Slide 1 Towards a Cost-Effective Homecare for a Caregiver Assistance System in Brazil MAURO OLIVEIRA LAR-A Computer Network Laboratory of Aracati

Slide 2 16th Healthcom October 16th, 2014 Natal - RN Slide 2 Mauro Oliveira Federal Institute of Ceará (IFCE) Aracati, Brazil Odorico Andrade Federal University of Ceara (UFC) Fortaleza, Brazil Marcos Santos State University of Ceara (UECE) Fortaleza, Brazil Roberto Alcântara Federal Institute of Ceará (IFCE) Aracati, Brazil Germanno Teles Northeast Bank of Brazil(BNB) Fortaleza, Brazil Nazim Agoulmine Joseph Fourier University (UJF) Université d´Evry Val dÉssone evry.fr Towards a Cost-Effective Homecare for a Caregiver Assistance System In Brazil Towards a Cost-Effective Homecare for a Caregiver Assistance System In Brazil Team working on this project

Slide 3 1.Contextualization 2.Application Scenario 3.Brazilian Digital TV 4. LARIISA Project 5. Prototype Conclusion Summary

Slide 4 1. Contextualization

Slide 5 Health System - Information Era Based on Disease PREVENTION Costs ¢ Encouraged Discouraged Fonte: K. Jennings, K. Miller, S. Materna (1997) Hospital (specialits) Health Agent Primary Health Care $ CONTEXTUALIZATION Descentralization of Public Health System

Slide 6 PROBLEM Primary Health Care Primary Health Care Hospital (specialits) Hospital (specialits) Health Agent Health Agent Management Information Message Data Acquisition CONTEXTUALIZATION  Increasing Complexity of Health Management for Decision-making Increasing Complexity of Health Management for Decision-making

Slide 7 CONTEXT-AWARE FRAMEWORK SOLUTION ONTOLOGY BAYESIAN NETWORK Metadata Geolocation Decision- Making Information Health Knowledge Inference Mechanism PROBLEM  CONTEXTUALIZATION  LARIISA: an Intelligent System to support decision-making process DATA MINING

Slide 8 Data Acquisition (Patient CONTEXT) DECISION-MAKING LARIISA’s Scenario: a context-aware framework METADATA Option 1 Option 3 Option 2 LARIISA: A Context-Aware Framework LARIISA: A Context-Aware Framework ONTOLOGY BAYESIAN NETWORKS DATA MINING

Slide 9 2. Application Scenario

Slide 10 Scenario for LARIISA Application CAREGIVER - an unpaid or paid person who helps another individual with an impairment with his or her activities of daily living. 2. Motivation: The Brazilian Digital TV LARIISA can help Specialized person Or NON specialized person

Slide 11 Prague, Czech Republic July/2013 Data acquisition - CONTEXT

Slide 12 LARIISA Data Acquisition

Slide 13 ONTOLOGY BAYESIAN NETWORKS DARA MINING Data Acquisition (CONTEXT) METADATA DECISION-MAKING LARIISA: Next Generation

Slide The Brazilian Digital TV

Slide 15 Analógico Today Interactive Digital TV Digital The Brazilian Digital TV

Slide 16 Network Audio Video Data Data Carrossel 1. MOTIVATION Interactive Digital TV

Slide 17 Interactive Digital TV The Brazilian Digital TV

Slide 18 Prague, Czech Republic July/2013 Architecture of the Brazilian Digital TV GINGA, a recommendation H.761 of the International Telecommunications Union (ITU-T).

Slide LARIISA Project

Slide 20 Medical Sensors Humidity Sensor Atmospheric Pressure Sensor Temperature Sensor Digital Camera Global Positioning System (GPS) Accelerometer Internet Connection Light Sensor Proximity Sensor Compass Gyroscope Geographical Information System (GIS) LARIISA: a Context-Aware Framework

Slide 21 15th Healthcom October 10th, 2013 Lisbon, Portugal Slide 21 LARIISA: a Context-Aware Framework The photo IMG001 was taken at lat=S 3° 45' “, lon=W 38° 36' “ on February 2nd, 2013 at 8:00AM. Address =Av. G, Conj. Ceará, Fortaleza – CE. Local Temperatura=29°C. Comment= Dengue Habitat. 80%-90% likelihood of being with Dengue (Local Context) Information: lat=S 3° 45' “, lon=W 38° 36' “ on March 3rd, 2013 at 5:00PM. Body temperature=40°C, Heart rate=110 bpm, Blood pressure=140/90. Address=Av. F, Conj. Ceará, Fortaleza – CE. Local Temperature=25°C. Symptoms=Headache, Vomiting, Body aches. Patient B Patient A Health Agent Relocating a health agent for the Patient B’s house Information: lat=S 2° 22' “, lon=W 34° 33' “ on March 24th, 2013 at 3:00PM. Body temperature=37°C, Heart rate=90 bpm, Blood pressure=120/80. Address= Av. da Sé, n° 227, Conj. Palmeiras, Fortaleza – CE. Local Temperature=32°C. Symptoms=Chills, Diarrhea. Who is the patient? Are Data Structured? Who is the patient? Are Data Structured?

Slide 22 3° 45' " 38° 36' " 17:00 03/02/2013 Av. F, Conj. Ceará, Fortaleza - CE A, B, C 40°C 110bpm 140/90,,,,,,,,,, metadata file Building a metadata file Geolocation Patient Identification via Web Service Health Information

Slide 23 Context Providers Data Processing Data Acquisition Publishing User Device Internet Health Agent Device Symptoms + sus_id Global Context Local Context Inference Rules Context Aggregator (CA) Health Managers System Security Protocol Metadata LARIISA’s Architecture: a context-aware framework

Slide 24 IN LARIISA_BAY Inference Module Patient Health Agent Specialist Decision Module Interface Specialist Decision Module 1 1 Specialist Decision: f(%) 3 3 Pass Through A  f(%) A = A’ 2 2 Specialist Validation: A  f(%) A ≠ A’ RB % SITUATION ROOM Health Agent OUT A’ B’ C’ A’ B’ C’ C B A A C B OTHER CONTEXT PROVIDERS A’ B’ C’ LARIISA INFERENCE MODULE Sensors Health Center Ambulance METADATA User Interface Inference Rules Global Context Repository Local Context Repository Patient Specialist Epidemic Graph Manager LARIISA: Functional Diagram

Slide Prototype

Slide 26 Data Acquisition (Patient CONTEXT) DECISION-MAKING LARIISA’s Prototype METADATA Option 1 Option 3 Option 2 LARIISA: A Context-Aware Framework LARIISA: A Context-Aware Framework ONTOLOGY BAYESIAN NETWORKS

Slide 27 Local health context model Global health context model Prototype: Dengue Fever Case Study Metadata

Slide 28 ENTRADA DO SISTEMA Módulo de Inferência do LARIISA_Bay Paciente Agente de Saúde Especialista Interface Módulo de Decisão Módulo de Decisão 1 1 Decisão do Especialista: f(%) 3 3 Pass Through A  f(%) A = A’ 2 2 Validação do Especialista: A  f(%) A ≠ A’ RB % SALA DE SITUAÇÃO Agente de Saúde SAÍDA DO SISTEMA A’ B’ C’ A’ B’ C’ C B A A C B OUTROS PROVEDORES DE CONTEXTO A’ B’ C’ LARIISA LARIISA_Bay Sensores Posto de Saúde Ambulância METADADO Interface do Usuário Regras de Inferência Repositório de Contexto Global Repositório de Contexto Local Paciente Especialista Gráfico de Epidemias Gestor Screens of the proposed System Patient Health Agent Specialist

Slide 29

Slide 30 Conclusion

Slide 31 Conclusão Diga Saude (FUNCAP) SISA (FIOCRUZ) LARIISA (IFCE) GISSA (FINEP) Next Saude (DATASUS / Min Saúde) Sponsors LARIISA project is being sponsored since 2004 by the Science and Technology Ministry of Brazil and others Brazilian Research Agencies It will be applied to the brazilian public health system LARIISA project is being sponsored since 2004 by the Science and Technology Ministry of Brazil and others Brazilian Research Agencies It will be applied to the brazilian public health system

Slide 32 15th Healthcom October 10th, 2013 Lisbon, Portugal Slide 32 Mauro Oliveira

Slide 33 MUITO OBRIGADO