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IBM Research © 2006 IBM Corporation HARMONI: Client Middleware for Long-Term, Continuous, Remote Health Monitoring Iqbal Mohomed, Maria Ebling, William Jerome, Archan Misra
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IBM Research © 2006 IBM Corporation Remote Health Monitoring: The Business Motivation The United States spends $1.9 trillion on healthcare, or more than 16% of its GDP More than 90 million Americans live with chronic illnesses. –Chronic diseases account for 70% of all deaths in the United States. –The medical care costs of people with chronic diseases account for more than 75% of the nation’s $1.4 trillion medical care costs. –Chronic diseases require long-term management By 2010, the US will experience the most citizens in history, age 65 or over –200,000 Doctor Deficit by the year 2010
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IBM Research © 2006 IBM Corporation Remote Health Monitoring: The Opportunity Long-term monitoring offers benefits: –Early disease detection and trend analysis for healthy and at-risk individuals –Treatment and progress monitoring for patients –Participants in drug trials or experimental treatments to gauge efficacy, and side effects –Reduced workload on doctors, nurses and other healthcare providers Enabled by rapid improvements in two key technologies: –Improvements in wireless communications (WiFi, 3G, Bluetooth) –Continuing miniaturization of wireless sensors. Server Patient Diary BT Data
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IBM Research © 2006 IBM Corporation Challenges of Long-term Monitoring Technical –Cheap, unobtrusive, relatively accurate sensor technology –Specialized backend data storage, processing, analysis and visualization techniques and infrastructure –Techniques to deal with the limitations of mobile devices –End-to-end security Non-Technical –Privacy, Bioethics, Healthcare Access, etc.
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IBM Research © 2006 IBM Corporation Challenges of Long-term Monitoring Technical –Cheap, unobtrusive, relatively accurate sensor technology –Specialized backend data storage, processing, analysis and visualization techniques and infrastructure –Techniques to deal with the limitations of mobile devices –End-to-end security Non-Technical –Privacy, Bioethics, Healthcare Access, etc.
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IBM Research © 2006 IBM Corporation Remote Health Monitoring using Personal Mobile Hub Three-tier architecture, using a personal pervasive device (cell phone or PDA) as a relay (sensor pervasive device server) –Cellphones are becoming the ubiquitous computing device. Sensors collect variety of physiological and context data, and transmit via Bluetooth –Examples: Heart Rate, Weight, Blood Pressure, GPS Examples: PCC (IBM), CodeBlue (Harvard), Medical Jacket (Berkeley) PAN (Bluetooth) WAN (CDMA)
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IBM Research © 2006 IBM Corporation The Evolution of Long-term Monitoring 3-Tier Hub Architecture Client device functions as a pure relay –All data is relayed to backend server –Provides only “store-and-forward” during disconnection Optimizing client resources (e.g., bandwidth, energy) not a primary objective –Sensor stream rates relatively modest in practice HARMONI: Healthcare Adaptive Remote Monitoring Data stream processing distributed across both client and server –Appropriately filtered data relayed to backend server –Local triggering of actions while in disconnected state Optimized usage of device resources and network bandwidth –Context-aware, adaptive data filtering –Using connectivity predictions for scheduling transmissions –Stream-based data compression
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IBM Research © 2006 IBM Corporation HARMONI: Opportunities Addressed Efficient utilization of bandwidth and energy –If you are sitting at your desk, and have a heart rate within a normal range, does the system need to transmit every single value? Customize behavior for individual users –Is the normal range of your heart rate the same as the person sitting beside you? Adjust system behavior to the user’s context –If you leave your desk and go to the gym, does the range of your heart rate change? Cope with disconnections –What happens if an “interesting” pattern in sensor readings occurs when there is no connectivity to the remote server?
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IBM Research © 2006 IBM Corporation Key Innovations in HARMONI Context-Aware Stream Correlation and Data Filtering Predictive Anticipation and Transmission Scheduling Smart Disconnected Operation Compressed, Energy-Efficient Sensor Data Relaying
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IBM Research © 2006 IBM Corporation HARMONI Implementation Platform Nokia 770 Internet tablet –ARM processor, Linux-based –High-resolution display(800x480), touch screen with up to 65,536 colors –64-128 MB RAM, 64 MB FLASH storage (expandable up to 1GB … can be used for virtual memory) –Built-in Bluetooth (BlueZ stack) and 802.11 interfaces –Relatively cheap: $350 –http:///www.maemo.org provides open-source software and development environment.http:///www.maemo.org –Code compiled on an Intel/Debian Linux 3.1 box using cross-compiler (http://www.scratchbox.org) Nonin Model 4100 Sp02/heart rate monitor –Provides Heart rate and Oxygen saturation –Supports Bluetooth Serial Port Profile (SPP) –120 hours of continuous operation with 2 AA batteries –Three packets transmitted per second, where each packet is 375 bytes
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IBM Research © 2006 IBM Corporation Variation in User Data
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IBM Research © 2006 IBM Corporation Summary: Next Steps (Ongoing) Complete implementation and testing of the HARMONI Middleware –Perform real user studies to validate the impact of data compression and event filtering Develop algorithms and techniques for efficient connectivity prediction and anticipation. Connect with backend component to develop personalized filters and rules.
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IBM Research © 2006 IBM Corporation (Backup) Data rates for different sensors
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