Twin Meander Coil

Energy-efficient and unconstrained wearable sensing platforms are essential for ubiquitous healthcare and activity monitoring applications. This paper presents Twin Meander Coil for wirelessly connecting battery-free on-body sensors to a textile-based reader knitted into clothing. This connection is based on passive inductive telemetry (PIT), wherein an external reader coil collects data from passive sensor coils via the magnetic field. In contrast to standard active sensing techniques, PIT does not require the reader to power up the sensors. Thus, the reader can be fabricated using a lossy conductive thread and industrial knitting machines. Furthermore, the sensors can superimpose information such as ID, touch, rotation, and pressure on its frequency response. However, conventional PIT technology needs a strong coupling between the reader and the sensor, requiring the reader to be small to the same extent as the sensors' size. Thus, applying this technology to body-scale sensing systems is challenging. To enable body-scale readout, Twin Meander Coil enhances the sensitivity of PIT technology by dividing the body-scale meander-shaped reader coils into two parts and integrating them so that they support the readout of each other. To demonstrate its feasibility, we built a prototype with a knitting machine, evaluated its sensing ability, and demonstrated several applications.

An improved Whale Optimization Approach for Effective Data Transmission for IoT Communication

Internet of Things (IoT) offers interconnection among several wireless communication devices for the provision of device accessibility and in-built capacity. IoT provides device interaction and provision of advantages capability for networking and socialization with consideration of intermediate devices. Through innovation in technology IoT devices convert cyber environments with hyper-connectivity. IoT communication contains several smart devices such as body sensors, smartphones, tags, electronic gadgets, and so on. IoT communication is involved in the provision of heterogeneous connectivity among devices for the provision of interface and connectivity for enhancing service quality. The data sending among IoT devices is affected by several threats that have an impact on the network’s performance. To overcome the limitation related to IoT communication, it is necessary to develop an appropriate technique for enhancing IoT network communication performance. In this research developed a multi-channel routing approach is adopted in IoT communication. The developed approach utilizes a meta-heuristics approach with probability-based characteristics. For the meta-heuristics approach this research utilizes whale optimization technique combined with probability characteristics for improving the IoT communication performance of the network. The proposed approach utilizes initially constructs the IoT communication path for information sharing and gathering. This path information is identified through the objective function of a meta-heuristic approach. Based on the objective function hoping between the devices is minimized through which data are transmitted in the network. Simulation is performed as a unique proposed approach with a coverage area of 100 meters. For identification of the optimal path in the network, WOA identifies the path of communication through probability function. Comparative analysis of research exhibited that WOA provides significant performance with the identification of optimal value at the range of 1.0746e-78. Further, the proposed probability-based WOA approach significantly improves the performance of the IoT network.

Respiration Based Non-Invasive Approach for Emotion Recognition Using Impulse Radio Ultra Wide Band Radar and Machine Learning

Emotion recognition gained increasingly prominent attraction from a multitude of fields recently due to their wide use in human-computer interaction interface, therapy, and advanced robotics, etc. Human speech, gestures, facial expressions, and physiological signals can be used to recognize different emotions. Despite the discriminating properties to recognize emotions, the first three methods have been regarded as ineffective as the probability of human’s voluntary and involuntary concealing the real emotions can not be ignored. Physiological signals, on the other hand, are capable of providing more objective, and reliable emotion recognition. Based on physiological signals, several methods have been introduced for emotion recognition, yet, predominantly such approaches are invasive involving the placement of on-body sensors. The efficacy and accuracy of these approaches are hindered by the sensor malfunctioning and erroneous data due to human limbs movement. This study presents a non-invasive approach where machine learning complements the impulse radio ultra-wideband (IR-UWB) signals for emotion recognition. First, the feasibility of using IR-UWB for emotion recognition is analyzed followed by determining the state of emotions into happiness, disgust, and fear. These emotions are triggered using carefully selected video clips to human subjects involving both males and females. The convincing evidence that different breathing patterns are linked with different emotions has been leveraged to discriminate between different emotions. Chest movement of thirty-five subjects is obtained using IR-UWB radar while watching the video clips in solitude. Extensive signal processing is applied to the obtained chest movement signals to estimate respiration rate per minute (RPM). The RPM estimated by the algorithm is validated by repeated measurements by a commercially available Pulse Oximeter. A dataset is maintained comprising gender, RPM, age, and associated emotions which are further used with several machine learning algorithms for automatic recognition of human emotions. Experiments reveal that IR-UWB possesses the potential to differentiate between different human emotions with a decent accuracy of 76% without placing any on-body sensors. Separate analysis for male and female participants reveals that males experience high arousal for happiness while females experience intense fear emotions. For disgust emotion, no large difference is found for male and female participants. To the best of the authors’ knowledge, this study presents the first non-invasive approach using the IR-UWB radar for emotion recognition.

Garment-Integrated Thermoelectric Generator Arrays for Wearable Body Heat Harvesting

Wearable thermoelectric generator arrays have the potential to use waste body heat to power on-body sensors and create, for example, self-powered health monitoring systems. In this work, we demonstrate that a surface coating of a conducting polymer poly(3,4-ethylenedioxythiophene) (PEDOT-Cl), created on one face of a wool felt using a chemical vapor deposition method was able to manifest a Seebeck voltage when subjected to a temperature gradient. The wool felt devices can produce voltage outputs of up to 120 mV when measured on a human body. Herein, we present a strategy to create arrays of polymer-coated fabric thermopiles and to integrate such arrays into familiar garments that could become a part of a consumer’s daily wardrobe. Using wool felt as the substrate fabric onto which the conducting polymer coating is created allowed for a higher mass loading of the polymer on the fabric surface and shorter thermoelectric legs, as compared to our previous iteration. Six or eight of these PEDOT-Cl coated wool felt swatches were sewed onto a backing/support fabric and interconnected with silver threads to create a coupled array, which was then patched onto the collar of a commercial three-quarter zip jacket. The observed power output from a six-leg array while worn by a healthy person at room temperature (ΔT = 15 °C) was 2 µW, which is the highest value currently reported for a polymer thermoelectric device measured at room temperature.

Recent advancements in flexible and wearable sensors for biomedical and healthcare applications

In the past decades, with the increasing awareness of personal health management, various types of flexible and wearable body sensors have been developed. Thanks to the superiorities of advanced wearable technologies, including miniaturization and portability, stretchability and comfortability, intelligent human-machine interface, etc., flexible and wearable body sensors hold great promise in the next generation biomedicine and healthcare applications. Unfortunately, the data precision, response speed, sensitivity and selectivity, durability, compatibility with flexible substrates, and preparation technics still need to be enhanced and refined to meet the requirements of clinical evaluations or even commercialization. According to the working principles, flexible and wearable sensing platform can be roughly divided into four categories: physical sensors, chemical sensors, biosensors, and the fusion of different types of sensors. Here, a brief review focused on recent developments of these flexible and wearable sensors applied especially to biomedicine and healthcare is presented. In addition, the existing challenges and potential opportunities ahead in flexible and wearable sensor technologies are discussed. At last, an outlook of wearable sensing platforms in biomedicine and healthcare is proposed. We hope this review can provide guidance for superior flexible and wearable sensing technologies in the future.

Possibilities of Virtual Reality Technologies for the Development of Gaming Applications

The rapid development of virtual and augmented reality technologies is currently taking place in almost all spheres of activity. Elements of virtual and augmented reality are used in such areas as education, medicine, transport, gaming, tourism and others. The active spread of these technologies causes the emergence of special competencies in the IT labor market and, as a result, the formation of new professions.Many Russian universities are training students in IT training areas. Specialization in the development of computer games and virtual reality applications has begun recently. The provision of practical classes is accompanied by specific tasks, which gives students the opportunity to improve the use of software and technical devices.The relevance of the research is determined by the current demand for the use of the latest technologies by IT developers in the field of creating computer games. Today, technologies that provide a player’s immersion in virtual reality are becoming more and more popular. One of these technologies is a suit with wearable sensors that track a person’s position in space in real time. However, there are quite a few real described projects in the literature and on the Internet. This study examines the process of developing a task for creating a game application using virtual reality technology: a suit with wearable sensors for teaching students.Materials and methods of research. Timely identification of the needs of the IT market in personnel training allows educational organizations to form new training programs of different levels of training. This approach makes it possible to target the educational and methodological materials being developed to use the latest achievements in the development of the field under study.Using a systematic approach, the study characterizes virtual reality suits and sensors for monitoring the position in the user’s space. Thus, the goal of the task was to ensure the immersiveness and convenience of interaction between the player and the game environment.Based on materials on software, position sensors in space, the approach of pedagogical design was applied and the procedure was formed for a practical task, reflecting the relevant competencies.Results. The study was conducted on the basis in the framework of laboratory and practical work of students, as well as at a real enterprise. Training in the new profile of the direction of training “Applied informatics” is fully equipped with all the latest technologies in this field. As a result of the work, the content of the practical task was developed.Real development of virtual and augmented reality applications is conducted jointly with students. Almost all projects used a suit with body sensors.Conclusion. Our study examines in detail the process of developing an application using a suit with wearable sensors for further training of students. Based on the results, work can be carried out on real projects for any field. Based on the research materials, it is planned to issue a textbook for students with the profile of developing computer games and virtual / augmented reality applications.

Stress Prediction and Detection Using IoT and Deep Learning: A Comprehensive Review

Stress is the part of life that is an unpleasant emotional state that individuals experience in situations like working for long hours ahead of a computer. Stress is often positive, but it can affect your health if it's chronic. Also Stress is a characteristic response to different pressure instigating factors which can prompt physiological and conduct changes. On the off chance that continues for a more extended period, stress can cause destructive consequences for our body. The body sensors alongside the idea of the Internet of Things can give rich data about one's psychological and actual wellbeing. The proposed work focuses the mind level and identifies enthusiastic changes that happened in an individual when he/she is under pressure, melancholy, or uneasiness. On recognizing, A hint message will be sent to their relatives so that they will assist that individual with emerging from his/her circumstances to fostering an IoT framework which can proficiently identify the anxiety of an individual and give an input which can help the individual to adapt to the stressors. Index Terms: Stress Detection, IoT, Heartbeat Rate, Sensors, Mind analysis & Monitoring.

Material Response: Technology, Material Systems and Responsive Design

This paper investigates the role technology and materials play in making meaningful connections between people, architectural space and the workplace. It indicates that design can synergize with responsive technology and material systems to leverage new power for future workplace interaction design. We have created a spatial prototype paired with a series of simulations that act as a proposal to stimulate workplace interaction. The project employs a responsive ceiling that combines a fluid computational pattern with temperature-responsive bi-material laminates with thermochromic coatings and electrically programmed micro-controllers. The project is then connected to a computer code that computes readings based upon ongoing interactions with humans wearing body sensors. The methodology categorizes the simulation results into aroused states and calm states. As the computational patterns and colors change, we are made aware of the relationships between space, technology, and the human sensorium. This conversation brings insight into how we can design more effectively for workplace interactions.

The Rise of Wearable Devices during the COVID-19 Pandemic: A Systematic Review

The COVID-19 pandemic has wreaked havoc globally and still persists even after a year of its initial outbreak. Several reasons can be considered: people are in close contact with each other, i.e., at a short range (1 m), and the healthcare system is not sufficiently developed or does not have enough facilities to manage and fight the pandemic, even in developed countries such as the USA and the U.K. and countries in Europe. There is a great need in healthcare for remote monitoring of COVID-19 symptoms. In the past year, a number of IoT-based devices and wearables have been introduced by researchers, providing good results in terms of high accuracy in diagnosing patients in the prodromal phase and in monitoring the symptoms of patients, i.e., respiratory rate, heart rate, temperature, etc. In this systematic review, we analyzed these wearables and their need in the healthcare system. The research was conducted using three databases: IEEE Xplore®, Web of Science®, and PubMed Central®, between December 2019 and June 2021. This article was based on the PRISMA guidelines. Initially, 1100 articles were identified while searching the scientific literature regarding this topic. After screening, ultimately, 70 articles were fully evaluated and included in this review. These articles were divided into two categories. The first one belongs to the on-body sensors (wearables), their types and positions, and the use of AI technology with ehealth wearables in different scenarios from screening to contact tracing. In the second category, we discuss the problems and solutions with respect to utilizing these wearables globally. This systematic review provides an extensive overview of wearable systems for the remote management and automated assessment of COVID-19, taking into account the reliability and acceptability of the implemented technologies.