The elderly population is increasing at a rapid rate each year, and with the increase in the elderly population there is a need for better medical assistance and devices. The greatest problem this demographic is facing is the ability to age in place. More elderly people are being placed in nursing homes, assisted living homes, moving in with relatives due to disabilities or fear of disabilities caused by a life threaten event such as heart disease, stroke, falling/fainting, or uncontrolled glucose levels. Falling is the number one leading cause of deaths, injuries and incapacity in the elderly. Stroke is the 3rd leading cause of death in the U.S; it is the 2nd leading cause worldwide. Rapid change in glucose levels is another leading cause of disabilities and deaths. Heart disease is the 2nd leading cause of death in the elderly. These life threatening events can be prevented and if treated early enough can allow the person to have a full recovery and continue to age in place. A device was proposed that could monitor these four life threatening events: heart disease, stroke, falling/fainting and changes in glucose levels. This device will monitor the user continuously. Research was conducted to see what other products are on the market and how they detect these events and how reliable they are for the user. A literature review was performed to understand what other people are doing to solve the aging in place problem. Using this and needs assessment of the elderly, the system architecture for the wrist worn device was designed along with a testing plan and procedure. More research needs to be done in certain areas to better improve solutions and technology in the area aging in place of the elderly. Before this device can bridge some of the gaps between the current issues and the solution the device will have to be tested for several things such as its ability to differentiate between stimulated falling/fainting and fall like activities such as sitting then lying. The orientation and position will be tested to see if the device can actually tell where the person is located. The device will have to be tested against well-known devices and see if it gives similar precise and accurate readings in real time. / Master of Science

Background: Consumer smartwatches have gained attention as mobile health (mHealth) tools able to detect atrial fibrillation (AF) using photoplethysmography (PPG) or a short strip of electrocardiogram (ECG). PPG has limited accuracy due to the movement artifacts, whereas ECG cannot be used continuously, is usually displayed as a single-lead signal and is limited in asymptomatic cases. Objective: DoubleCheck-AF is a validation study of a wrist-worn device dedicated to providing both continuous PPG-based rhythm monitoring and instant 6-lead ECG with no wires. We evaluated its ability to differentiate between AF and sinus rhythm (SR) with particular emphasis on the challenge of frequent premature beats. Methods and Results: We performed a prospective, non-randomized study of 344 participants including 121 patients in AF. To challenge the specificity of the device two control groups were selected: 95 patients in stable SR and 128 patients in SR with frequent premature ventricular or atrial contractions (PVCs/PACs). All ECG tracings were labeled by two independent diagnosis-blinded cardiologists as “AF,” “SR” or “Cannot be concluded.” In case of disagreement, a third cardiologist was consulted. A simultaneously recorded ECG of Holter monitor served as a reference. It revealed a high burden of ectopy in the corresponding control group: 6.2 PVCs/PACs per minute, bigeminy/trigeminy episodes in 24.2% (31/128) and runs of ≥3 beats in 9.4% (12/128) of patients. AF detection with PPG-based algorithm, ECG of the wearable and combination of both yielded sensitivity and specificity of 94.2 and 96.9%; 99.2 and 99.1%; 94.2 and 99.6%, respectively. All seven false-positive PPGbased cases were from the frequent PVCs/PACs group compared to none from the stable SR group (P < 0.001). In the majority of these cases (6/7) cardiologists were able to correct the diagnosis to SR with the help of the ECG of the device (P = 0.012). Conclusions: This is the first wearable combining PPG-based AF detection algorithm for screening of AF together with an instant 6-lead ECG with no wires for manual rhythm confirmation. The system maintained high specificity despite a remarkable amount of frequent single or multiple premature contractions

The ownership and demand for fitness trackers, smartwatches, and wrist-worn deviceshave been increasing globally. These devices offer various features such as measuringphysical activity, sleep monitoring, and health-related measurements like heart rate andheart rate variability using PhotoPlethysmoGraphy (PPG). However, research indicatesthat PPG measurements are less accurate on darker skin compared to lighter skin due to thehigher presence of melanin, a light-absorbing substance in dark skin.This thesis addresses the impact of melanin on the accuracy of heart rate measurements ondifferent skin colors using four commercial smartwatches, Apple Watch Series 5, FitbitCharge 2, Xiaomi Miband 3, and Sony mSafety. The study involves analyzing the accuracyof these smartwatches on individuals with varying skin colors while controlling forexternal factors. The collected data from the smartwatches are compared to a referencesensor that uses electrocardiography (ECG) measurements with electrodes placed aroundthe chest. Three different tests are conducted wearing the devices, with no movement,while walking, and with circular hand motions.The tests were conducted on twelve participants representing the 6 different skin typescategorized using the Fitzpatrick scale. With the presented results in this thesis, it wasconcluded that the 4 smartwatches' measurement accuracy does not seem to be dependenton specific skin types. Ranked in terms of Mean Absolute Error (MAE), the Apple Watchshowed the lowest value, followed by Xiaomi, Fitbit and the mSafety and that the accuracydid not depend on skin color. / Ägandet och efterfrågan av smartklockor har ökat globalt. Dessa enheter erbjuder olikafunktioner som mäter fysisk aktivitet, övervakning av sömn och hälsorelaterade mätningarsom puls och hjärtfrekvensvariabilitet med hjälp av PhotoPlethysmoGraphy (PPG).Forskning har dock visat att PPG-mätningar är mindre noggranna på mörkare hud jämförtmed ljusare hud på grund av den högre närvaron av substansen melanin, ettljusabsorberande ämne.Syftet med detta arbete är att undersöka påverkan av melanin på noggrannheten i pulsmätningar på olika hudfärger med hjälp av fyra kommersiella smartklockor: Apple WatchSeries 5, Fitbit Charge 2, Xiaomi Miband 3 och mSafety av Sony. Arbetet inkluderar enanalys av dessa smartklockors noggrannhet på personer med de olika hudfärger samtidigtsom externa faktorer som kan påverka noggrannheten kontrolleras. De insamlade data frånsmartklockorna jämförs med en referenssensor, Polar band, som använderelektrokardiografimätningar (ECG) med elektroder. Tre olika tester utförs med enheterna,utan rörelse, medan man går och med cirkulära handrörelser.Testerna utfördes på tolv deltagare som representerar olika hudtyper kategoriserade enligtFitzpatrick-skalan. Utifrån de presenterade resultaten i denna avhandling drogs slutsatsenatt de fyra smartklockornas mätnoggrannhet inte verkar vara beroende av specifikahudtyper. Rankade i termer av Mean Absolute Error (MAE) visade Apple Watch det lägstavärdet, följt av Xiaomi, Fitbit och mSafety.