Measurement of Capillary Refill Time (CRT) in Healthy Subjects using a Robotic Hand

Research output: Contribution to conferencePaper

Abstract

A human’s Capillary Refill Time (CRT) is a key indicator of their current health status. Being able to accurately assess a human’s cardiovascular system peripherally by assessing their CRT in an emergency or search and rescue situation could, in critical scenarios, mean the difference between life and death. This paper presents a novel algorithm that enables a Shadow Robot Hand equipped with BioTAC biomimetic tactile fingertip sensors and a red, green, blue (RGB) camera to measure the CRT of humans by making contact with their forehead, regardless of their skin tone.
The method presented replicates, to some extent, the methods carried out by medical professionals when measuring CRT and could be used to equip a first responder robot.
Furthermore, the algorithms determine whether a person has a healthy cardiovascular system or whether the blood supply has been cut off from the skin indicating various issues such as shock or severe dehydration. The method presented in this work allows for a more accurate measurement of CRT than that of a medical professional.

Conference

ConferenceCVPR 2018
Abbreviated titleIEEE/CVF Conference
CountryUnited States
CitySalt Lake City
Period18/06/1822/06/18
Internet address

Fingerprint

Cardiovascular system
End effectors
Skin
Robots
Biomimetics
Dehydration
Blood
Cameras
Health
Sensors

Keywords

  • Tactile Sensing
  • Robotics
  • vital signs
  • Assisted living
  • Computer Vision

Cite this

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title = "Measurement of Capillary Refill Time (CRT) in Healthy Subjects using a Robotic Hand",
abstract = "A human’s Capillary Refill Time (CRT) is a key indicator of their current health status. Being able to accurately assess a human’s cardiovascular system peripherally by assessing their CRT in an emergency or search and rescue situation could, in critical scenarios, mean the difference between life and death. This paper presents a novel algorithm that enables a Shadow Robot Hand equipped with BioTAC biomimetic tactile fingertip sensors and a red, green, blue (RGB) camera to measure the CRT of humans by making contact with their forehead, regardless of their skin tone.The method presented replicates, to some extent, the methods carried out by medical professionals when measuring CRT and could be used to equip a first responder robot.Furthermore, the algorithms determine whether a person has a healthy cardiovascular system or whether the blood supply has been cut off from the skin indicating various issues such as shock or severe dehydration. The method presented in this work allows for a more accurate measurement of CRT than that of a medical professional.",
keywords = "Tactile Sensing, Robotics, vital signs, Assisted living, Computer Vision",
author = "Emmett Kerr and Sonya Coleman and T.Martin McGinnity and Andrea Shepherd",
year = "2018",
month = "4",
day = "4",
language = "English",
pages = "1404",
note = "CVPR 2018 : Conference on Computer Vision and Pattern Recognition, IEEE/CVF Conference ; Conference date: 18-06-2018 Through 22-06-2018",
url = "http://cvpr2018.thecvf.com/",

}

Kerr, E, Coleman, S, McGinnity, TM & Shepherd, A 2018, 'Measurement of Capillary Refill Time (CRT) in Healthy Subjects using a Robotic Hand' Paper presented at CVPR 2018, Salt Lake City, United States, 18/06/18 - 22/06/18, pp. 1404.

Measurement of Capillary Refill Time (CRT) in Healthy Subjects using a Robotic Hand. / Kerr, Emmett; Coleman, Sonya; McGinnity, T.Martin; Shepherd, Andrea.

2018. 1404 Paper presented at CVPR 2018, Salt Lake City, United States.

Research output: Contribution to conferencePaper

TY - CONF

T1 - Measurement of Capillary Refill Time (CRT) in Healthy Subjects using a Robotic Hand

AU - Kerr, Emmett

AU - Coleman, Sonya

AU - McGinnity, T.Martin

AU - Shepherd, Andrea

PY - 2018/4/4

Y1 - 2018/4/4

N2 - A human’s Capillary Refill Time (CRT) is a key indicator of their current health status. Being able to accurately assess a human’s cardiovascular system peripherally by assessing their CRT in an emergency or search and rescue situation could, in critical scenarios, mean the difference between life and death. This paper presents a novel algorithm that enables a Shadow Robot Hand equipped with BioTAC biomimetic tactile fingertip sensors and a red, green, blue (RGB) camera to measure the CRT of humans by making contact with their forehead, regardless of their skin tone.The method presented replicates, to some extent, the methods carried out by medical professionals when measuring CRT and could be used to equip a first responder robot.Furthermore, the algorithms determine whether a person has a healthy cardiovascular system or whether the blood supply has been cut off from the skin indicating various issues such as shock or severe dehydration. The method presented in this work allows for a more accurate measurement of CRT than that of a medical professional.

AB - A human’s Capillary Refill Time (CRT) is a key indicator of their current health status. Being able to accurately assess a human’s cardiovascular system peripherally by assessing their CRT in an emergency or search and rescue situation could, in critical scenarios, mean the difference between life and death. This paper presents a novel algorithm that enables a Shadow Robot Hand equipped with BioTAC biomimetic tactile fingertip sensors and a red, green, blue (RGB) camera to measure the CRT of humans by making contact with their forehead, regardless of their skin tone.The method presented replicates, to some extent, the methods carried out by medical professionals when measuring CRT and could be used to equip a first responder robot.Furthermore, the algorithms determine whether a person has a healthy cardiovascular system or whether the blood supply has been cut off from the skin indicating various issues such as shock or severe dehydration. The method presented in this work allows for a more accurate measurement of CRT than that of a medical professional.

KW - Tactile Sensing

KW - Robotics

KW - vital signs

KW - Assisted living

KW - Computer Vision

M3 - Paper

SP - 1404

ER -