Machine Learning and Sensing for Remote Biomedicine

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Machine Learning and Sensing for Remote
Biomedicine

• Tomás Lozano-Pérez
• MIT CSAIL

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Remotely assisted living

• Growth of elderly population a major challenge
  for 21st century
• Exploit cost-effective communication, computation
  and robotics to provide support for elderly
• On-site robotic assistance
• Remote medical monitoring

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Pervasive and Transparent

• Existing computer systems are inadequate for our
  goal
• Computers must live in users world not force
  users to live in computers world

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In general

• Reduce need for careful prior design
• Adapt to wide range of environments
• Understand the user

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Adaptive Computing

• Adapting to users
• People and Machines
• Adapting to computational environment
• Computers and Networks
• Adapting to physical environment
• Sensors and Effectors

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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.

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Adapting to Physical Environment

• Sensors
• Audio, video, haptics, X-ray/MRI, etc
• Effectors
• Displays, speakers, robots, etc

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Adapting to Computational Environment

• Bandwidth and latency
• Sensor/effector variation
• Computing resources available
• New software/hardware

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A Scenario SARS management
Hospital
Calling Ambulance
Hospital Admission
Community Infection Control
Recovery
Treatment
Contact Tracing
Patient Discharged
Collecting Disease Information
Disease Worsening
Supporting Clinical and Policy Research
Public Education
Courtesy Leong Tze Yun
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Other applications

• Remote consultation
• Tele-surgery
• Distance education
• Meeting support

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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

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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

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Operating Room Setup