Search Results (34)

This paper describes the design, fabrication, and successful evaluation of a wristband developed for alerting users in critical situations. The target group is single people, especially the elderly, but also people with various disabilities. A low-cost wristband, which, when these people fall, immediately triggers a Wi-Fi-connected alert system on the gadgets of the staff or the person belonging to them. The system is implemented as a wearable forearm sleeve that integrates multiple sensors and electronic components, capable of sending instant alerts to family members or caregivers via the Blynk application. Full article

Data over sound (DoS) is an established technique that has experienced a resurgence in recent years, finding applications in areas such as contactless payments, device pairing, authentication, presence detection, toys, and offline data transfer. This study introduces CardiaWhisper, a system that extends the DoS concept to the medical domain by using a medical data-over-sound (MDoS) framework. CardiaWhisper integrates wearable biomedical sensors with home care systems, edge or IoT gateways, and telemedical networks or cloud platforms. Using a transmitter device, vital signs such as ECG (electrocardiogram) signals, PPG (photoplethysmogram) signals, RR (respiratory rate), and ACC (acceleration/movement) are sensed, conditioned, encoded, and acoustically transmitted to a nearby receiver—typically a smartphone, tablet, or other gadget—and can be further relayed to edge and cloud infrastructures. As a case study, this paper presents the real-time transmission and processing of ECG signals. The transmitter integrates an ECG sensing module, an encoder (either a PLL-based FM modulator chip or a microcontroller), and a sound emitter in the form of a standard piezoelectric speaker. The receiver, in the form of a mobile phone, tablet, or desktop computer, captures the acoustic signal via its built-in microphone and executes software routines to decode the data. It then enables a range of control and visualization functions for both local and remote users. Emphasis is placed on describing the system architecture and its key components, as well as the software methodologies used for signal decoding on the receiver side, where several algorithms are implemented using open-source, platform-independent technologies, such as JavaScript, HTML, and CSS. While the main focus is on the transmission of analog data, digital data transmission is also illustrated. The CardiaWhisper system is evaluated across several performance parameters, including functionality, complexity, speed, noise immunity, power consumption, range, and cost-efficiency. Quantitative measurements of the signal-to-noise ratio (SNR) were performed in various realistic indoor scenarios, including different distances, obstacles, and noise environments. Preliminary results are presented, along with a discussion of design challenges, limitations, and feasible applications. Our experience demonstrates that CardiaWhisper provides a low-power, eco-friendly alternative to traditional RF or Bluetooth-based medical wearables in various applications. Full article

The increasing development of gadgets to evaluate stress, wellness, and anxiety has garnered significant attention in recent years. These technological advancements aim to expedite the identification and subsequent treatment of these prevalent conditions. This study endeavors to critically examine the latest smart gadgets and portable techniques utilized for diagnosing depression, stress, and emotional trauma while also exploring the underlying biochemical processes associated with their identification. Integrating various detectors within smartphones and smart bands enables continuous monitoring and recording of user activities. Given their widespread use, smartphones, smartwatches, and smart wristbands have become indispensable in our daily lives, prompting the exploration of their potential in stress detection and prevention. When individuals experience stress, their nervous system responds by releasing stress hormones, which can be easily identified and quantified by smartphones and smart bands. The study in this paper focused on the examination of anxiety and stress and consistently employed “heart rate variability” (HRV) characteristics for diagnostic purposes, with superior outcomes observed when HRV was combined with “electroencephalogram” (EEG) analysis. Recent research indicates that electrodermal activity (EDA) demonstrates remarkable precision in identifying anxiety. Comparisons with HRV, EDA, and breathing rate reveal that the mean heart rate employed by several commercial wearable products is less accurate in identifying anxiety and stress. This comprehensive review article provides an evidence-based evaluation of intelligent gadgets and wearable sensors, highlighting their potential to accurately assess stress, wellness, and anxiety. It also identifies areas for further research and development. Full article

Quantized large language models are large language models (LLMs) optimized for model size while preserving their efficacy. They can be executed on consumer-grade computers without the powerful features of dedicated servers needed to execute regular (non-quantized) LLMs. Because of their ability to summarize, answer questions, and provide insights, LLMs are being used to analyze large texts/documents. One of these types of large texts/documents are Internet of Things (IoT) privacy policies, which are documents specifying how smart home gadgets, health-monitoring wearables, and personal voice assistants (among others) collect and manage consumer/user data on behalf of Internet companies providing services. Even though privacy policies are important, they are difficult to comprehend due to their length and how they are written, which makes them attractive for analysis using LLMs. This study evaluates how quantized LLMs are modeling the language of privacy policies to be potentially used to transform IoT privacy policies into simpler, more usable formats, thus aiding comprehension. While the long-term goal is to achieve this usable transformation, our work focuses on evaluating quantized LLM models used for IoT privacy policy language. Particularly, we study 4-bit, 5-bit, and 8-bit quantized versions of the large language model Meta AI version 2 (Llama 2) and the base Llama 2 model (zero-shot, without fine-tuning) under different metrics and prompts to determine how well these quantized versions model the language of IoT privacy policy documents by completing and generating privacy policy text. Full article

A coplanar-waveguide-type fed half-circular spike-shaped monopole antenna is designed on textile substrates and analyzed in this paper. The most suitable textile substrate is identified in this work by testing the current model performance characteristics on silk, jeans and cotton fabrics and is presented this analytical study. The cotton material model provided a bandwidth of 9.4 GHz, the silk material provided a 9.2 GHz bandwidth and the jeans material provided 9.1 GHz. A maximum gain of 9.5 dB was attained for 3.6 GHz of the 5G band and 8.2 dB for 5.8 GHz of the WLAN band. The antenna is prototyped on cotton substrate, bending analysis is also performed at 15 degrees, 30 degrees and 45 degrees in vertical and horizontal conditions and we find satisfactory results for the specified application. Compact, wearable antennas with varied performance are in demand as wireless communication systems evolve. The antenna is designed for wearable and textile-integrated wireless communication. The textile substrate makes the antenna flexible and can be integrated into garments, wearable gadgets and smart textiles. This paper describes how to choose textile materials and design a half-circular spike monopole antenna. Electromagnetic simulations evaluate the antenna’s impedance matching, radiation pattern and bandwidth. The CPW feedline is designed to efficiently transfer power to the antenna, improving performance. This study also examines the antenna’s longevity and resilience in textile materials, addressing real-world issues like bending and washing. This examination verifies the antenna’s wearable functionality and reliability. Full article

Wireless Body Area Networks (WBANs) are an emerging industrial technology for monitoring physiological data. These networks employ medical wearable and implanted biomedical sensors aimed at improving quality of life by providing body-oriented services through a variety of industrial sensing gadgets. The sensors collect vital data from the body and forward this information to other nodes for further services using short-range wireless communication technology. In this paper, we provide a multi-aspect review of recent advancements made in this field pertaining to cross-domain security, privacy, and trust issues. The aim is to present an overall review of WBAN research and projects based on applications, devices, and communication architecture. We examine current issues and challenges with WBAN communications and technologies, with the aim of providing insights for a future vision of remote healthcare systems. We specifically address the potential and shortcomings of various Wireless Body Area Network (WBAN) architectures and communication schemes that are proposed to maintain security, privacy, and trust within digital healthcare systems. Although current solutions and schemes aim to provide some level of security, several serious challenges remain that need to be understood and addressed. Our aim is to suggest future research directions for establishing best practices in protecting healthcare data. This includes monitoring, access control, key management, and trust management. The distinguishing feature of this survey is the combination of our review with a critical perspective on the future of WBANs. Full article

The emergence of magnetic polymer composites has had a transformative impact on the field of soft robotics. This overview will examine the various methods by which innovative materials can be synthesized and utilized. The advancement of soft robotic systems has been significantly enhanced by the utilization of magnetic polymer composites, which amalgamate the pliability of polymers with the reactivity of magnetic materials. This study extensively examines the production methodologies involved in dispersing magnetic particles within polymer matrices and controlling their spatial distribution. The objective is to gain insights into the strategies required to attain the desired mechanical and magnetic properties. Additionally, this study delves into the potential applications of these composites in the field of soft robotics, encompassing various devices such as soft actuators, grippers, and wearable gadgets. The study emphasizes the transformative capabilities of magnetic polymer composites, which offer a novel framework for the advancement of biocompatible, versatile soft robotic systems that utilize magnetic actuation. Full article

Due to the growth of sensor technology, more affordable integrated circuits, and connectivity technologies, the usage of wearable equipment and sensing devices for monitoring physical activities, whether for wellness, sports monitoring, or medical rehabilitation, has exploded. The current literature review was performed between October 2022 and February 2023 using PubMed, Web of Science, and Scopus in accordance with P.R.I.S.M.A. criteria. The screening phase resulted in the exclusion of 69 articles that did not fit the themes developed in all subchapters of the study, 41 articles that dealt exclusively with rehabilitation and orthopaedics, 28 articles whose abstracts were not visible, and 10 articles that dealt exclusively with other sensor-based devices and not medical ones; the inclusion phase resulted in the inclusion of 111 articles. Patients who utilise sensor-based devices have several advantages due to rehabilitating a missing component, which marks the accomplishment of a fundamental goal within the rehabilitation program. As technology moves faster and faster forward, the field of medical rehabilitation has to adapt to the time we live in by using technology and intelligent devices. This means changing every part of rehabilitation and finding the most valuable and helpful gadgets that can be used to regain lost functions, keep people healthy, or prevent diseases. Full article

Energy storage devices such as supercapacitors (SCs), if equipped with built-in energy harvesters such as piezoelectric nanogenerators, will continuously power wearable electronics and become important enablers of the future Internet of Things. As wearable gadgets become flexible, energy items that can be fabricated with greater compliance will be crucial, and designing them with sustainable and flexible strategies for future use will be important. In this review, flexible supercapacitors designed with built-in nanogenerators, mainly piezoelectric nanogenerators, are discussed in terms of their operational principles, device configuration, and material selection, with a focus on their application in flexible wearable electronics. While the structural design and materials selection are highlighted, the current shortcomings and challenges in the emerging field of nanogenerators that can be integrated into flexible supercapacitors are also discussed to make wearable devices more comfortable and sustainable. We hope this work may provide references, future directions, and new perspectives for the development of electrochemical power sources that can charge themselves by harvesting mechanical energy from the ambient environment. Full article

This study aimed to systematically review the application and research progress of flexible microfluidic wearable devices in the field of sports. The research team thoroughly investigated the use of life signal-monitoring technology for flexible wearable devices in the domain of sports. In addition, the classification of applications, the current status, and the developmental trends of similar products and equipment were evaluated. Scholars expect the provision of valuable references and guidance for related research and the development of the sports industry. The use of microfluidic detection for collecting biomarkers can mitigate the impact of sweat on movements that are common in sports and can also address the issue of discomfort after prolonged use. Flexible wearable gadgets are normally utilized to monitor athletic performance, rehabilitation, and training. Nevertheless, the research and development of such devices is limited, mostly catering to professional athletes. Devices for those who are inexperienced in sports and disabled populations are lacking. Conclusions: Upgrading microfluidic chip technology can lead to accurate and safe sports monitoring. Moreover, the development of multi-functional and multi-site devices can provide technical support to athletes during their training and competitions while also fostering technological innovation in the field of sports science. Full article

Background: The development of wearables has facilitated the monitoring of biomedical parameters in everyday life. One of the most common sensors of these gadgets is the photoplethysmograph (PPG); hence, the proper processing and interpretation of the PPG signal are essential. Besides pulse rate detection, these devices—together with an ECG—compute the pulse arrival time (PAT), from which the actual beat-to-beat blood pressure can be estimated. The heart rate shows asymmetrical accelerations and decelerations, quantified by the parameters of heart rate asymmetry (HRA). In the present study, we investigated the influences of different breathing-patterns on the PATs and HRA parameters. Methods: The authors evaluated 5 min simultaneous respiratory-, ECG- and PPG-signal recordings of 35 healthy, young volunteers specifically expressing the following breathing patterns: metronome-controlled inspiration, and both inspiration and expiration controlled at 1:1 and 1:2 ratios, respectively. The records were analyzed by HRVScan_Merge v3.2 software. The PAT values were calculated at eight different reference points. The HRA parameters and the PAT values at different breathing patterns were compared using the Friedman test and post hoc Wilcoxon paired-sample test. Results: Porta- and Guzik-indices significantly increased at 1:1 breathing compared to 1:2 and single-paced breathing. PATs increased significantly in dual-paced series compared to single-paced series at each reference point. Conclusion: Based on our results, the increased PATs at dual-paced versus single-paced breathing may indicate the involvement of cognitive functions. The symmetrical respiration ratio increases the heart rate symmetry; however, this effect is not detectable in the periphery through the PATs. Full article

Precision livestock farming has a crucial function as farming grows in significance. It will help farmers make better decisions, alter their roles and perspectives as farmers and managers, and allow for the tracking and monitoring of product quality and animal welfare as mandated by the government and industry. Farmers can improve productivity, sustainability, and animal care by gaining a deeper understanding of their farm systems as a result of the increased use of data generated by smart farming equipment. Automation and robots in agriculture have the potential to play a significant role in helping society fulfill its future demands for food supply. These technologies have already enabled significant cost reductions in production, as well as reductions in the amount of intensive manual labor, improvements in product quality, and enhancements in environmental management. Wearable sensors can monitor eating, rumination, rumen pH, rumen temperature, body temperature, laying behavior, animal activity, and animal position or placement. Detachable or imprinted biosensors that are adaptable and enable remote data transfer might be highly important in this quickly growing industry. There are already multiple gadgets to evaluate illnesses such as ketosis or mastitis in cattle. The objective evaluation of sensor methods and systems employed on the farm is one of the difficulties presented by the implementation of modern technologies on dairy farms. The availability of sensors and high-precision technology for real-time monitoring of cattle raises the question of how to objectively evaluate the contribution of these technologies to the long-term viability of farms (productivity, health monitoring, welfare evaluation, and environmental effects). This review focuses on biosensing technologies that have the potential to change early illness diagnosis, management, and operations for livestock. Full article

Wearable devices such as smartwatches, wristbands, and GPS shoes are commonly employed for fitness and wellness as they enable people to observe their day-to-day health status. These gadgets encompass sensors to accumulate data related to user activities. Clinical act graph devices come under the class of wearables worn on the wrist to compute the sleep parameters by storing sleep movements. Sleep is very important for a healthy lifestyle. Inadequate sleep can obstruct physical, emotional, and mental health, and could result in several illnesses such as insulin resistance, high blood pressure, heart disease, stress, etc. Recently, deep learning (DL) models have been employed for predicting sleep quality depending upon the wearables data from the period of being awake. In this aspect, this study develops a new wearables-assisted smart health monitoring for sleep quality prediction using optimal deep learning (WSHMSQP-ODL) model. The presented WSHMSQP-ODL technique initially enables the wearables to gather sleep-activity-related data. Next, data pre-processing is performed to transform the data into a uniform format. For sleep quality prediction, the WSHMSQP-ODL model uses the deep belief network (DBN) model. To enhance the sleep quality prediction performance of the DBN model, the enhanced seagull optimization (ESGO) algorithm is used for hyperparameter tuning. The experimental results of the WSHMSQP-ODL method are examined under different measures. An extensive comparison study shows the significant performance of the WSHMSQP-ODL model over other models. Full article

This research combines two emerging technologies, the IoT and blockchain, and investigates their potential and use in the healthcare sector. In healthcare, IoT technology can be utilized for purposes such as remotely monitoring patients’ health. This paper details ongoing research towards individualized health monitoring using wearable gadgets. The goal of improving healthcare facilities and improvement of the quality of life of citizens naturally brings up Internet of Things (IoT) technologies for consideration. Health observation is exceptionally critical in terms of avoidance, especially since the early determination of illnesses can minimize trouble and treatment costs. The cornerstones of intelligent, integrated, and individualized healthcare are continuous monitoring of physical signs and evaluation of medical data. To build a more reliable and robust IoMT model, the study will monitor the application of blockchain technology in federated learning (FL). A viable way to address the heterogeneity problem in federated learning is to design the system, data, and model tiers to lessen heterogeneity and produce a high-quality, tailored model for each endpoint. Blockchain-based federated learning allows for smarter simulations, lower latency, and lower power consumption while maintaining privacy at the same time. This solution provides another immediate benefit: in addition to having a shared model upgrade, the updated model on phones will now be used automatically, giving personalized knowledge about the phone is used. Full article

Type 2 diabetes mellitus (T2DM) is a metabolic disorder wherein the patients require DM management to keep their blood glucose under proper and regular control. Diabetes mellitus can be managed with the help of technologies, one of which is mobile health. Mobile health is an innovation in telemedicine that utilizes gadgets as a medium to access digitally based health information and services by utilizing electronic devices connected to the Internet. Mobile health services are distinguished based on interactions between users and medical personnel; namely, interactive and non-interactive services. The developed application can integrate Android mobile application software with supporting hardware, such as a glucometer, a wearable band, a heart rate sensor, a treadmill, and an exercise bike. The provided features in this mobile application include the monitoring of medication, food intake, exercise, and sleep. This study’s goal was to create a mobile application architecture for type 2 diabetes mellitus mobile applications. This research focused on developing an architecture for mobile diabetes applications, a hardware block diagram design, and an architecture of sensors for a type 2 diabetes mellitus mobile application. Full article