Transmission of ECG signals with android mobile system via bluetooth

Cruz, B. De La; Cuellar, R.; Rojas, Edward O; Molina, Valentín; Robles, Horderlin Vrangel

doi:10.1109/pahce.2015.7173316

Cited by 3 publications

(2 citation statements)

References 4 publications

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“…In [ 9 ], one single lead was digitized with a 10-bit Analog-to-Digital Converter (ADC), processed in the PIC, and sent to the cellphone for viewing. Another basic ECG mobile system was recently implemented with the filtering and conditioning modules for a single lead with instrumentation and operational amplifiers [ 10 ]. The ECG signal digitization was made with an Arduino™ board, and this signal was sent to the cellphone via Bluetooth.…”

Section: Previous Related Workmentioning

confidence: 99%

A Flexible 12-Lead/Holter Device with Compression Capabilities for Low-Bandwidth Mobile-ECG Telemedicine Applications

Pineda-Lopez

Martínez-Fernández

Rojo-Álvarez

et al. 2018

Sensors

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In recent years, a number of proposals for electrocardiogram (ECG) monitoring based on mobile systems have been delivered. We propose here an STM32F-microcontroller-based ECG mobile system providing both long-term (several weeks) Holter monitoring and 12-lead ECG recording, according to the clinical standard requirements for these kinds of recordings, which in addition can yield further digital compression at stages close to the acquisition. The system can be especially useful in rural areas of developing countries, where the lack of specialized medical personnel justifies the introduction of telecardiology services, and the limitations of coverage and bandwidth of cellular networks require the use of efficient signal compression systems. The prototype was implemented using a small architecture, with a 16-bits-per-sample resolution. We also used a low-noise instrumentation amplifier TI ADS1198, which has a multiplexer and an analog-to-digital converter (16 bits and 8 channels) connected to the STM32F processor, the architecture of which incorporates a digital signal processing unit and a floating-point unit. On the one hand, the system portability allows the user to take the prototype in her/his pocket and to perform an ECG examination, either in 12-lead controlled conditions or in Holter monitoring, according to the required clinical scenario. An app in the smartphone is responsible for giving the users a friendly interface to set up the system. On the other hand, electronic health recording of the patients are registered in a web application, which in turn allows them to connect to the Internet from their cellphones, and the ECG signals are then sent though a web server for subsequent and ubiquitous analysis by doctors at any convenient terminal device. In order to determine the quality of the received signals, system testing was performed in the three following scenarios: (1) The prototype was connected to the patient and the signals were subsequently stored; (2) the prototype was connected to the patient and the data were subsequently transferred to the cellphone; (3) the prototype was connected to the patient, and the data were transferred to the cellphone and to the web via the Internet. An additional benchmarking test with expert clinicians showed the clinical quality provided by the system. The proposed ECG system is the first step and paves the way toward mobile cardiac monitors in terms of compatibility with the electrocardiographic practice, including the long-term monitoring, the usability with 12 leads, and the possibility of incorporating signal compression at the early stages of the ECG acquisition.

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Section: Previous Related Workmentioning

confidence: 99%

A Flexible 12-Lead/Holter Device with Compression Capabilities for Low-Bandwidth Mobile-ECG Telemedicine Applications

Pineda-Lopez

Martínez-Fernández

Rojo-Álvarez

et al. 2018

Sensors

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“…For risk analysis, risk prediction, and implementation a device /tool is developing for diagnosing the disease is a common trend nowadays (De la Cruz, Cuellar, Rojas, Molina, & Robles, 2015;Lu, Zhao, Zhao, Li, & Zhang, 2015). Research on developing Smartphone-based risk prediction tools is done by many researchers specially Heart Attack risk prediction was developed (Rotheram-Borus, Tomlinson, Swendeman, Lee, & Jones, 2012).…”

Section: Machine Learning In Medical Sciencementioning

confidence: 99%

Maternal HealthCare Using IoT-Based Integrated Medical Device: Bangladesh Perspective

Kashem,

Ahmed,

Mohammad

2023

Journal of Multidisciplinary Academic and Practice Studies

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Purpose: The main purpose of this study is to develop a low-cost integrated medical device. This device will help investigate the risk levels of maternal patients as well will reduce the cost involved in medical diagnosis for poor countries like Bangladesh, where maternal healthcare is a great concern. Methodology: We proposed and developed an integrated medical device that includes all possible sensors to collect raw data from maternal patients. As soon as the data is collected it will be sent to the cloud for processing. In the cloud, there are a set of algorithms (software) for processing raw data received from the device. After processing and analyzing our system will automatically identify the risk levels of those patients. The software is developed in open source code so that in the future it can be updated by researchers. Results: We developed the system and practically collected raw data from patients and uploaded those data to our cloud system. In the cloud, it was processed and the resultant data were presented in the form of graphs. From these graphs, the risk levels were identified. Limitations: The proposed system is developed for maternal patients only. This system needs to be authorized by the health regulatory authority. To make it cost-effective some expensive sensors were not used. Contribution: The main contribution of this study is to minimize the cost involved in maternal healthcare in poor countries like Bangladesh. This, in turn, controls the death of mother and child by improving maternal healthcare facilities.

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Qualitative analysis of telemetry signals based on data gathered by dedicated mobile application

Wasąg¹,

Plechawska–Wójcik²

2017

jcsi

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The paper presents the analysis of the human heartbeat value under the physical exercise and rest condition. The test group was divided into four groups regarding age and sex. Measurements were performed using a mobile application and a blood pressure monitor. The phone's accuracy with respect to the blood pressure gauge was measured and the statistical significance of differences between age groups, sex and activity was also computed. Measurement inaccuracy varies from 4 to 12%. The mobile application accurately reproduces the pulse during rest.

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Transmission of ECG signals with android mobile system via bluetooth

Cited by 3 publications

References 4 publications

A Flexible 12-Lead/Holter Device with Compression Capabilities for Low-Bandwidth Mobile-ECG Telemedicine Applications

A Flexible 12-Lead/Holter Device with Compression Capabilities for Low-Bandwidth Mobile-ECG Telemedicine Applications

Maternal HealthCare Using IoT-Based Integrated Medical Device: Bangladesh Perspective

Qualitative analysis of telemetry signals based on data gathered by dedicated mobile application

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