Technology Roadmapping for Stroke Patients Assessment: Hospitalization Phase and Home Monitoring
dc.contributor.advisor | Yanushkevich, Svetlana | |
dc.contributor.advisor | Almekhlafi, Mohammed | |
dc.contributor.author | Yankovyi, Illia | |
dc.contributor.committeemember | Pichardo, Samuel | |
dc.contributor.committeemember | Krishnamurthy, Diwakar | |
dc.contributor.committeemember | Uddin, Gias | |
dc.date | 2024-02 | |
dc.date.accessioned | 2024-01-03T23:54:23Z | |
dc.date.available | 2024-01-03T23:54:23Z | |
dc.date.issued | 2023-12-20 | |
dc.description.abstract | Stroke is a worldwide problem, with over 13.7 million new strokes each year and the second commonest cause of death in the world. If it is not fatal, a stroke can result in permanent disabilities, including paralysis, sensory impairment, slurred speech, loss of vision, and loss of motor functions. Stroke can occur among hospitalized patients and go unnoticed, which represents a missed opportunity. It should be discovered in a timely manner. This is the motivation of this study. The goal of this research is technology roadmapping for video monitoring of stroke patients during hospitalization and partially at rehabilitation time, using e-health. A distinguishing feature of this thesis is discovering future technology needed for monitoring stroke patients. The starting point of this research is an experimental exploration of the problem using a novel technique called experimental evaluation. At its core is a computational intelligence technique (in particular, deep learning network) that produces various technology-centric scenarios. The task of a human expert is to interpret these scenarios according to the technology roadmapping methodology. The primary end users of the proposed results are hospitals. However, an extension for the post-stroke rehabilitation is possible. To achieve this, a monitoring system can be integrated into e-health care based on a self-aware platform. Examples of such applications are reported in the contributed papers. | |
dc.identifier.citation | Yankovyi, I. (2023). Technology roadmapping for stroke patients assessment: hospitalization phase and home monitoring (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. | |
dc.identifier.uri | https://hdl.handle.net/1880/117828 | |
dc.identifier.uri | https://doi.org/10.11575/PRISM/42671 | |
dc.language.iso | en | |
dc.publisher.faculty | Schulich School of Engineering | |
dc.publisher.institution | University of Calgary | |
dc.rights | University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission. | |
dc.subject | stroke | |
dc.subject | deep learning | |
dc.subject | roadmapping | |
dc.subject | motion impairment | |
dc.subject | human motion analysis | |
dc.subject | time series | |
dc.subject | motion tracking | |
dc.subject.classification | Engineering--Biomedical | |
dc.subject.classification | Engineering | |
dc.title | Technology Roadmapping for Stroke Patients Assessment: Hospitalization Phase and Home Monitoring | |
dc.type | master thesis | |
thesis.degree.discipline | Engineering – Biomedical | |
thesis.degree.grantor | University of Calgary | |
thesis.degree.name | Master of Science (MSc) | |
ucalgary.thesis.accesssetbystudent | I do not require a thesis withhold – my thesis will have open access and can be viewed and downloaded publicly as soon as possible. |