Special Issue "Wearable Wireless Devices"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: closed (31 January 2019)

Special Issue Editors

Guest Editor
Dr. Qammer H. Abbasi

School of Engineering, University of Glasgow, UK
Website | E-Mail
Interests: nano communication, biomedical applications of millimeter and terahertz communication, wearable and flexible sensors, compact antenna design, RF design and radio propagation, antenna interaction with human body, Implants, body centric wireless communication issues, wireless body sensor networks, non-invasive health care solutions, physical layer security for wearable/implant communication and multiple-input-multiple-output systems.
Guest Editor
Dr. Akram Alomainy

Queen Mary University of London, UK
Website | E-Mail
Interests: small and compact antennas for wireless body area networks, radio propagation characterisation and modelling, antenna interactions with human body, computational electromagnetic, advanced antenna enhancement techniques for mobile and personal wireless communications, nano-scale networks and communications, THz material characterisation and communication links and advanced algorithm for smart and intelligent antenna and cognitive radio system, biomedical EM applications in sensing and detection
Guest Editor
Dr. Hadi Heidari

School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK
Website | E-Mail
Interests: analog integrated circuit design; wearable and implantable electronics; sensors and systems; magnetoelectronics and magnetic sensors; point-of-care diagnostics

Special Issue Information

Dear Colleagues,

With the growing interest in the use of technology in daily life, the potential of using wearable wireless devices across multiple segments, e.g., healthcare, sports, child monitoring, military, emergency, consumer electronics, etc., is rapidly increasing. It is predicted that there will be multibillion wearable sensors by 2025, with over 30% of them being new types of sensors that are just beginning to emerge. This Special Issue will be focused on wireless wearable and implantable system, flexible textile-based electronics, bio-electromagnetics, antennas and propagation, RF circuits, sensor, security of wearables and implantable system, nano-bio communication and electromagnetic sensing.

Dr. Qammer H. Abbasi
Dr. Akram Alomainy
Dr. Hadi Heidari
Guest Editors

Manuscript Submission Information

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Keywords

  • wearables

  • implants

  • sensors

  • antenna’s

  • millimeter wave and terahertz sensing

  • security

  • propagation

  • bio electromagnetic

  • flexible

Published Papers (10 papers)

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Research

Open AccessArticle Reservoir Computing Based Echo State Networks for Ventricular Heart Beat Classification
Appl. Sci. 2019, 9(4), 702; https://doi.org/10.3390/app9040702
Received: 15 January 2019 / Revised: 1 February 2019 / Accepted: 1 February 2019 / Published: 18 February 2019
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Abstract
The abnormal conduction of cardiac activity in the lower chamber of the heart (ventricular) can cause cardiac diseases and sometimes leads to sudden death. In this paper, the author proposed the Reservoir Computing (RC) based Echo State Networks (ESNs) for ventricular heartbeat classification [...] Read more.
The abnormal conduction of cardiac activity in the lower chamber of the heart (ventricular) can cause cardiac diseases and sometimes leads to sudden death. In this paper, the author proposed the Reservoir Computing (RC) based Echo State Networks (ESNs) for ventricular heartbeat classification based on a single Electrocardiogram (ECG) lead. The Association for the Advancement of Medical Instrumentation (AAMI) standards were used to preprocesses the standardized diagnostic tool (ECG signals) based on the interpatient scheme. Despite the extensive efforts and notable experiments that have been done on machine learning techniques for heartbeat classification, ESNs are yet to be considered for heartbeat classification as a is fast, scalable, and reliable approach for real-time scenarios. Our proposed method was especially designed for Medical Internet of Things (MIoT) devices, for instance wearable wireless devices for ECG monitoring or ventricular heart beat detection systems and so on. The experiments were conducted on two public datasets, namely AHA and MIT-BIH-SVDM. The performance of the proposed model was evaluated using the MIT-BIH-AR dataset and it achieved remarkable results. The positive predictive value and sensitivity are 98.98% and 98.98%, respectively for the modified lead II (MLII) and 98.96% and 97.95 for the V1 lead, respectively. However, the experimental results of the state-of-the-art approaches, namely the patient-adaptable method, improved generalization, and the multiview learning approach obtained 92.8%, 87.0%, and 98.0% positive predictive values, respectively. These obtained results of the existing studies exemplify that the performance of this method achieved higher accuracy. We believe that the improved classification accuracy opens up the possibility for implementation of this methodology in Medical Internet of Things (MIoT) devices in order to bring improvements in e-health systems. Full article
(This article belongs to the Special Issue Wearable Wireless Devices)
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Open AccessArticle A Real Time and Lossless Encoding Scheme for Patch Electrocardiogram Monitors
Appl. Sci. 2018, 8(12), 2379; https://doi.org/10.3390/app8122379
Received: 30 October 2018 / Revised: 16 November 2018 / Accepted: 20 November 2018 / Published: 24 November 2018
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Abstract
Cardiovascular diseases are the leading cause of death worldwide. Due to advancements facilitating the integration of electric and adhesive technologies, long-term patch electrocardiogram (ECG) monitors (PEMs) are currently used to conduct daily continuous cardiac function assessments. This paper presents an ECG encoding scheme [...] Read more.
Cardiovascular diseases are the leading cause of death worldwide. Due to advancements facilitating the integration of electric and adhesive technologies, long-term patch electrocardiogram (ECG) monitors (PEMs) are currently used to conduct daily continuous cardiac function assessments. This paper presents an ECG encoding scheme for joint lossless data compression and heartbeat detection to minimize the circuit footprint size and power consumption of a PEM. The proposed encoding scheme supports two operation modes: fixed-block mode and dynamic-block mode. Both modes compress ECG data losslessly, but only dynamic-block mode supports the heartbeat detection feature. The whole encoding scheme was implemented on a C-platform and tested with ECG data from MIT/BIH arrhythmia databases. A compression ratio of 2.1 could be achieved with a normal heartbeat. Dynamic-block mode provides heartbeat detection accuracy at a rate higher than 98%. Fixed-block mode was also implemented on the field-programmable gate array, and could be used as a chip for using analog-to-digital convertor-ready signals as an operation clock. Full article
(This article belongs to the Special Issue Wearable Wireless Devices)
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Open AccessArticle Foot-Mounted Inertial Measurement Units-Based Device for Ankle Rehabilitation
Appl. Sci. 2018, 8(11), 2032; https://doi.org/10.3390/app8112032
Received: 6 October 2018 / Revised: 18 October 2018 / Accepted: 19 October 2018 / Published: 24 October 2018
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Abstract
Ankle sprains are frequent injuries that occur among people of all ages. Ankle sprains constitute approximately 15% of all sports injuries, and are the most common traumatic emergencies. Without proper treatment and rehabilitation, a more severe sprain can weaken the ankle, making it [...] Read more.
Ankle sprains are frequent injuries that occur among people of all ages. Ankle sprains constitute approximately 15% of all sports injuries, and are the most common traumatic emergencies. Without proper treatment and rehabilitation, a more severe sprain can weaken the ankle, making it more likely for new injures, and leading to long-term problems. In this work, we present an inertial measurement units (IMU)-based physical interface for measuring the foot attitude, and a graphical user interface that acts as a visual guide for patient rehabilitation. A foot-mounted physical interface for ankle rehabilitation was developed. The physical interface is connected to the computer by a Bluetooth link, and provides feedback to the patient while performing dorsiflexion, plantarflexion, eversion, and inversion exercises. The system allows for in-home rehabilitation at an affordable price while engaging the patient through active therapy. According to the results, more consistent rehabilitation could be achieved by providing feedback on foot angular position during therapy procedures. Full article
(This article belongs to the Special Issue Wearable Wireless Devices)
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Graphical abstract

Open AccessArticle Chronic Obstructive Pulmonary Disease Warning in the Approximate Ward Environment
Appl. Sci. 2018, 8(10), 1915; https://doi.org/10.3390/app8101915
Received: 23 August 2018 / Revised: 1 October 2018 / Accepted: 8 October 2018 / Published: 15 October 2018
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Abstract
This research presents the usage of modern 5G C-Band sensing for health care monitoring. The focus of this research is to monitor the respiratory symptoms for COPD (Chronic Obstructive Pulmonary Disease). The C-Band sensing is used to detect the respiratory conditions, including normal, [...] Read more.
This research presents the usage of modern 5G C-Band sensing for health care monitoring. The focus of this research is to monitor the respiratory symptoms for COPD (Chronic Obstructive Pulmonary Disease). The C-Band sensing is used to detect the respiratory conditions, including normal, abnormal breathing and coughing of a COPD patient by utilizing the simple wireless devices, including a desktop system, network interface card, and the specified tool for the extraction of wireless channel information with Omni directional antenna operating at 4.8 GHz frequency. The 5G sensing technique enhances the sensing performance for the health care sector by monitoring the amplitude information for different respiratory activities of a patient using the above-mentioned devices. This method examines the rhythmic breathing patterns obtained from C-Band sensing and digital respiratory sensor and compared the result. Full article
(This article belongs to the Special Issue Wearable Wireless Devices)
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Open AccessArticle Movement Noise Cancellation in Second Derivative of Photoplethysmography Signals with Wavelet Transform and Diversity Combining
Appl. Sci. 2018, 8(9), 1531; https://doi.org/10.3390/app8091531
Received: 31 July 2018 / Revised: 24 August 2018 / Accepted: 28 August 2018 / Published: 1 September 2018
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Abstract
In this paper, we propose an algorithm to remove movement noise from second derivative of photoplethysmography (SDPPG) signals. SDPPG is widely used in healthcare applications because of its easy and comfortable measurement. However, an SDPPG signal is vulnerable to movement, which degrades the [...] Read more.
In this paper, we propose an algorithm to remove movement noise from second derivative of photoplethysmography (SDPPG) signals. SDPPG is widely used in healthcare applications because of its easy and comfortable measurement. However, an SDPPG signal is vulnerable to movement, which degrades the signal. Degradation of SDPPG signal shapes can result in incorrect diagnosis. The proposed algorithm detects movement noise in a measurement signal using wavelet transform, and removes movement noise by selecting the best signal from among multiple signals measured at different locations. Experiment results show that the proposed algorithm outperforms the previous filter-based algorithm, and that movement noise with 30% time duration can be reduced by up to 70.89%. Full article
(This article belongs to the Special Issue Wearable Wireless Devices)
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Open AccessFeature PaperArticle An Anonymous Mutual Authenticated Key Agreement Scheme for Wearable Sensors in Wireless Body Area Networks
Appl. Sci. 2018, 8(7), 1074; https://doi.org/10.3390/app8071074
Received: 31 May 2018 / Revised: 15 June 2018 / Accepted: 21 June 2018 / Published: 2 July 2018
Cited by 1 | PDF Full-text (882 KB) | HTML Full-text | XML Full-text
Abstract
The advancement of Wireless Body Area Networks (WBAN) have led to significant progress in medical and health care systems. However, such networks still suffer from major security and privacy threats, especially for the data collected in medical or health care applications. Lack of [...] Read more.
The advancement of Wireless Body Area Networks (WBAN) have led to significant progress in medical and health care systems. However, such networks still suffer from major security and privacy threats, especially for the data collected in medical or health care applications. Lack of security and existence of anonymous communication in WBAN brings about the operation failure of these networks. Recently, Li et al. proposed a lightweight protocol for wearable sensors in wireless body area networks. In their paper, the authors claimed that the protocol may provide anonymous mutual authentication and resist against various types of attacks. This study shows that such a protocol is still vulnerable to three types of attacks, i.e., the offline identity guessing attack, the sensor node impersonation attack and the hub node spoofing attack. We then present a secure scheme that addresses these problems, and retains similar efficiency in wireless sensors nodes and mobile phones. Full article
(This article belongs to the Special Issue Wearable Wireless Devices)
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Open AccessArticle Respiration Symptoms Monitoring in Body Area Networks
Appl. Sci. 2018, 8(4), 568; https://doi.org/10.3390/app8040568
Received: 8 March 2018 / Revised: 1 April 2018 / Accepted: 1 April 2018 / Published: 6 April 2018
Cited by 1 | PDF Full-text (21391 KB) | HTML Full-text | XML Full-text
Abstract
This work presents a framework that monitors particular symptoms such as respiratory conditions (abnormal breathing pattern) experienced by hyperthyreosis, sleep apnea, and sudden infant death syndrome (SIDS) patients. The proposed framework detects and monitors respiratory condition using S-Band sensing technique that leverages the [...] Read more.
This work presents a framework that monitors particular symptoms such as respiratory conditions (abnormal breathing pattern) experienced by hyperthyreosis, sleep apnea, and sudden infant death syndrome (SIDS) patients. The proposed framework detects and monitors respiratory condition using S-Band sensing technique that leverages the wireless devices such as antenna, card, omni-directional antenna operating in 2 GHz to 4 GHz frequency range, and wireless channel information extraction tool. The rhythmic patterns extracted using S-Band sensing present the periodic and non-periodic waveforms that correspond to normal and abnormal respiratory conditions, respectively. The fine-grained amplitude information obtained using aforementioned devices is used to examine the breathing pattern over a period of time and accurately identifies the particular condition. Full article
(This article belongs to the Special Issue Wearable Wireless Devices)
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Open AccessArticle Internet of Things for Sensing: A Case Study in the Healthcare System
Appl. Sci. 2018, 8(4), 508; https://doi.org/10.3390/app8040508
Received: 1 December 2017 / Revised: 10 March 2018 / Accepted: 19 March 2018 / Published: 27 March 2018
Cited by 4 | PDF Full-text (11357 KB) | HTML Full-text | XML Full-text
Abstract
Medical healthcare is one of the fascinating applications using Internet of Things (IoTs). The pervasive smart environment in IoTs has the potential to monitor various human activities by deploying smart devices. In our pilot study, we look at narcolepsy, a disorder in which [...] Read more.
Medical healthcare is one of the fascinating applications using Internet of Things (IoTs). The pervasive smart environment in IoTs has the potential to monitor various human activities by deploying smart devices. In our pilot study, we look at narcolepsy, a disorder in which individuals lose the ability to regulate their sleep-wake cycle. An imbalance in the brain chemical called orexin makes the sleep pattern irregular. This sleep disorder in patients suffering from narcolepsy results in them experience irrepressible sleep episodes while performing daily routine activities. This study presents a novel method for detecting sleep attacks or sleepiness due to immune system attacks and affecting daily activities measured using the S-band sensing technique. The S-Band sensing technique is channel sensing based on frequency spectrum sensing using the orthogonal frequency division multiplexing transmission at a 2 to 4 GHz frequency range leveraging amplitude and calibrated phase information of different frequencies obtained using wireless devices such as card, and omni-directional antenna. Each human behavior induces a unique channel information (CI) signature contained in amplitude and phase information. By linearly transforming raw phase measurements into calibrated phase information, we ascertain phase coherence. Classification and validation of various human activities such as walking, sitting on a chair, push-ups, and narcolepsy sleep episodes are done using support vector machine, K-nearest neighbor, and random forest algorithms. The measurement and evaluation were carried out several times with classification values of accuracy, precision, recall, specificity, Kappa, and F-measure of more than 90% that were achieved when delineating sleep attacks. Full article
(This article belongs to the Special Issue Wearable Wireless Devices)
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Open AccessArticle Emergency-Prioritized Asymmetric Protocol for Improving QoS of Energy-Constraint Wearable Device in Wireless Body Area Networks
Appl. Sci. 2018, 8(1), 92; https://doi.org/10.3390/app8010092
Received: 6 December 2017 / Revised: 29 December 2017 / Accepted: 8 January 2018 / Published: 10 January 2018
Cited by 1 | PDF Full-text (2150 KB) | HTML Full-text | XML Full-text
Abstract
Wireless Body Area Network (WBAN) is usually composed of nodes for contacting the body and coordinator for collecting the body data from the nodes. In this setup, the nodes are under constraint of the energy resource while the coordinator can be recharged and [...] Read more.
Wireless Body Area Network (WBAN) is usually composed of nodes for contacting the body and coordinator for collecting the body data from the nodes. In this setup, the nodes are under constraint of the energy resource while the coordinator can be recharged and has relatively larger energy resource than the nodes. Therefore, the architecture mechanism of the networks must not allow the nodes to consume much energy. Primarily, Medium Access Control (MAC) protocols should be carefully designed to consider this issue, because the MAC layer has the key of the energy efficiency phenomenon (e.g., idle listening). Under these characteristics, we propose a new MAC protocol to satisfy the higher energy efficiency of nodes than coordinator by designing the asymmetrically energy-balanced model between nodes and coordinator. The proposed scheme loads the unavoidable energy consumption into the coordinator instead of the nodes to extend their lifetime. Additionally, the scheme also provides prioritization for the emergency data transmission with differentiated Quality of Service (QoS). For the evaluations, IEEE 802.15.6 was used for comparison. Full article
(This article belongs to the Special Issue Wearable Wireless Devices)
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Open AccessArticle Virtual Reality-Wireless Local Area Network: Wireless Connection-Oriented Virtual Reality Architecture for Next-Generation Virtual Reality Devices
Appl. Sci. 2018, 8(1), 43; https://doi.org/10.3390/app8010043
Received: 15 November 2017 / Revised: 23 December 2017 / Accepted: 27 December 2017 / Published: 3 January 2018
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Abstract
In order to enhance the user experience of virtual reality (VR) devices, multi-user VR environments and wireless connections should be considered for next-generation VR devices. Wireless local area network (WLAN)-based wireless communication devices are popular consumer devices with high throughput and low cost [...] Read more.
In order to enhance the user experience of virtual reality (VR) devices, multi-user VR environments and wireless connections should be considered for next-generation VR devices. Wireless local area network (WLAN)-based wireless communication devices are popular consumer devices with high throughput and low cost using unlicensed bands. However, the use of WLANs may cause delays in packet transmission, owing to their distributed nature while accessing the channel. In this paper, we carefully examine the feasibility of wireless VR over WLANs, and we propose an efficient wireless multiuser VR communication architecture, as well as a communication scheme for VR. Because the proposed architecture in this paper utilizes multiple WLAN standards, based on the characteristics of each set of VR traffic, the proposed scheme enables the efficient delivery of massive uplink data generated by multiple VR devices, and provides an adequate video frame rate and control frame rate for high-quality VR services. We perform extensive simulations to corroborate the outstanding performance of the proposed scheme. Full article
(This article belongs to the Special Issue Wearable Wireless Devices)
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