Robotic First aid response

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Title Robotic First aid response
Summary A robot system which assesses a person's state of health as a step toward first aid/ems
Keywords robot first aid, injury localization, anomalous breathing recognition, bleeding recognitionProperty "Keywords" has a restricted application area and cannot be used as annotation property by a user.
TimeFrame 2015/1/16-2015/6/30
References (first aid teleoperated robots)

http://www.uasvision.com/2014/10/29/ambulance-drone-with-integrated-defibrillator/ http://www.technologyreview.com/news/411865/a-robomedic-for-the-battlefield/ (fall detection example) Simin Wang, Salim Zabir, Bastian Leibe. Lying Pose Recognition for Elderly Fall Detection (breathing recognition) Phil Corbishley and Esther Rodriguez-Villegas. 2008. Breathing Detection: Towards a Miniaturized, Wearable, Battery-Operated Monitoring System. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 55, NO. 1, JANUARY 2008

Prerequisites Requirement: some ability to work with software (installing libraries and writing code), and interest in robots, healthcare, or recognition
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)

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