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221	NONINVASIVE MEASUREMENT OF HEARTRATE, RESPIRATORY RATE, AND BLOOD OXYGENATION THROUGH WEARABLE DEVICES Jason David Ummel (10724028) 29 April 2021 (has links) <p>The last two decades have shown a boom in the field of wearable sensing technology. Particularly in the consumer industry, growing trends towards personalized health have pushed new devices to report many vital signs, with a demand for high accuracy and reliability. The most common technique used to gather these vitals is photoplethysmography or PPG. PPG devices are ideal for wearable applications as they are simple, power-efficient, and can be implemented on almost any area of the body. Traditionally PPGs were utilized for capturing just heart rate, however, recent advancements in hardware and digital processing have led to other metrics including respiratory rate (RR) and peripheral oxygen saturation (SpO2), to be reported as well. Our research investigates the potential for wearable devices to be used for outpatient apnea monitoring, and particularly the ability to detect opioid misuse resulting in respiratory depression. Ultimately, the long-term goal of this work is to develop a wearable device that can be used in the rehabilitation process to ensure both accountability and safety of the wearer. This document details contributions towards this goal through the design, development, and evaluation of a device called “Kick Ring”. Primarily, we investigate the ability of Kick Ring to record heartrate (HR), RR, and SpO2. Moreover, we show that the device can calculate RR in real time and can provide an immediate indication of abnormal events such as respiratory depression. Finally, we explore a novel method for reporting apnea events through the use of several PPG characteristics. Kick Ring reliably gathers respiratory metrics and offers a combination of features that does not exist in the current wearables space. These advancements will help to move the field forward, and eventually aid in early detection of life-threatening events.</p> Biomedical Instrumentation Medical Devices Rehabilitation Engineering Flexible Manufacturing Systems Engineering Instrumentation Photoplethysmographic Signals photoplethysmography photoplethysmography sensor design photoplethysmography signal recording wearable sensors Fitness tracker Smart ring Smart Watches electrocardiograms blood oxygenation respiratory rate respiratory sinus arrhythmia Real-Time Respiration Rate opioid use disorder opioid use disorder treatment settings apnea hypoxia syndrome apnea detection sensor
222	Development and Evaluation of a Machine Vision System for Digital Thread Data Traceability in a Manufacturing Assembly Environment Alexander W Meredith (15305698) 29 April 2023 (has links) <p>A thesis study investigating the development and evaluation of a computer vision (CV) system for a manufacturing assembly task is reported. The CV inference results are compared to a Manufacturing Process Plan and an automation method completes a buyoff in the software, Solumina. Research questions were created and three hypotheses were tested. A literature review was conducted recognizing little consensus of Industry 4.0 technology adoption in manufacturing industries. Furthermore, the literature review uncovered the need for additional research within the topic of CV. Specifically, literature points towards more research regarding the cognitive capabilities of CV in manufacturing. A CV system was developed and evaluated to test for 90% or greater confidence in part detection. A CV dataset was developed and the system was trained and validated with it. Dataset contextualization was leveraged and evaluated, as per literature. A CV system was trained from custom datasets, containing six classes of part. The pre-contextualization dataset and post-contextualization dataset was compared by a Two-Sample T-Test and statistical significance was noted for three classes. A python script was developed to compare as-assembled locations with as-defined positions of components, per the Manufacturing Process Plan. A comparison of yields test for CV-based True Positives (TPs) and human-based TPs was conducted with the system operating at a 2σ level. An automation method utilizing Microsoft Power Automate was developed to complete the cognitive functionality of the CV system testing, by completing a buyoff in the software, Solumina, if CV-based TPs were equal to or greater than human-based TPs.</p> Automation engineering Flexible manufacturing systems Industrial engineering Manufacturing safety and quality Knowledge representation and reasoning Computer vision Object detection and classification object detection and tracking Smart Manufacturing Systems MES system Smart Manufacturing Approach Quality engineering Manufacturing automation systems manufacturing automation Cognitive Systems Engineering cognitive system computer vision machine vision manufacturing execution system robotic process automation Digital Thread (DT) Digital Thread digital twin approach manufacturing assembly assembly quality manufacturing traceability advanced manufacturing advanced quality control Quality 4.0 Industry 4.0 Industry 5.0 Quality 5.0 Human Machine Interactions

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NONINVASIVE MEASUREMENT OF HEARTRATE, RESPIRATORY RATE, AND BLOOD OXYGENATION THROUGH WEARABLE DEVICES

Development and Evaluation of a Machine Vision System for Digital Thread Data Traceability in a Manufacturing Assembly Environment