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An intelligent and portable ambulatory medical toolkit for automatic detection and assessment of traumatic brain injuries

Published: 05 October 2010 Publication History

Abstract

We propose to develop a portable, handheld, noninvasive solution for accurate screening and real-time monitoring of traumatic brain injury (BI) in ambulatory/emergency response scenarios. A layered sensing concept that unifies alternate modalities such as a) ultrasound (US), b) near infrared spectroscopy (NIRS), c) tonometry (IOP), to predict BI, their severity and mode of recommendations for emergency medical service (EMS) personnel is offered. Specifically, we aim to determine i) novel 3D morphometric parameters of optic nerve sheath that can predict elevated intracranial pressure from US data, ii) incidence of intracranial hematomas using NIRS, iii) intraocular pressure using a tonometer, iv) cerebral blood flow and blood oxygen content using other auxiliary non-invasive sensing modes and v) finally provide a sensor fused outcome of all i)-iv) combined. This decision-support system (DSS) will improve BI detection by incorporating accurate on-site measurements that accounts for individual baseline variations and monitors temporal manifestation of the injury. The data collected and the preliminary analysis performed by the DSS will be sent to an emergency department (ED) physician stationed at a nearby trauma center via a wireless 3G network. Based on the available bandwidth, either all the data including the preliminary analysis (US video, images, 1D measurements, etc) or only the refined signals (feature vector extracted during screening) along with the DSS diagnosis will be sent to the physician. If the DSS determined output is agreeable to the physician then the screening can be terminated and the physician/ED staff can prepare to perform advanced interventions (intubation, cerebralspinal fluid (CSF) drainage, etc). If not, the on-call physician can inform the medic to repeat the scans/take additional measurements to obtain a more concrete outcome via the DSS. In summary, such a knowledge-driven system will equip a novice or a trained medic with an easy-to-use tool to detect traumatic BI and reduce the diagnosis time involved (i.e., computed tomography (CT) scan, clinical evaluation) in ED before performing advanced interventions and thereby improve the prognosis.

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Cited By

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  • (2012)The Clinical Application of Mobile Technology to Disaster MedicinePrehospital and Disaster Medicine10.1017/S1049023X1200117327:5(473-480)Online publication date: 14-Aug-2012
  • (2010)A multimodal sensing system for detection of traumatic brain injuryWireless Health 201010.1145/1921081.1921110(198-199)Online publication date: 5-Oct-2010

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cover image ACM Other conferences
WH '10: Wireless Health 2010
October 2010
232 pages
ISBN:9781605589893
DOI:10.1145/1921081
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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  • WLSA: Wireless-Life Sciences Alliance
  • University of California, Los Angeles

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Published: 05 October 2010

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WH '10: Wireless Health 2010
October 5 - 7, 2010
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Cited By

View all
  • (2012)The Clinical Application of Mobile Technology to Disaster MedicinePrehospital and Disaster Medicine10.1017/S1049023X1200117327:5(473-480)Online publication date: 14-Aug-2012
  • (2010)A multimodal sensing system for detection of traumatic brain injuryWireless Health 201010.1145/1921081.1921110(198-199)Online publication date: 5-Oct-2010

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