Wearable and Implantable Wireless Sensor Network Solutions for Healthcare Monitoring

Wireless sensor network (WSN) technologies are considered one of the key research areas in computer science and the healthcare application industries for improving the quality of life. The purpose of this paper is to provide a snapshot of current developments and future direction of research on wearable and implantable body area network systems for continuous monitoring of patients. This paper explains the important role of body sensor networks in medicine to minimize the need for caregivers and help the chronically ill and elderly people live an independent life, besides providing people with quality care. The paper provides several examples of state of the art technology together with the design considerations like unobtrusiveness, scalability, energy efficiency, security and also provides a comprehensive analysis of the various benefits and drawbacks of these systems. Although offering significant benefits, the field of wearable and implantable body sensor networks still faces major challenges and open research problems which are investigated and covered, along with some proposed solutions, in this paper

A Flexible and Scalable Architecture for Real-Time ANT+ Sensor Data Acquisition and NoSQL Storage

Wireless Personal or Body Area Networks (WPANs or WBANs) are the main mechanisms to develop healthcare systems for an ageing society. Such systems offer monitoring, security, and caring services by measuring physiological body parameters using wearable devices. Wireless sensor networks allow inexpensive, continuous, and real-time updates of the sensor data, to the data repositories via an Internet. A great deal of research is going on with a focus on technical, managerial, economic, and social health issues. The technical obstacles, which we encounter, in general, are better methodologies, architectures, and context data storage. Sensor communication, data processing and interpretation, data interchange format, data transferal, and context data storage are sensitive phases during the whole process of body parameter acquisition until the storage. ANT+ is a proprietary (but open access) low energy protocol, which supports device interoperability by mutually agreeing upon device profile standards. We have implemented a prototype, based upon ANT+ enabled sensors for a real-time scenario. This paper presents a system architecture, with its software organization, for real-time message interpretation, event-driven based real-time bidirectional communication, and schema flexible storage. A computer user uses it to acquire and to transmit the data using a Windows service to the context server

Connectivity for Healthcare and Well-Being Management: Examples from Six European Projects

Technological advances and societal changes in recent years have contributed to a shift in traditional care models and in the relationship between patients and their doctors/carers, with (in general) an increase in the patient-carer physical distance and corresponding changes in the modes of access to relevant care information by all groups. The objective of this paper is to showcase the research efforts of six projects (that the authors are currently, or have recently been, involved in), CAALYX, eCAALYX, COGKNOW, EasyLine+, I2HOME, and SHARE-it, all funded by the European Commission towards a future where citizens can take an active role into managing their own healthcare. Most importantly, sensitive groups of citizens, such as the elderly, chronically ill and those suffering from various physical and cognitive disabilities, will be able to maintain vital and feature-rich connections with their families, friends and healthcare providers, who can then respond to, and prevent, the development of adverse health conditions in those they care for in a timely manner, wherever the carers and the people cared for happen to be

Towards fostering the role of 5G networks in the field of digital health

A typical healthcare system needs further participation with patient monitoring, vital signs sensors and other medical devices. Healthcare moved from a traditional central hospital to scattered patients. Healthcare systems receive help from emerging technology innovations such as fifth generation (5G) communication infrastructure: internet of things (IoT), machine learning (ML), and artificial intelligence (AI). Healthcare providers benefit from IoT capabilities to comfort patients by using smart appliances that improve the healthcare level they receive. These IoT smart healthcare gadgets produce massive data volume. It is crucial to use very high-speed communication networks such as 5G wireless technology with the increased communication bandwidth, data transmission efficiency and reduced communication delay and latency, thus leading to strengthen the precise requirements of healthcare big data utilities. The adaptation of 5G in smart healthcare networks allows increasing number of IoT devices that supplies an augmentation in network performance. This paper reviewed distinctive aspects of internet of medical things (IoMT) and 5G architectures with their future and present sides, which can lead to improve healthcare of patients in the near future

A Context-Aware mHealth System for Online Physiological Monitoring in Remote Healthcare

Physiological or biological stress is an organism’s response to a stressor such as an environmental condition or a stimulus. The identification of physiological stress while performing the activities of daily living is an important field of health research in preventive medicine. Activities initiate a dynamic physiological response that can be used as an indicator of the overall health status. This is especially relevant to high risk groups; the assessment of the physical state of patients with cardiovascular diseases in daily activities is still very difficult. This paper presents a context-aware telemonitoring platform, IPM-mHealth, that receives vital parameters from multiple sensors for online, real-time analysis. IPM-mHealth provides the technical basis for effectively evaluating patients’ physiological conditions, whether inpatient or at home, through the relevance between physical function and daily activities. The two core modules in the platform include: 1) online activity recognition algorithms based on 3-axis acceleration sensors and 2) a knowledge-based, conditional-reasoning decision module which uses context information to improve the accuracy of determining the occurrence of a potentially dangerous abnormal heart rate. Finally, we present relevant experiments to collect cardiac information and upper-body acceleration data from the human subjects. The test results show that this platform has enormous potential for use in long-term health observation, and can help us define an optimal patient activity profile through the automatic activity analysis

Strategic Intelligence Monitor on Personal Health Systems (SIMPHS): Report on Typology/Segmentation of the PHS Market

This market segmentation reports for Personal Health Systems (PHS) describes the methodological background and illustrates the principles of classification and typology regarding different fragments forming this market. It discusses different aspects of the market for PHS and highlights challenges towards a stringent and clear-cut typology or defining market segmentation. Based on these findings a preliminary hybrid typology and indications and insights are created in order to be used in the continuation of the SIMPHS project. It concludes with an annex containing examples and cases studies.JRC.DDG.J.4-Information Societ

M2M 원격심전도를 위한 스케일러블 코딩 및 링크 적응기법

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2017. 2. 신현식.Medical telemetry is one of the most demanding applications in recent wearable computing era. Telecardiology, which uses the power of telecommunications for the remote diagnosis and treatment of heart diseases, is one of the key telemetry applications that leverages IoT-based technologies to improve patient care. Based on recent advances in wearable sensors and telecommunication technologies, this thesis proposes a universal platform for wearable daily cardiac monitoring service. First, we propose an adaptive framework for layered representation and transmission of ECG (electrocardiography) data that can accommodate a time-varying wireless channel on cellular networks. The representation, combined with the layer-based earliest deadline first (LB-EDF) scheduler, ensures that the perceptual quality of the reconstructed ECG signal does not degrade abruptly under severe channel conditions and that the available bandwidth is utilized efficiently. Simulation shows that the proposed approach significantly improves the perceptual quality of the ECG signal reconstructed at the remote monitoring station. Then we extend the proposed adaptive framework to support time-critical medical applications. In fact, the use of wireless technologies has been avoided for medical situations that demand instantaneous cardiac monitoring because of their considerable and nondeterministic end-to-end latency. This thesis introduces a universal platform for machine-to-machine (M2M) telecardiology over cellular networks, along with a novel conservative modulation and coding scheme to minimize and stabilize the delay down to 10 ms of ultra-low latency level, incurred during the process of ECG transmission over a wireless medium while maintaining the desired level of ECG pattern quality required for improving the chance of its interpretation. Machine-type communication (MTC) system is adopted for the delivery of patient ECG data to benefit from its inherent reliability, pervasiveness, security, and performance of 4G long term evolution (LTE) technologies with reduced cost and enhanced coverage. Extensive evaluations indicate that the proposed system provides a sufficient level of service for medical-grade instantaneous ECG monitoring in significantly deteriorated channel conditions.1.Introduction 1 1.1 Motivation and Objectives 1 1.2 Research Contributions 6 1.3 Orgranization of Thesis 8 2 Background and Related Works 10 2.1 ECG Generals 10 2.2 Wireless ECG 15 2.3 Wireless Medium for Telecardiology 20 2.3.1 Wireless Personal Area Networks 21 2.3.2 Wireless Local Area Networks 22 2.3.3 Cellular Networks 23 3 Scalable ECG Transmission over Cellular Networks 24 3.1 System Architecture 26 3.2 Scalable Representation of ECG Data 27 3.3 ARQ-Based Error Control Using LB-EDF 30 3.4 Performance of Wireless ECG Transmission 33 4 Conservative Modulation and Coding for Instantaneous ECG Monitoring over LTE MTC 37 4.1 Architecture of Universal M2M ECG Platform 39 4.2 Demand for Instantaneous Monitoring 43 4.3 System Requirements for Instantaneous Monitoring Services 45 4.3.1 Latency Requirements and Analysis 45 4.3.2 Presentation Requirements for Sufficient Clinical Accuracy 53 4.4 System Architecture for Instantaneous Wireless ECG Monitoring using LTE MTC 58 4.4.1 Spatio-Temporal Scalable Media Coding for ECG signal 60 4.4.2 Conservative Modulation and Coding to Provide Extra Protection for Higher Prioritized Scalable Layers 64 4.4.3 System Parameter Analysis 68 4.5 Performance Evaluation 72 4.5.1 Simulation Environment 72 4.5.2 Simulation Results 72 4.5.3 Service Level Adjustment 78 5 Conclusion 79 5.1 Summary 79 5.2 Future Research Directions 83 Bibliography 84 Abstract in Korean 103Docto

Detecting Vital Signs with Wearable Wireless Sensors

The emergence of wireless technologies and advancements in on-body sensor design can enable change in the conventional health-care system, replacing it with wearable health-care systems, centred on the individual. Wearable monitoring systems can provide continuous physiological data, as well as better information regarding the general health of individuals. Thus, such vital-sign monitoring systems will reduce health-care costs by disease prevention and enhance the quality of life with disease management. In this paper, recent progress in non-invasive monitoring technologies for chronic disease management is reviewed. In particular, devices and techniques for monitoring blood pressure, blood glucose levels, cardiac activity and respiratory activity are discussed; in addition, on-body propagation issues for multiple sensors are presented

A Survey: Wireless Body Area Network for Health Monitoring

With an increasingly mobile society and the worldwide deployment of mobile and wireless networks, the wireless infrastructure can support many current and emerging health care applications. Citizens, being patients or non-patients, will not only be able to get medical advice from a distance but will also be able to send from any location full detailed and accurate vital signal measurements, as if they had been taken in medical centers. Towards this direction, the proposed system is highly customizable vital signal monitoring system based on Wireless Body Area Networks (WBAN). The proposed system allows the incorporation of diverse medical sensors via wireless connections and the live transmission of the measured vital signals over public wireless networks to healthcare providers. This paper discusses different scenarios where this wearable health monitoring system can be used and different types of sensors are used to measure the different parameters such as temperatures, glucose, heart beats, ECG, EEG, etc. Finally, through a case study, we demonstrate how the diabetic patient takes the advantage of this system

mHealth Engineering: A Technology Review

In this paper, we review the technological bases of mobile health (mHealth). First, we derive a component-based mHealth architecture prototype from an Institute of Electrical and Electronics Engineers (IEEE)-based multistage research and filter process. Second, we analyze medical databases with regard to these prototypic mhealth system components.. We show the current state of research literature concerning portable devices with standard and additional equipment, data transmission technology, interface, operating systems and software embedment, internal and external memory, and power-supply issues. We also focus on synergy effects by combining different mHealth technologies (e.g., BT-LE combined with RFID link technology). Finally, we also make suggestions for future improvements in mHealth technology (e.g., data-protection issues, energy supply, data processing and storage)