A Portable Real Time ECG Device for Arrhythmia Detection Using Raspberry Pi

Valliappan, C.A.; Balaji, Advait; Thandayam, Sai Ruthvik; Dhingra, Piyush; Baths, Veeky

doi:10.1007/978-3-319-58877-3_24

Cited by 11 publications

(9 citation statements)

References 9 publications

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“…The FLC control model can be found in Figure 7. The fuzzy system controller contains two inputs (the error e(t) and the error change e'(t)) and one output (the control signal (Voltage) y(t), see Figure 8); the error and the error change are calculated using Equations (12) and (13).…”

Section: Fuzzy Logic Controller For the Lego Mindstorms Ev3mentioning

confidence: 99%

Comparative Study of the Conventional Mathematical and Fuzzy Logic Controllers for Velocity Regulation

Valdez

Castillo

Caraveo

et al. 2019

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Currently, we are in the digital era, where robotics, with the help of the Internet of Things (IoT), is exponentially advancing, and in the technology market we can find multiple devices for achieving these systems, such as the Raspberry Pi, Arduino, and so on. The use of these devices makes our work easier regarding processing information or controlling physical mechanisms, as some of these devices have microcontrollers or microprocessors. One of the main challenges in speed control applications is to make the decision to use a fuzzy logic control (FLC) system instead of a conventional controller system, such as a proportional integral (PI) or a proportional integral-derivative (PID). The main contribution of this paper is the design, integration, and comparative study of the use of these three types of controllers—FLC, PI, and PID—for the speed control of a robot built using the Lego Mindstorms EV3 kit. The root mean square error (RMSE) and the settling time were used as metrics to validate the performance of the speed control obtained with the controllers proposed in this paper.

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Section: Fuzzy Logic Controller For the Lego Mindstorms Ev3mentioning

confidence: 99%

Comparative Study of the Conventional Mathematical and Fuzzy Logic Controllers for Velocity Regulation

Valdez

Castillo

Caraveo

et al. 2019

Axioms

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“…Prikupljeni podaci su se, zatim, slali putem Bluetooth konekcije na PC računar gde se vršila njihova obrada i vizuelizacija. U naučnom radu [5] opisan je merno-akvizicioni sistem koji je primarno realizovan kako bi ga koristili student u toku edukacije. Signali su se prikupljali putem senzora, a do PC računara su se slali putem RS232 interfejsa.…”

Section: Napomenaunclassified

Ulazni Stepen Edukativnog Elektrofiziološkog Akvizicionog Uređaja

Knežević¹

2019

Zbornik radova FTN

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“…Um dispositivo de ECG portátil em tempo real para detecção de arritmia usando Raspberry Pi foi desenvolvido em Valliappan et al (2017) [14]. No trabalho, o CI (Circuito Integrado) AD8232 da SparkFun é utilizado para o condicionamento do sinal de ECG, um conversor de analógico para digital modelo MCP3008 faz a conversão do sinal, e um Raspberry Pi 3 B+ ficou responsável por amostrar e enviar o sinal por meio de WiFi.…”

Section: Introductionunclassified

Aquisição e filtragem de sinais de ECG com Raspberry Pi e conversor AD

2019

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O eletrocardiograma (ECG) avalia a atividade elétrica do coração, e pode ser utilizado para avaliar se a atividade cardíaca está dentro da normalidade ou se há alterações nos músculos e nervos do coração. O ECG consiste na gravação do sinal elétrico gerado pela atividade cardíaca, no entanto quando esse sinal é gravado está sujeito a diversas interferências que causa variação na amplitude e/ou duração do sinal, levando a erros de diagnóstico. Para evitar essas interferências são utilizadas várias técnicas de filtragem, para este fim propomos um sistema de aquisição do sinal de ECG juntamente com uma filtragem digital. O sistema proposto utiliza um Raspberry Pi modelo B para fazer a filtragem digital, no qual implementamos um filtro digital passa-baixas com frequência de corte em 100 Hz do tipo Resposta ao Impulso Finita (RIF), utilizamos ainda uma janela de Hamming. Fizemos uma comparação entre o sinal filtrado e o sinal antes da filtragem e percebemos uma redução significativa na variabilidade do sinal, rendendo assim uma curva mais suave, dessa forma mostrando que foram eliminadas componentes de alta frequência.Palavras-chave: Eletrocardiograma, Filtragem Digital, Raspberry Pi.The electrocardiogram (ECG) evaluates the electrical activity of the heart, and can be used to evaluate if the heart activity is within normal or if there are changes in the muscles and nerves of the heart. The ECG consists of the recording of the electrical signal generated by the cardiac activity, however when this signal is recorded it is subject to several interferences that cause variation in the amplitude and / or duration of the signal, leading to diagnostic errors. To avoid such interference, several filtering techniques are used, for this purpose we propose an ECG signal acquisition system together with digital filtering. The proposed system uses a Raspberry Pi model B to do the digital filtering, in which we implemented a low pass digital filter with a cutoff frequency of 100 Hz of the Finite Impulse Response (FIR) type, we also used a Hamming window. We compared the filtered signal to the signal before filtering and realized a significant reduction in signal variability, thus yielding a smoother curve, thus showing that high frequency components were eliminated.

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A Portable Real Time ECG Device for Arrhythmia Detection Using Raspberry Pi

Cited by 11 publications

References 9 publications

Comparative Study of the Conventional Mathematical and Fuzzy Logic Controllers for Velocity Regulation

Comparative Study of the Conventional Mathematical and Fuzzy Logic Controllers for Velocity Regulation

Ulazni Stepen Edukativnog Elektrofiziološkog Akvizicionog Uređaja

Aquisição e filtragem de sinais de ECG com Raspberry Pi e conversor AD

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