Federal Initiatives in Smart Communities and the Internet of Things

Transcription

1 Federal Initiatives in Smart Communities and the Internet of Things Vinay M. Pai (Acting) Division Director Division of Health Information Technology National Institute of Biomedical Imaging and Bioengineering National Institutes of Health

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3 Medical Device Interoperability No means to coordinate devices with delivery of care Many non-integrated infusion pumps Devices, processes, non-integrated system errors No ability to synchronize imaging with ventilation No ability to integrate data for smart alarms

4 Medical Device Interoperability (MD PnP) PI: Julian Goldman, Partners HealthCare System and Mass Gen U01 mechanism Cooperative Agreement Aims Use cases Requirements Software & architecture Test and validation Complete deliverable sets Industry adoption Four Clinical Scenarios PCA Safety Interlock -component-level medical device interoperability ICU preparedness -from OR to ICU Tele-health (TH) devices between home and hospital Regulatory - regulatory pathway & regulatory safety

5 Medical Device Interoperability (MD PnP) PI: Julian Goldman, Partners HealthCare System and Mass Gen U01 mechanism Cooperative Agreement

6 Funding Opportunities PAR : Bioengineering Research Partnership (BRP) (R01) Accelerate development and adoption of promising tools and technologies to address important biomedical problems. Multidisciplinary teams yrs. 750K DC max. PA : Exploratory/Developmental BRGs (R21) Feasibility. High-risk, high reward. Multidisciplinary. Data generator. PAR : Bioengineering Research Grants (BRG) (R01) Multidisciplinary, accelerate adoption, integrative approach, small team. PAR : NIBIB Biomedical Technology Research Centers (P41) BTRCs: R&D new technologies at national/international level. Cutting edge, PI at forefront of field. 15 years max. 750K DC max

7 Cardiac Disease Management Problem:Patients with CVD have symptoms that frequently bring them to emergency care where there is limited baseline data Solution: Remote monitoring to create physiological cardiac activity fingerprints that alert professionals and patient when there are irregularities based on their own cardiac patterns Healthcare professional Subject Center Subject Cell Phone or Computer Connection Longitudinal pattern recognition Adapting parameters Vladimir Shusterman, PinMed, NHLBI, R43-44 HL , R41HL093953

8 Impact of Research: Technology-based Artificial Pancreas (AP) Cell and Smart phones* Microprocessors, Wireless Technology *Controllers based on mobile technologies allow option of remote monitoring In Testing: Automated, Ambulatory Systems Integrating Continuous Glucose Sensing and Insulin Delivery Electrode-based Continuous Glucose Monitors 2006-now In 2006, FDA-approves next-generation devices with realtime readings for users. Devices have continued to evolve. NIH, industry support Proven Benefits of Blood Glucose Control 1993: Intensive insulin therapy to control blood glucose greatly reduces risk for diabetic eye, kidney, and nerve complications. Requires frequent daily blood glucose checks. (Diabetes Control and Complications Trial ) NIH support Self-monitoring of Blood Glucose 1970s-1980s: Industry produces first commercial blood glucose meters for patients home use. Clinical research studies demonstrate improved diabetes control with selfmonitoring, advancing its adoption. NIH, industry support Error Grid Analysis 1987: Biostatistics method developed to evaluate clinical accuracy of blood glucose monitors. NIH support Interstitial Fluid Glucose Sensors 1980s-now: Interstitial fluid glucose found to reflect blood glucose. Minimally invasive technologies are developed for continuous monitoring--including miniaturized, biocompatible enzyme electrodes. NIH, industry support Insulin Pumps 1970s-now: Devices developed for programmable insulin delivery via pump, in conjunction with frequent blood glucose readings. Clinical studies help move insulin pumps into practice. Pumps can now display glucose readings. NIH, industry support

9 Developing an Artificial Pancreas

10 Current initiatives and FOAs RFA-DK : Advanced Clinical Trials to test Artificial Pancreas Device Systems in Type 1 Diabetes (UC4): $20M available To support the conduction of advanced clinical trials designed to test the outpatient clinical safety and efficacy of artificial pancreas (AP) device systems in type 1 diabetes patients. Must be advanced trials with preliminary data based on pilot and transitional studies already completed. RFA-DK : Physiological and Behavioral Approaches to Improve Type 1 Diabetes Outcomes (DP3): $10M available Human studies to develop and/or test a highly reliable, wearable, portable, easy to operate system linking continuous glucose monitoring and pancreatic hormone delivery in a closed loop system. RFA-DK : Development and Integration of Novel Components for an Automated Artificial Pancreas System (DP3): $6M available the development of new technologies that may be integrated in a wearable, portable, automated, closed loop system for glucose control in individuals with T1D.

11 Smart Environment Technologies for Health Assessment and Assistance acquire and apply knowledge about the resident and the physical surroundings to improve the resident s experience. Percepts (sensors) Environment Agent Actions (controllers) Cook and Schmitter-Edgecombe, PIs, Washington State University

12 Technology Challenges Longitudinal smart home data collection Characterize daily lifestyle of smart environment residents through minimal-supervision activity recognition and activity discovery; collected data will allow for a better measure of real-world outcome Design software algorithm that detect trends in behavioral data; earlier, preventative health interventions Evaluate activity-aware automated prompting technology for extending functional independence and improving quality of life; ecological momentary intervention

13 Funding Opportunities PAR /119: Technologies for Healthy Independent Living (R01/R21) Monitor health/deliver care in real-time, accessible, effective, and minimal obtrusive way. PA /161: Translational Research to help Older Adults Maintain their health and independence in the community (R21/R01) Move evidence-based research findings to develop new approaches to help older adults remain healthy and independent. NSF : NSF-NIH Interagency Initiative: Smart and Connected Health Accelerate development and use of innovative approaches to transform healthcare from reactive to prospective..

14 For further information/queries Contact me: Vinay M. Pai / Thank you

15 For further information/queries Contact me: Vinay M. Pai / Thank you

16 For further information/queries Contact me: Vinay M. Pai / Thank you

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18 Artificial Organs Artificial Pancreas Continuous glucose monitoring Collaborative effort with FDA, JDRF, NIH

19 Activity recognition Features: Sensor IDs/frequencies Study Scripted activities # Participants # Activities Recogn accuracy % Time of day Day of week Length of activity Previous activity Interwoven activities Multiple residents % % Learning Models: Naïve Bayes classifier Hidden Markov model Conditional random fields Support vector machines

20 Can we conduct functional assessment? Data from Day Out Task Day Out Task Complete 8 tasks in preparation for a day out. Can multitask and interweave to complete the tasks in and efficient and natural way. Feature Type DOT features Interruption features Sequencing features Parallelism feature Duration, sensor counts, sensor events Number of activity interruptions Sequence vector Pindex Dawadi, P., Cook, D., & Schmitter-Edgecombe, M. (2013). Automated cognitive health assessment using smart home monitoring of complex tasks. IEEE Transactions on Human-Machine Systems.

21 Can we present the data in a usable format?