Efficient PPG Signal Acquisition for Atrial Fibrillation Screening with Wearable Devices

Rivera, Daniel Moisés Sáez; Castineira, Diego; Veiga, César; Rodríguez-Andina, Juan J.; Fariña, José; García, Enrique

doi:10.1109/iecon.2018.8592817

Cited by 1 publication

(1 citation statement)

References 12 publications

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“…Screening tests for heart disease, stroke, and other diseases are visually appealing. 9 To prevent potentially fatal events, diseases should be diagnosed at early stages. To achieve this important, the optimal strategy for screening tests should be determined.…”

Section: Introductionmentioning

confidence: 99%

An integrated methodology to control the risk of cardiovascular disease in patients with hypertension and type 1 diabetes

Shetaban

Esfahani

Saghaei

et al. 2020

Computational Intelligence

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Today, air pollution, smoking, use of fatty acids and ready-made foods, and so on, have exacerbated heart disease. Therefore, controlling the risk of such diseases can prevent or reduce their incidence. The present study aimed at developing an integrated methodology including Markov decision processes (MDP) and genetic algorithm (GA) to control the risk of cardiovascular disease in patients with hypertension and type 1 diabetes. First, the efficiency of GA is evaluated against Grey Wolf optimization (GWO) algorithm, and then, the superiority of GA is revealed. Next, the MDP is employed to estimate the risk of cardiovascular disease. For this purpose, model inputs are first determined using a validated micro-simulation model for screening cardiovascular disease developed at Tehran University of Medical Sciences, Iran by GA. The model input factors are then defined accordingly and using these inputs, three risk estimation models are identified. The results of these models support WHO guidelines that provide medicine with a high discount to patients with high expected LYs. To develop the MDP methodology, policies should be adopted that work well despite the difference between the risk model and the actual risk. Finally, a sensitivity

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Section: Introductionmentioning

confidence: 99%