Robotic First aid response
| Title | Robotic First aid response |
|---|---|
| Summary | EMS Robot: assessing health state |
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| Author | Tianyi Zhang and Yuwei Zhao |
| Supervisor | Martin Cooney, Anita Sant'Anna |
| Level | Master |
| Status | Ongoing |
Goal: The capability for a robot in a home or facility to be able to care for people in the event of a health emergency, by possessing some critical first aid skills to allow assessment of a person's state.
Motivation: Robots need to be useful. One of the most useful things a robot can do is look after people's health and safety. A quick and meaningful assessment of a person's state during first response to a possible emergency could help save lives and prevent anguish.
Challenge: the first thing which should be done is to assess a victim's state, but this is very difficult; e.g., for a person who has fallen and unresponsive:
1) where did they hurt themselves? 2) are they breathing normally? 3) are they bleeding?
Approach: the student will perform three steps
1) obtain kinect data (skeleton and depth) of a human-shaped dummy falling in different ways
create a recognition system (possibly using LIBSVM) to classify if the head has been hurt
2) record sound samples based on videos of "agonal" respiration, tachypnea (fast breathing),
and regular breathing from YouTube
calculate mfcc features with htk
create a recognition system (possibly using LIBSVM) to classify kind of breathing
3) use a robot (possibly Turtlebot) to drag a white glove over a dummy (red ink will symbolize
blood at some areas) to detect the presence/location of deadly bleeding
Evaluation of system: accuracy or similar metric for how often the system detects head trauma, breathing, bleeding
Requirement: some ability to work with software (installing libraries and writing code), and interest in robots, healthcare, or recognition
Deliverable: an intelligent robot system which can assess a victim's state (thesis/report, code, video)