Appliance Aggregation Scenarios for Healthcare Ambient Assisted Living and Patient Risk Management ADINA RIPOSAN Department of Applied Informatics, Military Technical Academy (MTA), and Contact Net Ltd, Bucharest, Romania
Why mobile and static integration for Healthcare? The Objectives
Ambient Assisted Living ICT-enabled independent living for elderly for disabled people Personal Health Systems (PHS) self management of healthcare at home by individuals remote monitoring of high-risk patients Paramedical Emergency Scenarios integrate static & mobile medical entities aggregate patient data on-the-fly' on-the-fly' from static & mobile data sources patient-centered virtual environment (case- specific, context-aware )
APPAGG for Ambient Assisted Living (AAL) Personal Health Systems (PHS)
AAL & PHS Objectives: ICT-enabled independent living for elderly and disabled patients Self management of diseases and care at home by individuals and their families Remote health monitoring & diagnosis Synergy between wearable sensors / portable medical devices and home automation systems Integration of: personal medical devices, wireless medical sensors, digital home technologies, home automation systems, cognitive assistance, advanced robotics for care support, context aware applications and services, intelligent proactive computing technologies
1. From Sensors to Personal Health Assistant (PHA device) PHA -> Adaptability -> Ambient-intelligent PHA The utilization of a PDA as intelligent point-of-care (POC): to gathering sensor data from multiple sources, to integrate and analyzing data, to autonomously interpret the results, to return the diagnosis or monitoring status for home care Context awareness and ambient intelligence: to include environmental factors when analyzing data generated by different sensors, to combine physiological, contextual and environmental parameters in a multi-parameter monitoring process
2. Scientific workflows: Intelligent, autonomous systems: multi-parameter monitoring, multi-parameter signal processing, correlation, interpretation, Þ patient self management Þ support for (personal) decision making Workflow solutions for intelligent data management, integrated data analysis and algorithms for multi-parameter correlation and interpretation. Workflow management from mobile devices: (disconnected mode) The user interface provided by a mobile device, can interact with a number of workflow systems The enactment engine can run elsewhere, independently of the user interface => to execute the aggregated workflow selected through the user interface
3.Devices/Sensors to expose Web Services for remote monitoring: Remote sensing technical paradigm shift The P2P (Peer-to-Peer) approach: Þ to allow the hosting and interaction with Web services and WS-RF services within ah-doc P2P environments Þ decentralized (Peer-to-Peer) discovery Web services interaction between: light-weight devices (limited and potentially unreliable) high-end machines and static, sophisticated environments Peer groups: Ensuring QoS (stability by aggregation capabilities) Enforcing Security (group membership, group identity)
4.Multimodal Adaptable Interfaces and User profiles: appropriate ways to interface the systems for the user To adapt to both: the particular user requirements/profile the environmental factors Intelligent systems to learn from the user behaviour and requirements => automatic user profile generation (e.g. based on the levels of disability) System capabilities for self-configuration (support for disabled) Note: Synergy with E-Inclusion projects (e.g. multimodal adaptable interfaces for visually-impaired people).
APPAGG for Paramedical Emergency Scenarios
Paramedical Emergency Operations Mobile P2G Architecture Using distributed computing techniques: to connect static & mobile entities bringing the tools, expertise and databases together to aggregate patient data on-the-fly'' integrate it into a situation & context-specific patient- centered virtual environment. We propose a hybrid P2G (Peer-to-Grid) framework to: consolidate Peer-to-Peer & Grid computing research address mobility of transiently connected devices support interactive configurability of components for dynamic data-driven distributed paramedical scenarios.
P2G 3 Layer Architecture Mobile Grid Multiple Ambulance Environments Bridge Layer Static Grid Virtual Emergency Environment Hospitals and patient record databases the architecture of the P2G here, we use P2P overlay techniques, grouping, authentication etc to organize the mobile resources
Static Entities: Medical Emergency Control Centre paramedical control centre, the management and monitoring authority for emergency operations; hosts the gateway / bridge layer in the P2G architecture Medical Data Resource Centres medical units that keep patient data and health records databases; represent static data sources for data & knowledge discovery, and form the static grid layer in the P2G architecture Medical Emergency Units medical units / hospitals where the patients can be transported; can also play the role of static data sources for data & knowledge discovery
Mobile Entities: Fleet of Ambulances managed and monitored by the Emergency Control Centre; play the role of controller nodes and super-peers in the P2G architecture Medical Devices various types of medical devices & tools used in ambulances, sensors and wearable systems, to record real-time vital medical data from patients; can play the role of mobile data sources,, and represent peers in the P2G architecture Personnel Devices communication mobile devices (smart phones, PDAs) used by the medical team; represent peers in the P2G architecture, but are capable to take the coordination & management role from the super-peer (controller node, the ambulance) in case of node failure, to ensure fault tolerance.
The Ambulance environment: Set of mobile devices => communicate & exchange data locally during the rescue operation. medical tools personnel devices (E.g., the personnel mobile devices receive notices and automatic messages from the medical tools & sensor devices) Controller node situated in the Ambulance: acts as a gateway to the ambulance environment, handles data transfer to: other ambulances participating in the rescue operation Emergency Control Center could be: integrated into the ambulance-vehicle itself added to the vehicle as a separate device
Medical Data discovery & integration from the Ambulance environment: Medical devices & tools used in ambulances: record real-time data from patients ad hoc vital medical data acquisition & quantification Sensors integrated via base stations and pre-processed locally sensor data acquisition: patient's medical and physiological parameters, biometric & environmental data unobtrusive monitoring of electrocardiogram (ECG), heart and respiratory rates, blood pressure, blood glucose level, oxygen saturation, skin temperature Filtered signals and data are instantly transmitted to the Emergency Control Centre and integrated within the VEE. => All medical and physiological measurements become available via the gateway
Collaborating Adina Riposan Department of Applied Informatics, Military Technical Academy, and Contact Net Ltd, Bucharest Ian Taylor & Ian Kelley Department of Computer Science, Cardiff University, and the Center for Computation and Technology (CCT)( @ LSU Andrew Harrison Department of Computer Science, Cardiff University
Thank you for attention! For more information Adina.Riposan@contactnet.ro