傅立成 教授 郭斯彥 教授

2. Outline
Introduction
Technical Components
Scenario 2

3. Objectives Three goals of cloud-based platform
Integrate various resources of elderly care.
Provide necessary care services and information to elders, care-givers and researchers.
Provide extensible service provision interface to extend our service
Extending other services by extensible service provision interface. 3

4. Technical Components Healthcare Platform Demo Inference Engine
(5)Healthcare Platform Service
(4)ADL Data Mining Platform
第三方服務：可為其他雲端服務或終端服務提供者等等
Inference Engine
Improvement
Cloud Database
(3)Inference Engine Improvement
ADL Data Mining
Platform
Cloud Middleware（Live E!、API）
(2)Cloud Middleware
Cloud Services
Service Expansion
Activity Recognition
Weather
(1)Data Collection 4

5. Data Collection （1/5） WSN User Feedback Activities of Daily Living
Indoor Temperature, Humidity
Outdoor Temperature, Humidity, Rainfall
Heartbeat, Systolic, Diastolic
User Feedback
Excretion frequency
Quality of sleep
Pain index
Activities of Daily Living
Read
Watch TV
Prepare Food
Drink
Go out & Go home
Sleep
Clean 5

6. Cloud Middleware （2/5） Live E! protocol API for cloud data center
Developed by The University of Tokyo
IEEE 1888
API for cloud data center
Design a highly reliable middleware to access cloud databases.
The high flexibility feature of cloud facilitates dynamic adjustment of services and the receiving of useful information.
Live E! Data
Transfer Platform
or sensor data
Cloud Middleware
Cloud Database 6

7. Inference Engine Improvement（3/5）
Use self-developed cloud MREM algorithm to adapt home-side activity recognition model to context change dynamically.
ADL Database
(HBase)
Cloud Collaborative Mode Mining Service
Model Update
Cloud Model
Update Service
Home Service
Active Recognition
Engine
Activities Data
MREM: MapReduce-Assisted EM 7

8. Inference Engine Adjustment（3/5）
Use self-developed cloud MREM algorithm to adapt home-side activity recognition model to context change dynamically.
ADL Database
(HBase)
Cloud Collaborative Mode Mining Service
Model Update
Cloud Model
Update Service
Home Service
Active Recognition
Adjustment
Activities Data
MREM: MapReduce-Assisted EM 8

9. ADL Data Mining Platform （4/5）
Objectives
Mine useful caring knowledge from collected data
Serve as a readily accessible web service.
Possible combining applications
Chronic diseases alerting system
Other possibilities.
Properties:
Large-scale MapReduce enabled data mining.
Directly connection with the healthcare platform
Mining result may directly return to the healthcare platform.
Automatic medical advices generation.
Other
Cloud Database
Data Mining Platform
Households
Cloud Middleware
Other Information

10. Healthcare Platform Service (5/5)
Provide current information
body measurement, activity of daily living (ADL), and doctor prescription
To elderly and their families, and medical institutes.
Support Caring record for medical staff to better understand elderly people from long- term health status.
Explore potential applicative possibility through caring records analysis
Data mining related applications
Enhance social involvement of elderly people through Facebook application
Automatic sentence analysis and generation
Elderly Information
Caring Record
Use Caring record to help medical personnel better understand the long-term health status of the elders
Attention XML
FaceBook 10

11. Healthcare Platform Service (5/5)
Provide the latest information
body measurement, activity of daily living (ADL), and doctor prescription
Use Caring record to help medical personnel better understand the long-term health status of the elders
Explore other applicative possibility through the use of the caring records
Data mining related applications
Use Facebook to enhance social activities of elderlies
Automatic sentence analysis
Elderly Information
Caring Record
Attention XML
FaceBook 11

12. Thanks for your attention