Monitoring electrocardiogram using android based smart phone

Kaushik, Aditi; Sabherwal, Pooja

doi:10.1109/indicon.2015.7443125

Cited by 2 publications

(1 citation statement)

References 4 publications

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“…After feature extraction, its implementation was done in an android environment. Effective results are derived from this proposed research [7]. The research conducted by Salman Ahmed and others in 2015 results the construction of a device that can be used for transferring the data of a patient's vital signs to a remote device wirelessly.…”

Section: Review Of Literaturementioning

confidence: 99%

Implementation of Low Cost Remote Primary Healthcare Services through Telemedicine: Bangladesh Perspectives

Prodhan¹,

Kanti²,

Shaharin³

et al. 2020

IJACSA

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In this paper, we have implemented a low cost primary healthcare service for the remote rural people of Bangladesh. These services were delivered through our developed advanced telemedicine model. The main aim of this paper is to provide basic healthcare service through the developed low cost hardware. We have developed Arduino based low cost hardware's to be used for this telemedicine services. Remote patients of Bangladesh can get the expert doctors opinion without going to the urban areas. We have collected nine vital signs such as electrocardiogram (ECG), oxygen saturation (SPO2), blood pressure, temperature, body position, glucose level, airflow, height, and weight of patients to be used in our model. We have removed unwanted signals from the collected vital signs through several filtering algorithms. Our system was successfully tested with the patients of Marie Stopes Bangladesh Hospital. From our developed model, rural patients can get primary healthcare services from the pharmacy of any remote village of Bangladesh with the assistance of local doctor by using Raspberry PI. Finally, we can say that the deployment of the developed healthcare service will reduce the cost of the telemedicine services and advances the healthcare facilities for the remote people of Bangladesh.

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Section: Review Of Literaturementioning

confidence: 99%

Implementation of Low Cost Remote Primary Healthcare Services through Telemedicine: Bangladesh Perspectives

Prodhan¹,

Kanti²,

Shaharin³

et al. 2020

IJACSA

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Statistical and Learning Aided Classifier for ECG Based Predictive Diagnostic Tool

Bharali¹,

Sarma²,

Sarma

et al. 2017

MATEC Web Conf.

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Abstract. Early diagnosis and classification of long term cardiac signals are crucial issues in the treatment of heart related disorders. The available number of medical professional are not sufficient to deal with the increase patients for which design of certain machine based diagnostics tools have been accepted as a viable option. Typical Electrocardiogram (ECG) machine is helpful for monitoring the heart abnormalities only for short interval of time. Therefore, it becomes necessary to design a system which captures relevant features of the ECG signal for use with certain classifiers. In our proposed system, ECG signal elements like Q, R and S peaks are detected and heart rate estimated using Linear Discriminant Analysis (LDA), Adaptive Linear Discriminant Analysis (ALDA) and Support Vector Machine (SVM). For our work we have been used MIT BIH (Standard Arrhythmia Database).

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Monitoring electrocardiogram using android based smart phone

Cited by 2 publications

References 4 publications

Implementation of Low Cost Remote Primary Healthcare Services through Telemedicine: Bangladesh Perspectives

Implementation of Low Cost Remote Primary Healthcare Services through Telemedicine: Bangladesh Perspectives

Statistical and Learning Aided Classifier for ECG Based Predictive Diagnostic Tool

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