{"id":2629,"date":"2020-08-14T21:52:36","date_gmt":"2020-08-14T21:52:36","guid":{"rendered":"https:\/\/fs-s-wpmu-03.facsci.ualberta.ca\/ammi\/?page_id=2629"},"modified":"2020-08-19T22:04:42","modified_gmt":"2020-08-19T22:04:42","slug":"continuous-heart-anomaly-detection-system-with-motion-artifacts-suppression","status":"publish","type":"page","link":"https:\/\/spaces.facsci.ualberta.ca\/ahci\/projects\/medical-projects\/continuous-heart-anomaly-detection-system-with-motion-artifacts-suppression\/","title":{"rendered":"Continuous Heart Anomaly Detection System with Motion Artifacts Suppression"},"content":{"rendered":"

Cardiovascular diseases (CVDs) are the number one cause of death globally. An estimated 17.9 million people died from CVDs in 2016, representing 31% of all global deaths. Therefore, many products that monitors patient\u2019s heart conditions have been introduced on the market such as: Apple Watch, QardioMD, and Astroskin. Most of these powerful devices can record patient\u2019s biometric signals at rest. Devices such as Atroskin for example, can measure 3 lead electrocardiogram (ECG), breathing (upper and lower chest), body temperature, blood pressure, and acceleration. The main goal of this thesis is to develop a cardiac monitoring system that can detect heart anomalies continuously during normal activities such as resting, walking, cycling, running. This patient-speci\ufb01c monitoring systems starts by learning the patient\u2019s ECG in normal cardiac state creating a patient speci\ufb01c neural model. As data get acquired and compensated from artifacts created by body motion, it can then detect in real-time departures form normality that are only due to cardiac anomalies. In order to do so, the system use a LSTM neural network that combines ECG with accelerometer data to detect departure from the normal patient spe-ci\ufb01c model. By fusing this information, one can reduce false positive created by motion artifacts and allow true continuous heart anomaly detection.<\/p>\n

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For more information on this project please communicate with Hong Zu Li<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Cardiovascular diseases (CVDs) are the number one cause of death globally. An estimated 17.9 million people died from CVDs in 2016, representing 31% of all global deaths. Therefore, many products that monitors patient\u2019s heart conditions have been introduced on the market such as: Apple Watch, QardioMD, and Astroskin. Most of these powerful devices can record<\/p>\n

Read More<\/a><\/p>\n","protected":false},"author":4,"featured_media":0,"parent":1617,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-2629","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/spaces.facsci.ualberta.ca\/ahci\/wp-json\/wp\/v2\/pages\/2629","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/spaces.facsci.ualberta.ca\/ahci\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/spaces.facsci.ualberta.ca\/ahci\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/spaces.facsci.ualberta.ca\/ahci\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/spaces.facsci.ualberta.ca\/ahci\/wp-json\/wp\/v2\/comments?post=2629"}],"version-history":[{"count":2,"href":"https:\/\/spaces.facsci.ualberta.ca\/ahci\/wp-json\/wp\/v2\/pages\/2629\/revisions"}],"predecessor-version":[{"id":2696,"href":"https:\/\/spaces.facsci.ualberta.ca\/ahci\/wp-json\/wp\/v2\/pages\/2629\/revisions\/2696"}],"up":[{"embeddable":true,"href":"https:\/\/spaces.facsci.ualberta.ca\/ahci\/wp-json\/wp\/v2\/pages\/1617"}],"wp:attachment":[{"href":"https:\/\/spaces.facsci.ualberta.ca\/ahci\/wp-json\/wp\/v2\/media?parent=2629"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}