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dc.contributor.advisorEklund, Mikael
dc.contributor.authorKhan, Md. Nazrul Islam
dc.date.accessioned2020-02-26T15:11:28Z
dc.date.accessioned2022-03-29T18:04:28Z
dc.date.available2020-02-26T15:11:28Z
dc.date.available2022-03-29T18:04:28Z
dc.date.issued2019-11-01
dc.identifier.urihttps://hdl.handle.net/10155/1122
dc.description.abstractThe present hospital-based health care system will be burdened because of the growing aging population. Aging and stress result in cardiovascular diseases that cost around seventeen million lives globally every year. To control cardiovascular ailments, at-home monitoring of blood pressure is very important which helps diet control and promote medication adherence. The present health monitors are by default bulky, daunting, invasive, and not suitable for home use. The de-facto architecture of such systems entails discrete sensors and analog sub-systems known as the analog front end (AFE) for biosignal acquisition, conditioning, and vital bridging function. Being discrete and analog, signal processing is limited. Besides, with large form factor, component counts and power consumption increase with the constant need for calibration. For more than one century, the non‐invasive measurement of blood pressure has relied on the inflation of pneumatic cuffs around a limb. In addition to being occlusive and thus cumbersome, clinical cuff‐based methods, provide intermittent BP readings, hence impeding the suitable monitoring of short‐term BP regulation mechanisms. Cuff‐based methods may not be a true representative of BP. Therefore, the development of novel technologies that eliminate the use of pneumatic cuffs is justified. In this thesis, I present a highly integrated programmable AFE based biosignal computing platform, named TasDiag. TasDiag is a novel, integrated, remote platform capable of multimodal biosignal computing including non-invasive, continuous, and cuff-less BP estimation based on pulse transit time. Being integrated, and digital, TasDiag is a single board solution with an auto calibration scheme implemented through novel signal processing and computing. The developed system is validated using real-time data from human subjects and subjected to various statistical analyses for performance and accuracy. Test results show TasDiag comply with the Association for Advancement for Medical Instrumentation standard and can replace its industry-standard counterparts.en
dc.description.sponsorshipUniversity of Ontario Institute of Technologyen
dc.language.isoenen
dc.subjectHealth monitoren
dc.subjectBlood pressureen
dc.subjectAnalog front enden
dc.subjectPulse transit timeen
dc.subjectSingle board computeren
dc.titleAn AFE based embedded system for physiological computingen
dc.typeDissertationen
dc.degree.levelDoctor of Philosophy (PhD)en
dc.degree.disciplineElectrical and Computer Engineeringen


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