Grant: Collaborative Research and Development Grants
Ryerson University
$100,000.00
Intelligent analysis and visualization of IoT signals for medical emergency assistance
EF 2018-19
Résumé
Emergency healthcare is one of the key factors affecting the quality-of-life of the general population. A major challenge in providing emergency healthcare assistance is consolidation of data from myriads of different sources to make an informed decision. In many cases, healthcare providers such as doctors, nurses and EMTs work in isolation with problems in communicating and exchanging appropriate information and important decisions at the right time. Recent advances in sensor and communications technology have made round the clock monitoring and data collection much easier. Similar advances in information processing technologies have facilitated the multitude of health monitoring and decision-making to alert health professionals to threatening conditions and assist them in making proper diagnostic decisions. Moreover, recent advances in immersive environments like Augmented/Virtual Reality (AR/VR) have opened up possibilities to provide emergency assistance locally or remotely through utilizing AR/VR for achieving a better sense of the state of a patient through data visualization. Yet overall very limited effort has been invested in integrating data analysis, decision making, and immersive visualization into one healthcare system, due to various multidisciplinary technical challenges.* We propose to investigate modern information processing techniques to facilitate medical emergency service. We will develop healthcare systems utilizing various IoT sensors to record the symptoms of the patients and analyze the data with smart signal processing/recognition and visualization methods to assist the healthcare professionals in performing timely diagnosis and decision-making in emergency situations. Specifically, we attempt to solve challenging problems in intelligent signal processing and feature representation of the IoT data, robust information fusion, and context-aware visualization in immersive environment. A prototype system will be developed, and integrated into the industry partner's healthcare platform and deployed in hospitals and other healthcare units to evaluate the performances of the technologies developed.*
Programme
Collaborative Research and Development Grants
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
529677-2018
Name nom
Guan, Ling
Department département
Electrical, Computer and Biomedical Engineering
Organization id
43
Institution établissement
Ryerson University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2018
Competition year année de concours
2018
Award amount
100000
Program id
CRDPJ
Program name en
Collaborative Research and Development Grants
Program name fr
Subventions de recherche et développement coopérative
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
802
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Information systems and technology
Area of application fr
Systèmes d'information et technologie de l'information
Research subject code
2708
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Image processing
Research subject fr
Traitement des images
Partie
1
Nb partie
1
Application title
Intelligent analysis and visualization of IoT signals for medical emergency assistance
Keyword
NSERC
Application summary
Emergency healthcare is one of the key factors affecting the quality-of-life of the general population. A major challenge in providing emergency healthcare assistance is consolidation of data from myriads of different sources to make an informed decision. In many cases, healthcare providers such as doctors, nurses and EMTs work in isolation with problems in communicating and exchanging appropriate information and important decisions at the right time. Recent advances in sensor and communications technology have made round the clock monitoring and data collection much easier. Similar advances in information processing technologies have facilitated the multitude of health monitoring and decision-making to alert health professionals to threatening conditions and assist them in making proper diagnostic decisions. Moreover, recent advances in immersive environments like Augmented/Virtual Reality (AR/VR) have opened up possibilities to provide emergency assistance locally or remotely through utilizing AR/VR for achieving a better sense of the state of a patient through data visualization. Yet overall very limited effort has been invested in integrating data analysis, decision making, and immersive visualization into one healthcare system, due to various multidisciplinary technical challenges.* We propose to investigate modern information processing techniques to facilitate medical emergency service. We will develop healthcare systems utilizing various IoT sensors to record the symptoms of the patients and analyze the data with smart signal processing/recognition and visualization methods to assist the healthcare professionals in performing timely diagnosis and decision-making in emergency situations. Specifically, we attempt to solve challenging problems in intelligent signal processing and feature representation of the IoT data, robust information fusion, and context-aware visualization in immersive environment. A prototype system will be developed, and integrated into the industry partner's healthcare platform and deployed in hospitals and other healthcare units to evaluate the performances of the technologies developed.*