A new real-time resource-efficient algorithm for ECG denoising, feature extraction and classification-based wearable sensor network

Marhoon, Ali; Hamad, Ali H.

doi:10.1504/ijbet.2015.070032

Cited by 5 publications

(4 citation statements)

References 12 publications

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“…In the Pre-Processing stage, the digital value of the built-in ADC (Successive Approximation Register 12 bit type) in ESP32 microcontroller is calibrated into its original values. The following formula is used to convert the digital code into a millivolt values [13]. Where ADC output= ECG data in digital form, ADC offset = 2060, and Gain =100.…”

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confidence: 99%

“….b In the Filtering stage, an adaptive filter is applied to eliminate several forms of noise that distorting the shape and features of the signal [13]. α is the balance coefficient (default is 0.95).…”

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confidence: 99%

“…α is the balance coefficient (default is 0.95). c. In the Feature Extraction stage, a search algorithm is applied to detect ECG signal features [13]. The basic principle of the algorithm is based on a threshold value where the upper threshold used to find R-peak while lower threshold are used to find S-peak as shown in Fig.…”

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confidence: 99%

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Remote Patient Healthcare surveillance system based real-time vital signs

Alsahi

Marhoon²,

Hamad

2020

alkej

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Today many people suffering from health problems like dysfunction in lungs and cardiac. These problems often require surveillance and follow up to save a patient's health, besides control diseases before progression. For that, this work has been proposed to design and developed a remote patient surveillance system, which deals with 4 medical signs (temperature, SPO2, heart rate, and Electrocardiogram ECG. An adaptive filter has been used to remove any noise from the signal, also, a simple and fast search algorithm has been designed to find the features of ECG signal such as Q,R,S, and T waves. The system performs analysis for medical signs that are used to detected abnormal values. Besides, it sends data to the Base-Station with a data block (ECG signals) that contains the problem. In addition, it generates an alarm to the physicians via ringing up mobile and SMS to overcome the internet disconnected. Also, the system has been designed to achieve precision, low cost, and low energy consumption. Three types of sensors has been used in this work, ECG, SPo2, and temperature sensors. Also, a sim800L GSM module has been used for communications, the main controller in this work is ESP32 unit.

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confidence: 99%

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confidence: 99%

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Remote Patient Healthcare surveillance system based real-time vital signs

Alsahi

Marhoon²,

Hamad

2020

alkej

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“…In 2015, Ali.F and Ali.H [5], developed long term monitoring system that detects the abnormal condition of the elderly at home and performs all daily activities using Shammir Kit, which is considered costly in terms of price.…”

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confidence: 99%

Design Health care system using Raspberry Pi and ESP32

Alsahi¹,

Marhoon²

2020

IJCA

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The focus of this paper is to implement an intelligent health care system based on internet of thing (IOT) for the measurement of the vital signs like pulse rate, temperature, spo2, ECG, using (ESP32 div kit v1) for wireless wearable sensor controller and raspberry pi 3 as a server. With the system proposed, the doctor can save work time to visit the patients that responsible about them and any facilitates monitoring the huge number of patients. The WI-FI technology is utilized as a communication tool to allow transmission the data remotely. The data of patient are sent to the web server to be stored in the database and view the data on the web page anywhere and anytime using smart devices and alert the doctor to any abnormal state. This work with the intelligent health care system provide an efficient medical service ,by collecting and recording the informant that include heart rate, ECG, temperature and spo2 that enable the doctor to monitor his patient with flexibility and confidence .

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