WG 2: Distributed Control & Sensing of Networked Medical Device Systems

1. Tarek F. Abdelzaher Timothy Buchman Rick Craft Mike Eklund Sandeep K. S. Gupta Nagarajan Kandasamy T. John Koo Bruce H. Krogh Tom Martin Douglas Miller Klara Nahrstedt Tariq Samad Ronald Marchessault Sebastian Fischmeister George Fainekos Wei Zhao WG 2: Distributed Control & Sensing of Networked Medical Device Systems

2. Problem statement Research needed to realize networked medical device systems supporting distributed sensing and control with • security, privacy, robustness, interoperability, extensibility, mobility, safety for the purpose of • improving health care in multiple dimensions and • enabling the diffusion of medical services

3. Summary of state of the art • awash in data and information poor • Balkanized: systems don't talk to each other • no loop closing • lack of physiological basis for increasing and interpreting sensing modalities • everything depends on humans

4. R&D challenges: component level • embedded systems technology • QoS guarantees for embedded components • middleware for real-time medical systems • certifiability of safety critical software • models/theory • formal language for dialog among clinicians, physiologists, and engineers (device designers) (sensing is easy; devices that do something, and conveying "shall nots" is difficult) • richer hybrid systems theory to accommodate complexity of physiological ... • device design • constraints: form factor, power, ... • usability • IT implications of new sensors and sensing modalities, e.g., smart sensors, digital video processing, • new power management, e.g., harvest energy from the environment

5. R&D challenges: Systems level • human factors • ergonomics, human-machine interface • control over networks/ human in the loop remote control • system integration & performance issues • standards & architectures • end-to-end service models • system-level power management • QoS guarantees for systems of systems • systems engineering: identifying processes to be reengineered • information & algorithms • patient-specific learning/adaptivity • integration of devices and EHR/clinical decision support systems • security & privacy in embedded systems • distributed calibration and data validation • maintenance and authentication • augmenting situational awareness • model-based monitoring and control • extensibility, integration of new information

6. High priority IT research needs • standards & architectures • open source middleware for distributed systems • models • need formal languages for dialog between clinicians, physiologists, and engineers/computer scientists • model-based design tools • composability • test beds • components • user/patient • system • device

7. Roadmap: 3 Year Milestone • Deployed networked sensing and control system on a mobile distributed population • concept • sense ekg tracings, pulse oximeter • closed-looped oxygen bottle control • features • end-to-end QoS • infrastructure for 1000 nodes (large scale) • remote processing of data • integrated with EHR • multivendor plug n play - auto configuration • smart sensors & smart alarms

8. Roadmap: 5 Year Milestone • Configurable communication/sensing/control ER and geriatric primary care • concept • additional higher bandwidth sensing modalities • insulin/glucose (control) • features • point-to-(some) points • patient localization • service discovery & negotiation • secure network reprogramming • service virtualization • enhanced distributed control of local control loops

9. Roadmap: 7 Year Milestone • Integrated portable pre/post-operative monitoring for civilian and combat scenarios • concept • e.g., ambulatory ultrasound monitoring, monitoring blood vessel grafts, remote radiologist evaluation • real-time dosage adjustment • features • very high bandwidth • local and remote closed-loop control using patient-specific models • semi-autonomous treatment planning • wide-area distribution • ad hoc mobile environment • robust smart alarms using information fusion

10. Roadmap: 10 Year Goal • Fully integrated hospital acute care using distributed monitoring and control • Demonstration of impact of long-term deployment of networked in-home monitoring