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Full-Text Articles in Medicine and Health Sciences
Unveiling Pain: Wearables For Objective Pain Measurement, Hanqing Tang
Unveiling Pain: Wearables For Objective Pain Measurement, Hanqing Tang
Masters Theses
">">Pain perception is a subjective experience that differs significantly among individuals, often leading to inconsistencies in assessment and management. A critical issue within this context is the gender bias in pain evaluation, which contributes to unequal treatment and perpetuates gender inequality within the healthcare system. This thesis presents an in-depth investigation of the problem and proposes the development of a wearable device for objective pain assessment. Physiological parameters — Electrocardiography (ECG) can be collected from cardiac sound signals auscultated by fabrics via nanometre-scale vibrations. Machine learning methods can accurately classify heart rate and acute pain intensity of participants. …
A Cloud Infrastructure For Large Scale Health Monitoring In Older Adult Care Facilities, Uchechukwu Gabriel David
A Cloud Infrastructure For Large Scale Health Monitoring In Older Adult Care Facilities, Uchechukwu Gabriel David
Masters Theses
Technology development in the sub-field of older adult care has always been on the back-burner compared to other healthcare areas. But with increasing life expectancy, this is poised to change. With the increasing older adult population, the current older adult care facilities and personnel are struggling to keep up with demand. Research conducted in the Netherlands [1] found 33,000 older adults were awaiting admission into a home for the elderly showing that demand far exceeds availability. This huge demand for older adult care has resulted in a decrease in the quality of care being provided. A recent study involving older …
Computer Aided Detection Of Oral Lesions On Ct Images, Shaikat Mahmood Galib
Computer Aided Detection Of Oral Lesions On Ct Images, Shaikat Mahmood Galib
Masters Theses
"Oral lesions are important findings on computed tomography images. They are difficult to detect on CT images because of low contrast, arbitrary orientation of objects, complicated topology and lack of clear lines indicating lesions. In this thesis, a fully automatic method to detect oral lesions from dental CT images is proposed to identify (1) Closed boundary lesions and (2) Bone deformation lesions. Two algorithms were developed to recognize these two types of lesions, which cover most of the lesion types that can be found on CT images. The results were validated using a dataset of 52 patients. Using non training …