TY - JOUR
T1 - A model for safe transport of critical patients in unmanned drones with a ‘watch’ style continuous anesthesia sensor
AU - Jalal, Ahmed Hasnain
AU - Umasankar, Yogeswaran
AU - Christopher, Fraker
AU - Pretto, Ernesto A.
AU - Bhansali, Shekhar
N1 - Funding Information:
This work is supported by the ASSIST NSF ERC under Award Number (EEC-1160483). We acknowledge FIU graduate school for the financial support through “Doctoral Evidence Acquisition Fellowship.” We also acknowledge Kevin Luongo and Sara Abasi for their cordial support for material supply and sensor fabrication.
Publisher Copyright:
© The Author(s) 2018.
PY - 2018
Y1 - 2018
N2 - We envision unmanned aerial vehicles (UAV) for rapid evacuation of critically-ill patients from hazardous locations to health care facilities in safe zones. For safety, medical teams accompany patients to monitor vital signs and titrate anesthesia dose during transport. UAV transports would require continuous automated remote monitoring of both vital signs and of sedative dose to be feasible and safe. Volatile anesthetics (isoflurane) are the only anesthetic agents that can be monitored continuously with infrared spectroscopy (IR) devices; but unsuitable for transport. Our objective is to devise a safe UAV transport protocol incorporating novel technology for gas monitoring. Our group has developed and tested a miniaturized wearable fuel cell sensor that can detect isoflurane gas vapors as low as 40 ppm (within therapeutic range) with a sensitivity of 0.0112 nA ppm−1 cm−2. Ambient signal interference was resolved by principal component analysis (PCA). Data variance of 1st and 2nd principal components was 88.68% and 11.31%, respectively. The PCA regression model reported here can determine accurate Isoflurane concentrations. Electronic IoT platform has been built constituting micro-fuel cell, miniaturized electronic components with Bluetooth. This wearable sensor can be incorporated into a comprehensive life support system for casualty evacuation in conjunction with autonomous UAV emergency medical operations.
AB - We envision unmanned aerial vehicles (UAV) for rapid evacuation of critically-ill patients from hazardous locations to health care facilities in safe zones. For safety, medical teams accompany patients to monitor vital signs and titrate anesthesia dose during transport. UAV transports would require continuous automated remote monitoring of both vital signs and of sedative dose to be feasible and safe. Volatile anesthetics (isoflurane) are the only anesthetic agents that can be monitored continuously with infrared spectroscopy (IR) devices; but unsuitable for transport. Our objective is to devise a safe UAV transport protocol incorporating novel technology for gas monitoring. Our group has developed and tested a miniaturized wearable fuel cell sensor that can detect isoflurane gas vapors as low as 40 ppm (within therapeutic range) with a sensitivity of 0.0112 nA ppm−1 cm−2. Ambient signal interference was resolved by principal component analysis (PCA). Data variance of 1st and 2nd principal components was 88.68% and 11.31%, respectively. The PCA regression model reported here can determine accurate Isoflurane concentrations. Electronic IoT platform has been built constituting micro-fuel cell, miniaturized electronic components with Bluetooth. This wearable sensor can be incorporated into a comprehensive life support system for casualty evacuation in conjunction with autonomous UAV emergency medical operations.
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U2 - 10.1149/2.0111808jes
DO - 10.1149/2.0111808jes
M3 - Article
AN - SCOPUS:85048410326
VL - 165
SP - B3071-B3077
JO - Journal of the Electrochemical Society
JF - Journal of the Electrochemical Society
SN - 0013-4651
IS - 8
ER -