scholarly journals Multichannel ECG Recording from Waist using Textile Sensors

2020 ◽  
Author(s):  
Milad Alizadeh Meghrazi ◽  
Yupeng Tian ◽  
Amin Mahnam ◽  
Presish Bhattachan ◽  
Ladan Eskandarian ◽  
...  
Keyword(s):  
Sensor Fusion ◽  
Health Monitoring ◽  
Probabilistic Approach ◽  
Wearable Devices ◽  
The Body ◽  
Monitoring Systems ◽  
Multiple Sensors ◽  
Non Invasive ◽  
Health Monitoring Systems ◽  
Wearable Health Monitoring Systems

Abstract 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.

scholarly journals Multichannel ECG Recording from Waist using Textile Sensors

2020 ◽  
Author(s):  
Milad Alizadeh Meghrazi ◽  
Yupeng Tian ◽  
Amin Mahnam ◽  
Presish Bhattachan ◽  
Ladan Eskandarian ◽  
...  
Keyword(s):  
Sensor Fusion ◽  
Health Monitoring ◽  
Probabilistic Approach ◽  
Monitoring Systems ◽  
Qrs Complex ◽  
Ecg Signals ◽  
Non Invasive ◽  
Textile Sensors ◽  
Health Monitoring Systems ◽  
Wearable Health Monitoring Systems

Abstract 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.

scholarly journals Provably Secure Crossdomain Multifactor Authentication Protocol for Wearable Health Monitoring Systems

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Hui Zhang ◽  
Yuanyuan Qian ◽  
Qi Jiang
Keyword(s):  
Health Monitoring ◽  
Security Analysis ◽  
Wearable Devices ◽  
Authentication Protocol ◽  
Security And Privacy ◽  
Monitoring Systems ◽  
Multifactor Authentication ◽  
Health Monitoring Systems ◽  
Wearable Health Monitoring Systems ◽  
Provably Secure

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.

Dynamic Computation Offloading for Low-Power Wearable Health Monitoring Systems

2017 ◽  
Vol 64 (3) ◽  
pp. 621-628 ◽  
Author(s):  
Haik Kalantarian ◽  
Costas Sideris ◽  
Bobak Mortazavi ◽  
Nabil Alshurafa ◽  
Majid Sarrafzadeh
Keyword(s):  
Low Power ◽  
Health Monitoring ◽  
Computation Offloading ◽  
Monitoring Systems ◽  
Dynamic Computation ◽  
Health Monitoring Systems ◽  
Wearable Health Monitoring Systems

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

2021 ◽  
Vol 2021 ◽  
pp. 1-14 ◽  
Author(s):  
Tsu-Yang Wu ◽  
Lei Yang ◽  
Qian Meng ◽  
Xinglan Guo ◽  
Chien-Ming Chen
Keyword(s):  
Health Monitoring ◽  
Formal Analysis ◽  
Fog Computing ◽  
Key Exchange ◽  
Monitoring Systems ◽  
Health Monitoring Systems ◽  
Wearable Health Monitoring Systems ◽  
Secure Authentication ◽  
Internet Of Things Technology ◽  
Smart Wearable

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.

scholarly journals Activity and health monitoring systems

2018 ◽  
Vol 11 (1) ◽  
pp. 11-14
Author(s):  
Béla-Csaba Simon ◽  
Stefan Oniga ◽  
Iuliu Alexandru Pap
Keyword(s):  
Human Body ◽  
Health Monitoring ◽  
Touch Screen ◽  
Physiological Parameters ◽  
The Body ◽  
Raspberry Pi ◽  
Monitoring Systems ◽  
Solid Base ◽  
Processing Unit ◽  
Health Monitoring Systems

Abstract This paper presents an Open Platform Activity and health monitoring systems which are also called e-Health systems. These systems measure and store parameters that reflect changes in the human body. Due to continuous monitoring (e.g. in rest state and in physical effort state), a specialist can learn about the individual's physiological parameters. Because the human body is a complex system, the examiner can notice some changes within the body by looking at the physiological parameters. Six different sensors ensure us that the patient's individual parameters are monitored. The main components of the device are: A Raspberry Pi 3 small single-board computer, an e-Health Sensor Platform by Cooking-Hacks, a Raspberry Pi to Arduino Shields Connection Bridge and a 7-inch Raspberry Pi 3 touch screen. The processing unit is the Raspberry Pi 3 board. The Raspbian operating system runs on the Raspberry Pi 3, which provides a solid base for the software. Every examination can be controlled by the touch screen. The measurements can be started with the graphical interface by pressing a button and every measured result can be represented on the GUI’s label or on the graph. The results of every examination can be stored in a database. From that database the specialist can retrieve every personalized data.

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