The Improvement of Phonocardiograph Signal (PCG) Representation Through the Electronic Stethoscope

Sumarna,; Astono, Juli; Purwanto, Agus; Agustika, Dyah Kurniawati

doi:10.11591/eecsi.v4.1008

Cited by 4 publications

(1 citation statement)

References 6 publications

(6 reference statements)

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“…However, CWT has heavy computation. Sumarna, et al further carried out improvement on the PCG signal for electronic stethoscope by analyzing the signal using fast fourir transform (FFT) and further applied it on the making of reliable instrumentation [13]. In addition, Olga Szymanowska et al, created an electronic stethoscope connected with a Personal Computer (PC) with analyzable sampling and simultaneous monitoring of signals.…”

Section: Introductionmentioning

confidence: 99%

Electronic Stethoscope Design with IoT (Internet of Things)-based Disease Symptom Detection

Hamzah

Setioningsih

Sumber

et al. 2022

Indones.J.electronic.electromed.med.inf

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Auscultation is a technique or method most often used by medical personnel in the initial examination of patients. One way is to use a stethoscope. However, this method has its drawbacks because the diagnosis is carried out subjectively and cannot be relied on with the accuracy to diagnose the symptoms of heart defects. Thus, the purpose of this study is to create an IoT system for electronic stethoscopes with BPM value output and make analog filters to eliminate noise interference which was a major obstacle in previous studies. The contribution to this study is to make it easier for medical users to monitor vital conditions, namely BPM remotely and produce BPM values in real-time. The method used in this study was to use a mic condensor placed on the patient's chest to detect pressure changes that occurred. This change in pressure causes a change in the voltage output value on the condensor mic. Output dari mic condenser masuk dan diproses di rangkaian PSA. Output sinyal dari PSA masuk ke mikrokontroler yang telah diprogram. Hasil yang dipeoleh dari pengukuran mengasilkan nilai error pengukuran nilai BPM dari 5 responden dan diperoleh nilai error yang dihasilkan dari responden 1 diperoleh error sebesar 0.33 BPM, responden 2 diperoleh nilai error sebesar 0,67 BPM, responden 3 memiliki nilai error sebesar 0,5 BPM, responden 4 nilai error sebesar 0,67 dan responden 5 mempunyai nilai error sebesar 0,67 BPM. The results of the statistical test were also obtained P-Value>0.05 which explained that the resulting value did not have a significant difference and could be used for medical purposes. This research can help make it easier for doctors to analyze and diagnose symptoms of heart defects because this system is equipped with the detection of disease symptoms.

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Section: Introductionmentioning

confidence: 99%

Electronic Stethoscope Design with IoT (Internet of Things)-based Disease Symptom Detection

Hamzah

Setioningsih

Sumber

et al. 2022

Indones.J.electronic.electromed.med.inf

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Towards cyber-biosecurity by design: an experimental approach to Internet-of-Medical-Things design and development

Elgabry

2023

Crime Sci

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The introduction of the internet and the proliferation of internet-connected devices (IoT) enabled knowledge sharing, connectivity and global communications. At the same time, these technologies generated a crime harvest as security was overlooked. The Internet-of-Medical-Things (IoMT) generates biological information and is transforming healthcare through the introduction of internet-connected medical-grade devices that are integrated with wider-scale health networks to improve patients’ health. Many innovative ideas arise from academia; however, there is a lack of support in medical device regulation. The implementation of the current regulatory framework is limited to security risk assessment and guidance. Unfortunately, premarket risk-management requirements of current regulation do not include crime risks and a more predictive approach could help fill this gap. Crime science, or the perspective of crime as an event that can be influenced directly by its immediate environment, may encourage the biotechnology industry to design-in security and crime out. In this article, I provide a point of view of an early career researcher and medical device developer navigating the medical device regulatory pathway for the first time. I narrow the focus of this article to an assessment that is specific to current UK provisions and acknowledge the limited scope. In response to the ongoing changes in the current regulatory framework of the UK, I propose a new secure by design mechanism that can be employed by early career developers earlier in the development process of a product. Such a model can be used to systematically consider security design in devices and to understand and address potential crime risks ahead of their widespread use.

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Phonocardiography Signals Compression with Deep Convolutional Autoencoder for Telecare Applications

2020

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Phonocardiography (PCG) signals that can be recorded using the electronic stethoscopes play an essential role in detecting the heart valve abnormalities and assisting in the diagnosis of heart disease. However, it consumes more bandwidth when transmitting these PCG signals to remote sites for telecare applications. This paper presents a deep convolutional autoencoder to compress the PCG signals. At the encoder side, seven convolutional layers were used to compress the PCG signals, which are collected on the patients in the rural areas, into the feature maps. At the decoder side, the doctors at the remote hospital use the other seven convolutional layers to decompress the feature maps and reconstruct the original PCG signals. To confirm the effectiveness of our method, we used an open accessed dataset on PHYSIONET. The achievable compress ratio (CR) is 32 when the percent root-mean-square difference (PRD) is less than 5%.

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The Improvement of Phonocardiograph Signal (PCG) Representation Through the Electronic Stethoscope

Cited by 4 publications

References 6 publications

Electronic Stethoscope Design with IoT (Internet of Things)-based Disease Symptom Detection

Electronic Stethoscope Design with IoT (Internet of Things)-based Disease Symptom Detection

Towards cyber-biosecurity by design: an experimental approach to Internet-of-Medical-Things design and development

Phonocardiography Signals Compression with Deep Convolutional Autoencoder for Telecare Applications

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