A Comprehensive Review on Wearable Health Monitoring Systems

This paper presents a comprehensive review of the wearable healthcare monitoring systems proposed by the researchers to date. One of the earliest wearable recorders, named “a silicon locket for ECG monitoring”, was developed at the Indian Institute of Technology, Bombay, in 2003. Thus, the wearable health monitoring systems, started with the acquisition of a single signal/ parameter to the present generation smart and affordable multi-parameter recording/monitoring systems, have evolved manifolds in these two decades. Wearable systems have dramatically changed in terms of size, cost, functionality, and accuracy. The early-day wearable recorders were with limited functionalities against today’s systems, e.g., Apple’s iWatch which comprises abundant health monitoring features like heart rate monitoring, breathing app, accelerometers, smart walking/ activity monitoring, and alerts. Most of the present-day smartphones are not only capable of recording various health features like body temperature, heart rate, photoplethysmograph (PPG) signal, calory consumption, smart activity monitoring, stress measurement, etc. through different apps, but they also help the user to get monitored by a family physician via GSM or even internet of things (IoT). One of the latest, state-of-the-art real-time personal health monitoring systems, Wearable IoT-cloud-based health monitoring system (WISE), is a beautiful amalgamation of body area sensor network (BASN) and IoT framework for ubiquitous health monitoring. The future of wearable health monitoring systems will be far beyond the IoT and BASN.

Fog-Driven Secure Authentication and Key Exchange Scheme for Wearable Health Monitoring System

Smart wearable devices, as a popular mobile device, have a broad market. Smart wearable medical devices implemented in wearable health monitoring systems can monitor the data pertaining to a patient’s body and let the patient know their own physical condition. In addition, these data can be stored, analyzed, and processed in the cloud to effectively prevent diseases. As an Internet-of-things technology, fog computing can process, store, and control data around devices in real time. However, the distributed attributes of fog nodes make the monitored body data and medical reports at risk of privacy disclosure. In this paper, we propose a fog-driven secure authentication and key exchange scheme for wearable health monitoring systems. Furthermore, we conduct a formal analysis using the Real-Oracle-Random model, Burrows–Abadi–Needham logic, and ProVerif tools and an informal analysis to perform security verification. Finally, a performance comparison with other related schemes shows that the proposed scheme has the best advantages in terms of security, computing overhead, and communication cost.

Provably Secure Crossdomain Multifactor Authentication Protocol for Wearable Health Monitoring Systems

Wearable health monitoring systems (WHMSs) have become the most effective and practical solutions to provide users with low-cost, noninvasive, long-term continuous health monitoring. Authentication is one of the key means to ensure physiological information security and privacy. Although numerous authentication protocols have been proposed, few of them cater to crossdomain WHMSs. In this paper, we present an efficient and provably secure crossdomain multifactor authentication protocol for WHMSs. First, we propose a ticket-based authentication model for multidomain WHMSs. Specifically, a mobile device of one domain can request a ticket from the cloud server of another domain with which wearable devices are registered and remotely access the wearable devices with the ticket. Secondly, we propose a crossdomain three-factor authentication scheme based on the above model. Only a doctor who can present all three factors can request a legitimate ticket and use it to access the wearable devices. Finally, a comprehensive security analysis of the proposed scheme is carried out. In particular, we give a provable security analysis in the random oracle model. The comparisons of security and efficiency with the related schemes demonstrate that the proposed scheme is secure and practical.

Multichannel ECG Recording from Waist using Textile Sensors

Background: The development of wearable health monitoring systems is garnering tremendous interest in research, technology and commercial applications. Their ability of providing unique capabilities in continuous, real-time, and non-invasive tracking of the physiological markers of users can provide insights into the performance and health of individuals. Electrocardiogram (ECG) signals are of particular interest, as cardiovascular disease is the leading cause of death globally. Monitoring heart health and its conditions such as ventricular disturbances and arrhythmias can be achieved through evaluating various features of ECG such as R-peaks, QRS complex, T-wave, and P-wave. Despite recent advances in biosensors for wearable applications, most of the currently available solutions rely solely on a single system attached to the body, limiting the ability to obtain reliable and multi-location biosignals. However, in engineering systems, sensor fusion, which is the optimal integration and processing of data from multiple sensors, has been a common theme and should be considered for wearables. In recent years, due to an increase in the availability and variety of different types of sensors, the possibility of achieving sensor fusion in wearable systems has become more attainable. Sensor fusion in multi-sensing systems results in significant enhancements of information inferences compared to those from systems with a sole sensor. One step towards the development of sensor fusion for wearable health monitoring systems is the accessibility to multiple reliable electrophysiological signals, which can be recorded continuously.Results: In this paper, we develop a textile-based multi-channel ECG band that has the ability to measure ECG from multiple locations on the waist. As a proof of concept, we demonstrate that ECG signals can be reliably obtained from different locations on the waist where the shape of the QRS complex is nearly comparable with recordings from the chest using traditional gel electrodes. In addition, we develop a probabilistic approach – based on prediction and update strategies – to detect R-Peaks from noisy textile data in different statuses, including sitting, standing, and jogging. In this approach, an optimal search method is utilized to detect R-Peaks based on the history of the intervals between previously detected R-Peaks. We show that the performance of our probabilistic approach in R-Peak detection is significantly better than that based on Pan-Tompkins and optimal-threshold methods. Conclusion: A textile-based multi-channel ECG band was developed to track the heart rate changes from multiple locations on the waist. We demonstrated that (i) the ECG signal can be detected from different locations on the waist, and (ii) the accuracy of the detected R-Peaks from textile sensors was improved by using our proposed probabilistic approach.Despite the limitations of the textile sensors that might compromise the quality of ECG signals,we anticipate that the textile-based multi-channel ECG band can be considered as an effective wearable system to facilitate the development of sensor fusion methodology for pervasive and non-invasive health monitoring through continuous tracking of heart rate variability (HRV) from the waist. In addition, from the commercialization point of view, we anticipate that the developed band has the potential to be integrated into garments such as underwear, bras or pants so that individuals can use it on a daily basis.

Multichannel ECG Recording from Waist using Textile Sensors

Background: The development of wearable health monitoring systems is garnering substantial interest in research and technology due to their unique capabilities in continuous, real-time, and non-invasive tracking of the physiological states of the human body. Wearable devices provide insights into the performance and health of individuals. Despite recent advances in biosensors, most of the currently available wearable devices rely solely on a single sensor attached to the body, limiting the ability to obtain reliable bio-information. However, in engineering systems, sensor fusion, which is the optimal integration and processing of data from multiple sensors, has been a common theme. In recent years due to an increase in the availability and variety of different types of sensors, the possibility of achieving sensor fusion in wearable systems has become more attainable. Sensor fusion in multi-sensing systems results in a significant enhancement of information inference compared to that from systems with a sole sensor. One step towards the development of sensor fusion for wearable health monitoring systems is the accessibility to multiple reliable electrophysiological signals, which can be recorded continuously.Results: In this paper, we develop a textile-based multi-channel ECG band that has the ability to measure from multiple locations on the waist. As a proof of concept, we show that ECG signals can be reliably obtained from different locations on the waist where the shape of the QRS complex is comparable with that recorded from the chest using traditional gel electrodes. As well, we develop a probabilistic approach to detect R-Peaks from noisy textile data in different sitting, standing, and jogging statuses. We show that the performance of the proposed algorithm is significantly better than that based on Pan-Tompkins and optimal-threshold methods. Conclusion: This band can be easily integrated into garments such as underwear, bras or pants. We predict that the textile-based multi-channel ECG band can be considered as an effective wearable system which enables the development of sensor fusion methodology for pervasive and non-invasive health monitoring through continuous tracking of heart rate variability (HRV) from the waist.