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Machine Learning and Sensing for Remote Biomedicine

Machine Learning and Sensing for Remote Biomedicine






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    Machine Learning and Sensing for Remote Biomedicine Machine Learning and Sensing for Remote Biomedicine Presentation Transcript

    • Machine Learning and Sensing for Remote Biomedicine Tomás Lozano-Pérez MIT CSAIL
    • Remotely assisted living
      • Growth of elderly population a major challenge for 21 st century
      • Exploit cost-effective communication, computation and robotics to provide support for elderly
        • On-site robotic assistance
        • Remote medical monitoring
    • Pervasive and Transparent
      • Existing computer systems are inadequate for our goal
      • Computers must live in user’s world not force users to live in computer’s world
    • In general…
      • Reduce need for careful prior design
      • Adapt to wide range of environments
      • Understand the user
    • Adaptive Computing
      • Adapting to users
        • People and Machines
      • Adapting to computational environment
        • Computers and Networks
      • Adapting to physical environment
        • Sensors and Effectors
    • Adapting to Users
      • Physical environment
        • Where are they?
      • Goals
        • Find glasses
      • Activities
        • Cooking dinner
      • Knowledge state
        • Do they know Jane called?
      • Mental state
        • Are they depressed?
      • Cultural and social milieu
        • Currency, food, family, etc.
    • Adapting to Physical Environment
      • Sensors
        • Audio, video, haptics, X-ray/MRI, etc
      • Effectors
        • Displays, speakers, robots, etc
    • Adapting to Computational Environment
      • Bandwidth and latency
      • Sensor/effector variation
      • Computing resources available
      • New software/hardware
    • A Scenario: SARS management Hospital Contact Tracing Hospital Admission Treatment Recovery Disease Worsening Patient Discharged Calling Ambulance Community Infection Control Collecting Disease Information Supporting Clinical and Policy Research Public Education Courtesy: Leong Tze Yun
    • Other applications
      • Remote consultation
      • Tele-surgery
      • Distance education
      • Meeting support
    • Fundamental Technological Needs
      • Signal to Symbol
        • Object/Activity recognition
      • Recognizing patterns
        • Recognize deviations from normal behavior
      • Goal oriented systems
        • Achieve goals not follow rote instructions
    • Getting there…
      • Perception
        • Vision, speech, medical imaging
      • Machine Learning
        • Fitting complex models, classification
        • Optimal data acquisition and decision making
      • Modular, adaptive, distributed systems
        • Adaptive software design methodology
        • Reconfigurable hardware
      • Algorithms
        • Real time algorithms
        • Correctness
    • Operating Room Setup