Internet of Medical Things for Cardiac Monitoring: Paving the Way to 5G Mobile Networks

Health and medical care are considered as one of the most fascinating applications that can fully benefit from the IoT deployment. In this work, we built a prototype of the Internet of Medical Things (IMedT) for monitoring cardiac activity in the form of phonocardiograph (PCG) signal. The prototype comprises of an agent and a manager. An agent runs a special task to collect heart sound signals and conditioning the signals. A manager, on the other hand, performs some tasks including: (i) gathering signal from some an agent or sensor node, (ii) operated as a web server to make the data available online locally and globally for doctors in order that the data can be accessed anywhere with certain uthorization schemes, (iii) it is equipped with ability to do data mirroring to a data center in the cloud system in such a way that the most updated file can be copied to the targeted location to ensure the authorized healthcare providers and doctors anywhere around the globe to get the latest heart sound data for cardiac monitoring and diagnosing. Some issues regarding future development of the IMedT system were presented including smart diagnosis capability, security issues, and extension to the 6LoPAN as well as its compliance to the emerging 5G mobile networks

Auskultasi Jarak Jauh untuk Pengukuran dan Perekaman Sinyal Suara Jantung

In 2014, the Sample Registration System (SRS) released a survey showing that heart diseases can be categorized as the second highest non-communicable disease in Indonesia. The percentage is 12.9%. In this work, a tele-auscultation system for heart sound signals was built to transmit the signal over the global Internet networks and store them in a Cloud storage. Thus, the system allows measurement of heart sound signal for the rural area where the presence of expert is very scarce and helps the expert doctors to perform clinical analysis anywhere. Our examination showed that the system exhibited the average transmission delay of 5.68 second and data lost of only less than 1% for transmission of 1 heart sound signal. On the other hand, examination using two heart sound signals transmitted simultaneously showed that it displayed a smaller average of transmission delay. It may be caused by the measurement of the transmission delay as well as data lost that is depended on the traffic in the internet networks. Moreover, correlation of the heart sound signals before and after transmission showed a strong correlation where the correlation value is very close to 1 at, indicating that there is a strong similarity between the two signals

A Novel and Low Processing Time ECG Security Method Suitable for Sensor Node Platforms

An anonymisation of electrocardiogram (ECG) signal is essential during the distribution and storage in a public repository. In this paper, we propose a novel low processing time ECG anonymisation method based on the fast Fourier transform (FFT) algorithm that is suitable for sensor node platforms. The proposed framework was developed to address two major constraints in the Internet of Medical Thing environment, i.e., immediate need for securing ECG signal and efficient method for overcoming physical limitation of sensor nodes. Performance evaluation by way of computer simulation over normal and abnormal ECG signals showed that the proposed framework was able to conceal fiducial and non-fiducial features of the ECG signals. Additionally, it showed that the proposed framework offered flexibility in determining the secret key length of the anonymised ECG signal. Strong cross-correlation indicated close similarity between the original and the reconstructed ECG signals implying lossless reconstruction of the original ECG signal. Furthermore, the proposed method achieved a lower processing time security algorithm as compared with the recently proposed wavelet based anonymisation methods

Advanced sensors technology survey

This project assesses the state-of-the-art in advanced or 'smart' sensors technology for NASA Life Sciences research applications with an emphasis on those sensors with potential applications on the space station freedom (SSF). The objectives are: (1) to conduct literature reviews on relevant advanced sensor technology; (2) to interview various scientists and engineers in industry, academia, and government who are knowledgeable on this topic; (3) to provide viewpoints and opinions regarding the potential applications of this technology on the SSF; and (4) to provide summary charts of relevant technologies and centers where these technologies are being developed

Wireless sensor network for health monitoring

Wireless Sensor Network (WSN) is becoming a significant enabling technology for a wide variety of applications. Recent advances in WSN have facilitated the realization of pervasive health monitoring for both homecare and hospital environments. Current technological advances in sensors, power-efficient integrated circuits, and wireless communication have allowed the development of miniature, lightweight, low-cost, and smart physiological sensor nodes. These nodes are capable of sensing, processing, and communicating one or more vital signs. Furthermore, they can be used in wireless personal area networks (WPANs) or wireless body sensor networks (WBSNs) for health monitoring. Many studies were performed and/or are under way in order to develop flexible, reliable, secure, real-time, and power-efficient WBSNs suitable for healthcare applications. To efficiently control and monitor a patient’s status as well as to reduce the cost of power and maintenance, IEEE 802.15.4/ZigBee, a communication standard for low-power wireless communication, is developed as a new efficient technology in health monitoring systems. The main contribution of this dissertation is to provide a modeling, analysis, and design framework for WSN health monitoring systems. This dissertation describes the applications of wireless sensor networks in the healthcare area and discusses the related issues and challenges. The main goal of this study is to evaluate the acceptance of the current wireless standard for enabling WSNs for healthcare monitoring in real environment. Its focus is on IEEE 802.15.4/ZigBee protocols combined with hardware and software platforms. Especially, it focuses on Carrier Sense Multiple Access with Collision Avoidance mechanism (CSMA/CA) algorithms for reliable communication in multiple accessing networks. The performance analysis metrics are established through measured data and mathematical analysis. This dissertation evaluates the network performance of the IEEE 802.15.4 unslotted CSMA/CA mechanism for different parameter settings through analytical modeling and simulation. For this protocol, a Markov chain model is used to derive the analytical expression of normalized packet transmission, reliability, channel access delay, and energy consumption. This model is used to describe the stochastic behavior of random access and deterministic behavior of IEEE 802.15.4 CSMA/CA. By using it, the different aspects of health monitoring can be analyzed. The sound transmission of heart beat with other smaller data packet transmission is studied. The obtained theoretical analysis and simulation results can be used to estimate and design the high performance health monitoring systems

Phonocardiogram: evaluate and construction

Este artículo presenta la construcción de un instrumento para monitorizar la frecuencia cardíaca (FC), caracterizado por el bajo coste material de su producción. Para verificar la aplicabilidad del Fonocardiograma (FCG) se tomó la FC de nueve (9) sujetos experimentales con a través de dos sistemas: el FCG y el monitor de FC de la marca Polar inc. (Finlandia) modelo RS 800 Cx HR. A continuación, se compraron los resultados. A las nueve (9) personas (4 hombres y 5 mujeres) investigadas se les midió la FC en posición sentada y en posición supina (Zuttin, R. S., Moreno, M. A., César, M. C., Martins, L. E. B., Catai, A. M., & Silva, E., 2008) durante 5 minutos (Vanderlei, L.C.M., Silva, R.A., Pastre, C.M., Azevedo, F.M. & Godoy, M.F., 2008). Se obtuvo una correlación de r = 0,982 para la posición supina y de r = 0,794 para la posición sentada, ambas con p <0,05. Se conseja la construcción de este instrumento para la enseñanza y el aprendizaje de la monitorización de la FC, así como su importancia como método didáctico para la comprensión de la auto-regulación de los ritmos internos.This paper presents the development of a test to monitor heart rate (HR) which is characterized by low cost material expended in its production. In order to verify the applicability of the phonocardiogram (FCG), it was compared with a HR monitor from Polar Inc (Finland) model RS 800 Cx HR in nine (9) subjects (4 males and 5 females). The measures were made in the sitting and supine position (Zuttin, R. S., Moreno, M. A., César, M. C., Martins, L. E. B., Catai, A. M., & Silva, E.,2008) during 5 minutes (Vanderlei, L.C.M., Silva, R.A., Pastre, C.M., Azevedo, F.M. & Godoy, M.F., 2008). A correlation of r = 0.982 to supine position and of r = 0.794 to sitting position was obtained, both with p <0.05. The building of this instrument is suggested to teaching and learning of the HR monitoring, and its importance is demonstrated as a method for understanding the autorregularion and the internal rhythms of body.Facultad de Humanidades y Ciencias de la Educació

Telemedicine

Telemedicine is a rapidly evolving field as new technologies are implemented for example for the development of wireless sensors, quality data transmission. Using the Internet applications such as counseling, clinical consultation support and home care monitoring and management are more and more realized, which improves access to high level medical care in underserved areas. The 23 chapters of this book present manifold examples of telemedicine treating both theoretical and practical foundations and application scenarios

Review and Analysis of mHealth Applications : Development and Evaluation of a Heart Diseases Self-Management App

Este trabajo tiene dos objetivos principales. El primero es realizar una revisión de las apps móviles existentes centradas en enfermedades o condiciones no comunicables, especialmente en el campo de la cardiología. Esta revisión se basó en las condiciones más prevalentes, las enfermedades líderes en mortalidad y las enfermedades cardíacas. Fue además complementada con una revisión de Sistemas de Ayuda a la Decisión Móviles (SADM). El segundo objetivo es el diseño, creación y desarrollo de una app móvil innovadora en el campo de la cardiología, con el objetivo de copar un hueco comercial encontrado en la revisión anterior. Para llevar a cabo dicho objetivo, varios estudios fueron realizados para solucionar los problemas encontrados. La experiencia aprendida es compartida con investigadores y desarrolladores con el objetivo de ayudarles en el proceso de creación de apps de mSaludDepartamento de Teoría de la Señal y Comunicaciones, e Ingeniería Telemátic

Intelligent Biosignal Processing in Wearable and Implantable Sensors

This reprint provides a collection of papers illustrating the state-of-the-art of smart processing of data coming from wearable, implantable or portable sensors. Each paper presents the design, databases used, methodological background, obtained results, and their interpretation for biomedical applications. Revealing examples are brain–machine interfaces for medical rehabilitation, the evaluation of sympathetic nerve activity, a novel automated diagnostic tool based on ECG data to diagnose COVID-19, machine learning-based hypertension risk assessment by means of photoplethysmography and electrocardiography signals, Parkinsonian gait assessment using machine learning tools, thorough analysis of compressive sensing of ECG signals, development of a nanotechnology application for decoding vagus-nerve activity, detection of liver dysfunction using a wearable electronic nose system, prosthetic hand control using surface electromyography, epileptic seizure detection using a CNN, and premature ventricular contraction detection using deep metric learning. Thus, this reprint presents significant clinical applications as well as valuable new research issues, providing current illustrations of this new field of research by addressing the promises, challenges, and hurdles associated with the synergy of biosignal processing and AI through 16 different pertinent studies. Covering a wide range of research and application areas, this book is an excellent resource for researchers, physicians, academics, and PhD or master students working on (bio)signal and image processing, AI, biomaterials, biomechanics, and biotechnology with applications in medicine

WOFEX 2021 : 19th annual workshop, Ostrava, 1th September 2021 : proceedings of papers

The workshop WOFEX 2021 (PhD workshop of Faculty of Electrical Engineer-ing and Computer Science) was held on September 1st September 2021 at the VSB – Technical University of Ostrava. The workshop offers an opportunity for students to meet and share their research experiences, to discover commonalities in research and studentship, and to foster a collaborative environment for joint problem solving. PhD students are encouraged to attend in order to ensure a broad, unconfined discussion. In that view, this workshop is intended for students and researchers of this faculty offering opportunities to meet new colleagues.Ostrav