WBSN in IoT health-based application: toward delay and energy consumption minimizing

The wireless body sensor network (WBSN) technologies are one of the essential technologies of the Internet of things (IoT) growths of the healthcare paradigm, where every patient is monitored through a group of small-powered and lightweight sensor nodes. Thus, energy consumption is a major issue in WBSN. The major causes of energy wastage in WBSN are collisions and retransmission process. However, the major cause of the collision happened when two sensors are attempting to transmit data at exactly the same time and same frequency, and the major cause of the retransmission process happened when the collision takes place or data does not received properly due to channel fading. In this paper, we proposed a cognitive cooperative communication with two master nodes, namely, as two cognitive master nodes (TCMN), which can eliminate the collision and reduce the retransmission process. First, a complete study of a scheme is investigated in terms of network architecture. Second, a mathematical model of the link and outage probability of the proposed protocol are derived. Third, the end-to-end delay, throughput, and energy consumption are analyzed and investigated. The simulation and numerical results show that the TCMN can do system performance under general conditions with respect to direct transmission mode (DTM) and existing work

Energy harvesting Internet of Things health-based paradigm: toward outage probability reduction through inter-wireless body area network cooperation

In today’s healthcare environment, the Internet of Things technology provides suitability among physicians and patients, as it is valuable in numerous medicinal fields. Wireless body sensor network technologies are essential technologies in the growth of Internet of Things healthcare paradigm, where every patient is monitored utilising small-powered and lightweight sensor nodes. A dual-hop, inter–wireless body sensor network cooperation and an incremental inter–wireless body sensor network cooperation with energy harvesting in the Internet of Things health-based paradigm have been investigated and designed in this work. The three protocols have been named and abbreviated as follows: energy harvesting–based dual-hop cooperation, energy harvesting–based inter–wireless body sensor network cooperation and energy harvesting–based incremental inter–wireless body sensor network cooperation. Outage probabilities for the three designed protocols were investigated and inspected, and mathematical expressions of the outage probabilities were derived. The simulation and numerical results showed that the energy harvesting–based incremental inter–wireless body sensor network cooperation provided superior performance over the energy harvesting–based inter–wireless body sensor network cooperation and energy harvesting–based dual-hop cooperation by 1.38 times and 5.72 times, respectively; while energy harvesting–based inter–wireless body sensor network cooperation achieved better performance over energy harvesting–based dual-hop cooperation by 1.87 times

Distributed remote antenna unit with selection-based of (RoF-IoT) paradigm: Performance improvement

Data availability statement: All data are available within manuscript.Copyright © 2022 The Authors. Mixing the wireless medium with fiber optics can form a new communication system called a radio-over-fiber (RoF) network; it is a promising solution that can provide high bandwidth and a reliable connection between numerous sensors in wireless sensor networks (WSN) and the central office (base station) within a particular area. This paper first design and discusses new paradigms of fire detection in the IoT environment using RoF technology. Second, this paper covers the distribution of remote antenna unit (DRAU) architecture within RoF-IoT. Finally, best remote antennas unit selection (BRAUS) of distributed RAUs architecture protocols utilizing new selection metrics is proposed. Two important metrics have been analysed and mathematically modelled, outage probability and bandwidth efficiency, respectively. Both metrics have been analysed as a function of the distance, number of RAUs, fiber optic attenuation, and path loss factor. Based on the simulation and numerical analysis, the outage probability of proposed protocols is reduced by 65% compared to recent work; in addition, the bandwidth efficiency of the proposed protocol is increased by 34% compared to recent work.Brunel University London. Grant Number: J066

Contactless privacy-preserving head movement recognition using deep learning for driver fatigue detection

Head movement holds significant importance in con-veying body language, expressing specific gestures, and reflecting emotional and character aspects. The detection of head movement in smart or assistive driving applications can play an important role in preventing major accidents and potentially saving lives. Additionally, it aids in identifying driver fatigue, a significant contributor to deadly road accidents worldwide. However, most existing head movement detection systems rely on cameras, which raise privacy concerns, face challenges with lighting conditions, and require complex training with long video sequences. This novel privacy-preserving system utilizes UWB-radar technology and leverages Deep Learning (DL) techniques to address the mentioned issues. The system focuses on classifying the five most common head gestures: Head 45L (HL45), Head 45R (HR45), Head 90L (HL90), Head 90R (HR90), and Head Down (HD). By processing the recorded data as spectrograms and leveraging the advanced DL model VGG16, the proposed system accurately detects these head gestures, achieving a maximum classification accuracy of 84.00% across all classes. This study presents a proof of concept for an effective and privacy-conscious approach to head position classification.</p

TAQWA: Teaching Adolescents Quality Wadhu/Ablution contactlessly using deep learning

This research presents a unique and innovative approach to teaching young children the proper steps of ablution (wazoo/wudu) by utilizing a non-invasive sensing system integrated with deep learning algorithms. However, most existing ablution detection systems rely on cameras, which raise privacy concerns, face challenges with lighting conditions, and require complex training with long video sequences. We conducted experiments with a group of youngsters to evaluate the system’s effectiveness, demonstrating its potential in fostering a deeper appreciation and comprehension of religious practices among young learners. This innovative privacy-preserving ablution system employs state-of-the-art UWB-radar technology with advanced Deep Learning (DL) techniques to effectively address the challenges mentioned above. The core focus of this system is to categorize the four fundamental ablution steps: Wash Face 3x, Wash Hand 3x, Wash Head 1x, and Wash Feet 3x. By transforming the collected data into spectrograms and harnessing the sophisticated DL models VGG16 and VGG19, the proposed system accurately detects these ablution steps, achieving an impressive maximum accuracy of 97.92% across all categories with the utilization of VGG16

Enhancement of the duty cycle cooperative medium access control for wireless body area networks

This paper presents a novel energy-efficient and reliable connection to enhance the transmission of data over a shared medium for wireless body area networks (WBAN). We propose a novel protocol of two master nodes-based cooperative protocol. In the proposed protocol, two master nodes were considered, that is, the belt master node and the outer body master node. The master nodes work cooperatively to avoid the retransmission process by sensors due to fading and collision, reducing the bit error rate (BER), which results in a reduction of the duty cycle and average transmission power. In addition, we have also presented a mathematical model of the duty cycle with the proposed protocol for the WBAN. The results show that the proposed cooperative protocol reduced the BER by a factor of 4. The average transmission power is reduced by a factor of 0.21 and this shows the potential of the proposed technique to be used in future wearable wireless sensors and systems

Non-Cooperative Game Theory Approach for Cognitive Cooperative Communication in WBAN

To increase the Quality of Service (QoS) of wireless body area network, we need an effective data-rate delivering method, which capably forwarding the data over several path. For this reason, we proposed a non-cooperative game approach, based on utilizing a pricing-based spectrum leasing mechanism to transmit the data over several path based on non-cooperative game theory. The parameter price c is together determined by WBAN sensor and D2D users. Then, all selected D2D users used optimized powers that can fulfil the need of the WBSN users. Numerical results show the proposed approach improves the utility of WBSN users and their throughput

Lessons learned from COVID-19 Lockdown: An ASPED/MENA Study on Lifestyle Changes and Quality of Life during Ramadan Fasting in Children and Adolescents living with Type 1 Diabetes

Background: Lockdown was a unique experience that affected many aspects of life, particularly during the challenge of Ramadan fasting (RF). Studying this can increase understanding of the effects of lifestyle changes on quality of life (QoL) for children with type 1 diabetes (T1D) during RF. Methods: A cross-sectional study that assessed the effect of lockdown on lifestyle and QoL on fasting children living with T1D during Ramadan in the Middle East and North Africa region (2020-2021). We compared the child (self) and parent (proxy) reports using PEDQoL v3.0 disease specific questionnaire during lockdown and non-lockdown periods, and assessed correlations with lifestyle changes using regression and gap analyses. Results: A total of 998 reports from 499 children with T1D aged 8-18 years (study=276, control=223), and their parents during RF in lockdown and non-lockdown periods. Fathers were more involved in their children’s care during lockdown (p=0.019). Patients had better compliance with treatment (p= 0.002), a reversed sleep pattern (p= 0.033), increased food intake (p=<0.001) and less exercise (p<0.001). Children and parents perceived better QoL during lockdown (p=<0.001) with no differences between their reports in “Diabetes Symptoms”, “Treatment Adherence” and “Communication” domains. Self and proxy reports were different in all domains during non-lockdown (p-values <0.001- 0.009). In gap analysis, although not statistically significant, the gap was approximated between children’s and parents’ perceptions in all domains during lockdown. Conclusion: COVID-19 lockdown had a positive impact on QoL of children living with T1D during RF, possibly due to lifestyle changes and superior psychosocial family dynamics

The clinical impact of using complex molecular profiling strategies in routine oncology practice

Molecular profiling and functional assessment of signalling pathways of advanced solid tumours are becoming increasingly available. However, their clinical utility in guiding patients’ treatment remains unknown. Here, we assessed whether molecular profiling helps physicians in therapeutic decision making by analysing the molecular profiles of 1057 advanced cancer patient samples after failing at least one standard of care treatment using a combination of next-generation sequencing (NGS), immunohistochemistry (IHC) and other specific tests. The resulting information was interpreted and personalized treatments for each patient were suggested. Our data showed that NGS alone provided the oncologist with useful information in 10–50% of cases (depending on cancer type), whereas the addition of IHC/other tests increased extensively the usefulness of the information provided. Using internet surveys, we investigated how therapy recommendations influenced treatment choice of the oncologist. For patients who were still alive after the provision of the molecular information (76.8%), 60.4% of their oncologists followed report recommendations. Most treatment decisions (93.4%) were made based on the combination of NGS and IHC/other tests, and an approved drug- rather than clinical trial enrolment- was the main treatment choice. Most common reasons given by physicians to explain the non-adherence to recommendations were drug availability and cost, which remain barriers to personalised precision medicine. Finally, we observed that 27% of patients treated with the suggested therapies had an overall survival > 12 months. Our study demonstrates that the combination of NGS and IHC/other tests provides the most useful information in aiding treatment decisions by oncologists in routine clinical practice

The global burden of adolescent and young adult cancer in 2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In estimating the global burden of cancer, adolescents and young adults with cancer are often overlooked, despite being a distinct subgroup with unique epidemiology, clinical care needs, and societal impact. Comprehensive estimates of the global cancer burden in adolescents and young adults (aged 15–39 years) are lacking. To address this gap, we analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, with a focus on the outcome of disability-adjusted life-years (DALYs), to inform global cancer control measures in adolescents and young adults. Methods: Using the GBD 2019 methodology, international mortality data were collected from vital registration systems, verbal autopsies, and population-based cancer registry inputs modelled with mortality-to-incidence ratios (MIRs). Incidence was computed with mortality estimates and corresponding MIRs. Prevalence estimates were calculated using modelled survival and multiplied by disability weights to obtain years lived with disability (YLDs). Years of life lost (YLLs) were calculated as age-specific cancer deaths multiplied by the standard life expectancy at the age of death. The main outcome was DALYs (the sum of YLLs and YLDs). Estimates were presented globally and by Socio-demographic Index (SDI) quintiles (countries ranked and divided into five equal SDI groups), and all estimates were presented with corresponding 95% uncertainty intervals (UIs). For this analysis, we used the age range of 15–39 years to define adolescents and young adults. Findings: There were 1·19 million (95% UI 1·11–1·28) incident cancer cases and 396 000 (370 000–425 000) deaths due to cancer among people aged 15–39 years worldwide in 2019. The highest age-standardised incidence rates occurred in high SDI (59·6 [54·5–65·7] per 100 000 person-years) and high-middle SDI countries (53·2 [48·8–57·9] per 100 000 person-years), while the highest age-standardised mortality rates were in low-middle SDI (14·2 [12·9–15·6] per 100 000 person-years) and middle SDI (13·6 [12·6–14·8] per 100 000 person-years) countries. In 2019, adolescent and young adult cancers contributed 23·5 million (21·9–25·2) DALYs to the global burden of disease, of which 2·7% (1·9–3·6) came from YLDs and 97·3% (96·4–98·1) from YLLs. Cancer was the fourth leading cause of death and tenth leading cause of DALYs in adolescents and young adults globally. Interpretation: Adolescent and young adult cancers contributed substantially to the overall adolescent and young adult disease burden globally in 2019. These results provide new insights into the distribution and magnitude of the adolescent and young adult cancer burden around the world. With notable differences observed across SDI settings, these estimates can inform global and country-level cancer control efforts. Funding: Bill &amp; Melinda Gates Foundation, American Lebanese Syrian Associated Charities, St Baldrick's Foundation, and the National Cancer Institute