Reference number : GC-2017-Q3-00587, amendment number : , agreement type : G, recipient legal name : Mitsis, Georgios (McGill University)|Mitsis, Georgios (Université McGill), recipient country : CA, recipient province : nan, recipient city : Quebec|Québec, recipient postal code : nan, program name english : Engage Grants for universities, program name french : Subventions d'engagement partenarial pour les universités, program purpose english : The goal of this research project is to develop computational algorithms for processing ambulatory_x000D_
Electrocardiogram (ECG) signals recorded in real time by a wearable device and accurately measuring the_x000D_
variation in the time intervals between each heartbeat, referred to as heart rate variability (HRV). HRV is an_x000D_
important vital signal used by physicians and other healthcare professionals to monitor and assess the risk of_x000D_
several cardiac and non-cardiac disorders. The main technical challenges this research sets out to overcome_x000D_
involve reliably extracting HRV measurements despite common disturbances present in ambulatory ECG_x000D_
monitoring and efficiently designing the algorithms to operate in real-time to allow for continuous_x000D_
measurements of the subject's current HRV. The partner organization intends to add the developed algorithms_x000D_
to their existing remote monitoring device, which is currently capable of recording ECG amongst other_x000D_
physiological and physical activity signals. By adding the capability of accurate HRV measurement to the_x000D_
wearable device and monitoring platform developed by the industry partner, a crucial vital sign will be_x000D_
incorporated, thus further facilitating the adaptation of remote monitoring systems by the Canadian Healthcare_x000D_
System. Individuals known to be at risk of specific medical conditions and hospital patients recovering from_x000D_
operations where vital sign monitoring is needed can benefit from remote monitoring in the comfort of their_x000D_
homes. This will in turn reduce the burden incurred to hospitals and healthcare professionals and greatly reduce_x000D_
the associated hospitalization costs., program purpose french : The goal of this research project is to develop computational algorithms for processing ambulatory_x000D_
Electrocardiogram (ECG) signals recorded in real time by a wearable device and accurately measuring the_x000D_
variation in the time intervals between each heartbeat, referred to as heart rate variability (HRV). HRV is an_x000D_
important vital signal used by physicians and other healthcare professionals to monitor and assess the risk of_x000D_
several cardiac and non-cardiac disorders. The main technical challenges this research sets out to overcome_x000D_
involve reliably extracting HRV measurements despite common disturbances present in ambulatory ECG_x000D_
monitoring and efficiently designing the algorithms to operate in real-time to allow for continuous_x000D_
measurements of the subject's current HRV. The partner organization intends to add the developed algorithms_x000D_
to their existing remote monitoring device, which is currently capable of recording ECG amongst other_x000D_
physiological and physical activity signals. By adding the capability of accurate HRV measurement to the_x000D_
wearable device and monitoring platform developed by the industry partner, a crucial vital sign will be_x000D_
incorporated, thus further facilitating the adaptation of remote monitoring systems by the Canadian Healthcare_x000D_
System. Individuals known to be at risk of specific medical conditions and hospital patients recovering from_x000D_
operations where vital sign monitoring is needed can benefit from remote monitoring in the comfort of their_x000D_
homes. This will in turn reduce the burden incurred to hospitals and healthcare professionals and greatly reduce_x000D_
the associated hospitalization costs., agreement title english : Signal-to-noise ratio decision trees for extracting continuous, reliable and real-time heart rate variability (HRV) measurements from an ambulatory ECG monitoring device, agreement title french : Signal-to-noise ratio decision trees for extracting continuous, reliable and real-time heart rate variability (HRV) measurements from an ambulatory ECG monitoring device, agreement number : EGP, agreement value : 25000.0, agreement start date : 2017-11-08, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year (2017-2018 to 2018-2019)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019)., owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada