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Wearables: Fundamentals, advancements, and a roadmap for the future
Abstract
Today, the term “wearable” goes beyond the traditional definition of clothing; it refers to an accessory that enables personalized mobile information processing. In this chapter, we define the concept of wearables, present their attributes, and discuss their role at the core of an ecosystem for harnessing big data. We, then present the taxonomy for wearables and trace their advancements over the years. We discuss the practical challenges associated with the use of wearables and propose the concept of a meta-wearable – in the form of a wearable motherboard – as a feasible solution. We gaze into the future of wearables and propose a transdisciplinary approach to realizing this future that will transform the field and contribute to enhancing the quality of life for everyone.
... On one hand, the integration of digital fabrication technologies (DFT), intended both as an additive (e.g., 3D printing) and subtractive (e.g., laser-cutting) ways of prototyping/manufacturing products starting from 2D and 3D files does not impact only design practices and manufacturing processes, but potentially affects the development of innovative industrial models like digital craftsmanship, on-demand & bespoke production, and distributed manufacturing. Besides, smart wearable technologies (SWET), intending microcomputers and digital components integration into garments, have been already introduced in research activities, meanwhile struggling to be ready for commercialization (Park et al., 2021). ...
... The collaborative and experiential learning activities implemented in the AMSF modules were focused on discovering and solving problems through prototyping experiences with the ambition to give students more profound subject-specific knowledge, along with developing soft skills. Literature shows that these strategies are relevant in the context of teaching DFT and SWET (Park et al., 2021). Reflecting on the educational path, we acknowledge that several implementations at the level of organization and structure of the course could increase interdisciplinarity and boost both soft and subject-specific skills. ...
As a creative industry with high cultural, social, and environmental impacts, Fashion is crucially demanding a paradigmatic shift through digital transformation toward a positive, sustainable change. Therefore, fashion education needs to nurture professionals able to tackle increasingly complex challenges, delving into technological systems and aiming at meaningful environmental, economic, cultural, and societal transformations. New learning paths, approaches, and tools should prepare future fashion designers with a hybrid set of skills placed halfway between design, technology, science, and arts. This paper presents the lessons learned from the Advanced Manufacturing for Sustainable Fashion (ASMF) module conducted at Politecnico di Milano (Design School) in the course Design for the Fashion System. While exploring digital fabrication and smart wearable technologies, students delve into prototyping activities aiming at reflecting on sustainability and fashion design practices’ impacts. The paper describes the used learning tools and approaches and reports on instructional and pedagogical learning outcomes, problems, and future implementation of interdisciplinary educational experiences toward a systemic design paradigm.
... The concept of Wearable Technology (WT) has been used in various fields such as healthcare, sports, entertainment, electronics, textiles, and the defense industry for a long time [1][2][3][4][5]. Thanks to the opportunities provided by sensor and internet technology, WT has made significant progress in the last two decades and ha become devices that we frequently use in our daily lives. ...
... Shen et al. defined the concept of WT as mobile electronic devices that can be comfortably worn on the user's body or attached to their clothing [6]. Park et al., stated that WT devices differ from traditional clothing and enable personalized mobile computing [4]. Coyle and Diamond emphasized that WT devices should be soft, flexible, In the context of academic inquiry utilizing the Web of Science (WoS) database, an examination of research areas pertaining to wearables and sports reveals key insights, as illustrated in Figure 3. ...
Wearable technology is increasingly vital for improving sports performance through real-time data analysis and tracking. Both professional and amateur athletes rely on wearable sensors to enhance training efficiency and competition outcomes. However, further research is needed to fully understand and optimize their potential in sports. This comprehensive review explores the measurement and monitoring of athletic performance, injury prevention, rehabilitation, and overall performance optimization using body wearable sensors. By analyzing wearables’ structure, research articles across various sports, and commercial sensors, the review provides a thorough analysis of wearable sensors in sports. Its findings benefit athletes, coaches, healthcare professionals, conditioners, managers, and researchers, offering a detailed summary of wearable technology in sports. The review is expected to contribute to future advancements in wearable sensors and biometric data analysis, ultimately improving sports performance. Limitations such as privacy concerns, accuracy issues, and costs are acknowledged, stressing the need for legal regulations, ethical principles, and technical measures for safe and fair use. The importance of personalized devices and further research on athlete comfort and performance impact is emphasized. The emergence of wearable imaging devices holds promise for sports rehabilitation and performance monitoring, enabling enhanced athlete health, recovery, and performance in the sports industry.
... Consumers' perceptions of the novelty of the wearable plays a key role in their adoption intention and purchase decisions (Kalantari, 2017). Generally, an ideal wearable needs to possess physical attributes such as being lightweight, aesthetically pleasing, its visibility and shape conformability, and multi-functional attributes such as configurability, responsiveness, and having a sufficient data bandwidth for interactivity (Park et al., 2014). ...
... sociality-related (Section 2.1.4) wearable affordances have been widely mentioned in the relevant literature (Buruk and Ozcan, 2018;Davis et al., 1989;Dvorak, 2008;Faust and Yoo, 2006;Havlucu et al., 2017;Houzangbe et al., 2018;Högberg et al., 2019;Jing et al., 2017;Nacke et al., 2011;Park et al., 2014;Wright and Keith, 2014). In the following subsections, we review specific wearable features as exhaustively as possible, so as to provide a more comprehensive view of the understanding of wearable technologies for gaming. ...
... Secondly, it must comprise advanced circuitry, wireless connectivity and at least a minimal level of independent processing capability in order to directly transfer the data by the help of sensors (IHS Electronics & Media, 2020). Park et al. (2014) suggested a more comprehensive taxonomy for classifying WTs based on features such as functionality (single vs. multiple), type (active vs. passive), deployment mode (invasive vs. non-invasive), communication mode (wired vs. wireless), field of use, and reusability (disposable vs. reusable). ...
... Technology is considered to be wearable technology when "not only it can be worn, but also has the capability of incorporating information technology in order to be able to communicate autonomously and process information on the go" Park et al. (2014). This capability is basically what makes these technologies 'smart'. ...
... They can be designed to be simultaneously lightweight, strong, flexible, water or vapor permeable and resistive to wear [5,6]. A special property of textiles is their anisotropy, which induces self-alignment to contact surfaces [7], such as in composite preforms [8] or wearable textiles [9]. Due to their excellent properties and tunability, textiles constitute an integral part of medical devices such as wound dressings, implants [1,10] and tissue scaffolds [11], lay the foundation for composite structures and laminates [12], serve as biosensors, actuators, and communication devices [13,14] and provide mechanical interfaces of wearables [9]. ...
... A special property of textiles is their anisotropy, which induces self-alignment to contact surfaces [7], such as in composite preforms [8] or wearable textiles [9]. Due to their excellent properties and tunability, textiles constitute an integral part of medical devices such as wound dressings, implants [1,10] and tissue scaffolds [11], lay the foundation for composite structures and laminates [12], serve as biosensors, actuators, and communication devices [13,14] and provide mechanical interfaces of wearables [9]. ...
3D printing allows the fabrication of complex microstructures that would traditionally require specialized machinery. In the fabrication of textiles, 3D printing may enable unique yarn structures, greater manufacturing flexibility and facilitate the development of personalized and tunable devices. In literature, 3D printed textiles have not been subjected to a thorough mechanical characterization. In this paper, a generative model of 3D printed biaxial weaves is developed and a parametric study to effectively map the design parameters to the weaves’ mechanical properties is performed via a two-stage Design-of-Experiments methodology. The samples are printed with material jetting layer by layer in planar direction and destructively tested in tension to obtain the resulting stress-strain behavior. The stress-strain curves are approximated by a bilinear model characterized predominantly by a transition strain and the major modulus after transition. The transition strain is influenced by the load direction and the weave pattern, while the major modulus is impacted by the load direction, the yarn diameter, the weave pattern and the yarn spacing in descending order. Further evaluation of the fracture behavior shows a mitigation of layer-wise delamination. This result indicates that material jetting can enable the production of arbitrary, quasi-continuous textile structures. The characterization results presented here may pave the way towards the design of textiles with spatially varying mechanical properties.
... Physical monitoring Wearable technology is a term that refers to devices or clothing that can be worn by workers and have electronic or wireless capabilities (Park and Jayaraman, 2021;Seneviratne et al., 2017). These devices can collect and transmit data about the worker's health, activity, location, and environment. ...
This study aims to identify a cross-cultural dimension of the benefits of sensing technology application in the construction industry. In a cross-sectional survey, data were collected from construction professionals across three countries. In all, 129 construction professionals participated in the survey, of which 120 were used for the analysis. Mean score ranking and principal component analysis were the analytical methods. This study found construction project performance, safety atmosphere improvement, and cost reduction as the benefits of applying sensing technology in the construction industry. Also, the respondents ranked enhanced quality of construction project delivery time, time-saving, and improved productivity as the two leading benefits of sensing technology in the construction industry. The findings provide construction project managers with the crosscountry benefits of sensing technology applications in project management. This is expected to increase the adaptation of sensing technology in the industry for its sustainability. It also adds another perspective on applying sensing technology to construction management. This study provides a cross-cultural insight into the benefits of sensing technology application in the construction industry, the first of its kind. It further introduces new dimensions of the benefits of sensing technology application in construction project management literature. Keywords: construction industry/cross-culture/health and safety/sensing technology/technology adaptation/UN SDG 3: Good health and well-being/UN SDG 8: Decent work and economic growth/UN SDG 13: Climate action/UN SDG 17: Partnerships for the goals
... The portability and comfort of today's wearable devices allow for the easy collection of large amounts of human physiological signals in a noninvasive way. This capability is further enhanced by advancements in sensor miniaturization technology, allowing for the production of increasingly smaller, ergonomic, convenient, and more efficient devices [26]. While numerous advancements have been made in the collection of respiratory data from home in a short amount of time, there are many barriers to overcome including battery life, material allergy, Bluetooth compatibility, usability, and data privacy. ...
Respiratory frequency and volume are essential physiological signals for diagnosing and managing respiratory diseases such as asthma and chronic obstructive pulmonary disease (COPD). Wearable devices have emerged as a transformative tool for continuous, non-invasive respiratory monitoring and data portals, providing massive real-time data critical for both clinical and home settings. This state-of-the-art review delves into the advancements and applications of wearable respiratory monitoring devices, specifically focusing on inertial measurement units (IMUs), piezoresistive sensors, and optical fiber sensors. Detailed analyses of sensor designs, sensing methods, and clinical applications are presented, highlighting key studies such as the development of low-cost IMU devices for breathing frequency monitoring and the integration of piezoresistive sensors for real-time respiratory rate detection. This review identifies major challenges, including power efficiency, ergonomic design, data accuracy, and data privacy concerns, and also introduces innovative solutions proposed in recent research. Future research directions are suggested to address these challenges and further enhance the capabilities and reliability of wearable respiratory monitoring devices. This review underscores the potential of wearable technology to improve patient outcomes and resource cost burdens through early diagnosis and data creation towards continuous health monitoring and artificial intelligence applications.
... Second, the wide heterogeneity of the devices used at the edge makes data fusion a requirement in many scenarios. In that context, many research opportunities are emerging, with new devices (e.g., wearables [93]) appearing along with new modalities requiring a whole new family of data fusion techniques. One particularly compelling application in this context is urban edge analytics [29], where mobile devices (e.g., autonomous cars) collaboratively detect events with the help of base stations (e.g., smart traffic lights and roadside units). ...
With the emergence of the Internet of Things (IoT) and the rise of shared multimedia content on social media networks, available datasets have become increasingly heterogeneous. Several multimodal techniques for detecting events in data of different types and formats have emerged. Those techniques implement various detection algorithms and present different trade-offs in terms of data fusion. Unfortunately, little is known about their underlying detection mechanisms, as existing comparisons are limited to either unimodal event detection techniques or specific types or representations for multimodal techniques. Understanding the behavior of multimodal event detection techniques remains an acute open research problem. In this work, we present a systematic literature review of multimodal event detection techniques. We describe how various techniques leverage information from different modalities through data fusion. We further propose a novel taxonomy of multimodal event detection techniques according to their temporal orientation and the inner workings of their detection mechanism. Finally, we analyze the datasets and metrics used in previous works as well as their reported results. Our survey allows to uncover the properties of each approach and discuss future research directions in this field.
... Por fim, para atender às necessidades das pessoas com deficiência visual é necessário incorporar a abordagem em visão computacional a um dispositivo wearable (Park e Jayaraman, 2021), ou seja, um dispositivo vestível ou um equipamento que o usuário possa carregar junto ao corpo, como uma peça de roupa. Um exemplo de dispositivo já existente e ao alcance de uma grande parte da população é o smartphone (Sausen e Frozza, 2022), que, por meio de seus sistemas embarcados, dispensam o uso de equipamentos especialmente projetados para este fim (Pret, 2014) (e.g., o smartphone pode ser carregado junto ao corpo, em um bolso na camisa, por exemplo, com sua câmera filmando o ambiente à frente do usuário). ...
A falsificação de cédulas é um problema real que afeta o mundo inteiro, especialmente as pessoas com deficiência visual e as pessoas sem acesso ao sistema financeiro. Neste trabalho, foi realizada uma revisão sistemática da literatura sobre o reconhecimento de cédulas bancárias falsas com o objetivo de levantar o estado da arte atual, respondendo à seguinte questão de pesquisa: ``Quais abordagens em visão computacional foram utilizadas para reconhecer notas falsas?''. Como resultado, esta revisão de literatura selecionou 25 artigos, que passaram por critérios de inclusão e exclusão e foram sumarizados de acordo com o ano de publicação, a moeda utilizada e a abordagem utilizada. Finalmente, uma análise desses resultados foi realizada, apresentando perspectivas para pesquisas futuras. Além disso, este artigo descreve alguns conjuntos de dados relatados pela literatura, que contêm imagens de notas falsas e genuínas disponíveis ao público.
... Some of these key issues include those wearable devices should be friendly so that skin damages do not occur on an individual's body (Iqbal et al., 2021;Ling et al., 2020;Subhan et al., 2023). Furthermore, as the majority of wearables run on rechargeable batteries, it should be ensured that these batteries are of low consumption and have higher efficiency when wearable devices are used by patients (Jiang et al., 2015;Park & Jayaraman, 2021;Subhan et al., 2023). Lastly, as it understood that wearable devices collect sensitive health information, it is crucial to ensure that proper safeguards are in place to protect patient confidentiality and comply with regulatory requirements (Sivani & Mishra, 2022;Subhan et al., 2023). ...
Wearable technologies and self-tracking healthcare apps are becoming increasingly popular among people all over the world. Moreover, with the rapid increase in technological advancements, studies on the ease of use and intent to adopt wearable devices have gained prominence in the aftermath of the Covid-19 Pandemic. More specifically, fitness wearables have grown in popularity as health consciousness among the younger and older populations has grown, allowing them to track and monitor their heart rate, calories, sleep, and steps taken throughout the day. These wearable technologies are considered to have a wide range of applications ranging from the workplace to recreational activities. Several studies have shown how the emergence of wearable technology will benefit society, but fewer studies have integrated the practical implementations of wearable technologies and wearable devices which is utilised for personalised healthcare applications. As a result, the current study employs a bibliometric approach using Scopus databases to refine articles related to health tracking applications, remote patient monitoring , chronic disease management, and infectious disease prevention. In doing so, the findings of the study are portrayed in conjunction with VOSviewer, which showcases the key clusters and studies that are related to wearable technologies and their applications as physiological and biometric sensors. More specifically, the findings show that most studies emphasise on how wearable technologies are concentrated as physiological sensors to track important information about an indi-vidual's health, as well as how wearable technologies are widely adopted among older populations and can track critical diseases, enabling effective remote patient monitoring in healthcare fields. Finally, the paper concludes by acknowledging the risks and privacy concerns of using wearable technologies within the healthcare sector.
... The rapid advancement of new technologies has sparked the development and significant commercial impact of wearable smart devices that can be attached to the body to improve quality of life through safety, assistance, and entertainment [1][2][3]. The concept of wearable robotics as person-oriented systems was coined over a decade ago to primarily refer to exoskeletons, orthotic robots, and prosthetic robots [4,5]. ...
The rapid development of wearable technologies is increasing research interest in on-body robotics, where relocatable robots can serve as haptic interfaces, support healthcare measurements, or assist with daily activities. However, on-body mobile robotics poses challenges in aspects such as stable locomotion and control. This article proposes a novel small robot design for moving on human limbs that consists of an open grasping mechanism with a spring linkage, where one side holds a pivoting differential drive base (PDDB) with two spherical rollers, and the other side holds an actuated roller for grasping and stabilization. The spherical rollers maintain contact at three points on the limb, optimizing stability with a minimal number of rollers and integrating DC motors within. The PDDB wheels (spherical rollers) enable directional changes on limb surfaces. The combination of the open mechanism, the PDDB, and the spherical rollers allows adaptability to diameter variations along the limb. Furthermore, the mechanism can be easily put on or removed at any point along the limb, eliminating the need to slip the robot over the hand or foot. The kinematic model for the proposed mechanism has been developed. A cascade control strategy is proposed with an outer loop for stable grasping and an inner loop for trajectory adjustments using PDDB roller velocities. An on-limb robot prototype has been built to test its applicability to human arms. Simulation and experimental results validate the design.
... Embracing WDs in our daily lives has revolutionized human interaction and paved the way for groundbreaking innovations [18,19,27], offering new perspectives also for user modelling and personalization [1,13,23]. ...
Wearable Devices (WDs), encompassing a spectrum from smartwatches to fitness trackers, continuously furnish a wealth of physiological and activity-related data. This trove of information facilitates the creation of robust user models, offering a dynamic lens into users’ daily lives, health patterns, and interaction behaviours. Furthermore, the integration of Brain-Computer Interfaces (BCIs), directly interfacing with neural signals, presents a distinctive vantage point into cognitive processes and emotional states. This integration enriches user models, providing a profound understanding of mental states and engagement levels. While BCIs cannot be strictly categorized as WDs, the latest hardware developments are reaching a size comparable to earphones, anticipating their wearable integration in the near future. However, the exploitation of data from these devices for user modelling and profiling, enhancing personalized activities such as music listening and movie watching, remains an area ripe for exploration.
This workshop proposes an in-depth exploration of the transformative impact that data from WDs and BCIs can exert on user modelling. This initiative seeks to pave the way for a nuanced comprehension of individual preferences, cognitive states, and overall user experiences. The workshop invites researchers, practitioners, and enthusiasts to the convergence of wearable technology, BCIs, and user modelling. Through interactive sessions and discussions, participants will delve into the methodologies, challenges, and opportunities associated with harnessing data from these innovative sources. By fostering collaboration and facilitating knowledge exchange, the workshop aims to propel the current understanding of user modelling by exploiting WDs and BCIs. Attendees will acquire insights into cutting-edge research findings, practical applications, and potential future developments within this rapidly evolving field. Ultimately, the workshop aspires to inspire new research directions, catalyze interdisciplinary collaborations, and cultivate innovative solutions that leverage the synergy between wearable technologies and BCIs to elevate the field of user modelling to unprecedented heights.
... Therefore, the most accurate approach to capturing and understanding patients' motor function is through continuous monitoring of their body movements over an extended period, rather than relying solely on brief assessments during specific exercises. Thanks to the availability of small form factor, lightweight and low-power inertial sensors have already paved the way in the wearable healthcare domain [7,8] and free-living activity monitoring [9][10][11]. Table 1 explains the different proposals suggested for PD patients. ...
Parkinson’s disease (PD) is one of the most unremitting and dynamic neurodegenerative human diseases. Various wearable IoT devices have emerged for detecting, diagnosing, and quantifying PD, predominantly utilizing inertial sensors and computational algorithms. However, their proliferation poses novel challenges concerning security, privacy, connectivity, and power optimization. Clinically, continuous monitoring of patients’ motor function is imperative for optimizing Levodopa (L-dopa) dosage while mitigating adverse effects and motor activity decline. Tracking motor function alterations between visits is challenging, risking erroneous clinical decisions. Thus, there is a pressing need to furnish medical professionals with an ecosystem facilitating comprehensive Parkinson’s stage evaluation and disease progression monitoring, particularly regarding tremor and bradykinesia. This study endeavors to establish a holistic ecosystem centered around an energy-efficient Wi-Fi-enabled wearable bracelet dubbed A-WEAR. A-WEAR functions as a data collection conduit for Parkinson’s-related motion data, securely transmitting them to the Cloud for storage, processing, and severity estimation via bespoke learning algorithms. The experimental results demonstrate the resilience and effectiveness of the suggested technique, with 86.4% accuracy for bradykinesia and 90.9% accuracy for tremor estimation, along with good sensitivity and specificity for each scoring class. The recommended approach will support the timely determination of the severity of PD and ongoing patient activity monitoring. The system helps medical practitioners in decision making when initially assessing patients with PD and reviewing their progress and the effects of any treatment.
... In this paper, we consider a specific type of digital technology -wearable devices, i.e. electronic devices that can be worn directly on the body and are capable of sensing, storing, processing as well as sending and receiving data about the user over the Internet (4). We provide a detailed analysis of associated opportunities and challenges for using wearables to promote healthy ageing. ...
Digital technologies hold promise to modernize healthcare. Such opportunity should be leveraged also to address the needs of rapidly ageing populations. Against this backdrop, this paper examines the use of wearable devices for promoting healthy ageing. Previous work has assessed the prospects of digital technologies for health promotion and disease prevention in older adults. However, to our knowledge, ours is one of the first attempts to specifically address the use of wearables for healthy ageing, and to offer ethical insights for assessing the prospects of leveraging wearable devices in this context. We provide an analysis of the considerable opportunities associated with the use of wearables for healthy ageing, with a focus on the five domains of intrinsic capacity: locomotion, sensory functions, psychological aspects, cognition, and vitality. We then highlight current limitations and ethical challenges of such approach to healthy ageing, including issues related to access, inclusion, privacy, surveillance, autonomy, and regulation. We conclude by discussing the implications of our analysis in light of current debates on the ethics of digital health, and suggest measures to address the identified challenges.
... The redefinition of "wearable" within the "World of Wearables (WOW)" integrates technology to measure vital signs, maintaining a central focus on the functionality and practicality of clothing [5]. This updated definition mirrors the dynamic convergence of fashion and technology in the domain of wearable devices. ...
... Wearable devices, including smart watches, smart glasses, and fitness trackers, have embedded sensors and apps capable of collecting data, storing it, and sending it via the cloud, standalone device, or smartphone (Information Resources Management Association, 2018; Mardonova & Choi, 2018;Rani et al., 2021;Weber, 2015). It has reshaped many life experiences, such as healthcare, entertainment, sports, public safety, posture tracking, and financial services (Gimhae, 2013;Morabito, 2016;Park et al., 2014;Thierer, 2015). Similarly, a variety of interest-based lifelogging systems have been developed for wearable devices, including InSense (Blum et al., 2006), Ayumu (Stoddard et al., 2016), BWDAT (Cordeiro et al., 2021), AyeContex (Bulling et al., 2013), Life-tags (Aiordachioae & Vatavu, 2019), Memento (Jiang et al., 2019), FMT (Stiglic & Viner, 2019), VIMES (Bermejo et al., 2020). ...
The modern smart TV can record viewers’ daily life-watching experiences called digital logs. These logs can be used for various purposes, including but not limited to recommendations, monitoring viewers, watching behavior, memory augmentation, e-learning, viewers’ privacy, and designing and developing adaptive User Interfaces (UI). Much work is available on lifelogging technologies related to smartphones, fitness gadgets, and wearable and non-wearable devices. However, little attention has been given to smart TV-based lifelogging systems. In this paper, we proposed a TV-based SmartLog framework for logging specific information about watching experiences. The proposed work is implemented and installed on Android-based Smart TV. We logged various activities of individual viewers and other household members and their environmental contexts. We empirically evaluated the proposed solution by analyzing data from 75 household viewers of different age groups. These groups include teenagers, homemakers, senior citizens, literate, and educated. We carried out various tests on the collected data, ie, descriptive tabulation, Kendall’s tau-b, Cronbach alpha, and Principal Component Factor Analysis (PCFA). The findings suggest that the SmartLog app received a positive perception regarding attitude, user satisfaction, ease of use, and intention to use. The proposed solution can be used to assist household viewers in terms of personalization, usability, accessibility, user experience, learnability, and reducing cognitive overload while interacting with smart TV.
... Носимые устройства можно классифицировать по нескольким параметрам, таким как функции, приложения, способность «чувствовать» и многое другое. Одна из подобных классификаций включает в себя такие параметры, как функциональность (монофункциональное или многофункциональное устройство), тип (пассивная или активная потребляемая мощность) и способ размещения (инвазивный или неинвазивный) [11]. К классификационным признакам относятся также простота настраивания функционала, отклик, пропускная способность, эстетичность и эргономика. ...
Wearable devices that measure individual physiological parameters have become common companions of everyday life. The development of wearable medical device technologies that collect human data, combined with the analytical capabilities of artificial intelligence and machine learning, can improve human health. This paper discusses wearable gadgets currently used to diagnose and treat chronic conditions. Artificial intelligence algorithms that analyze human health data collected from wearable devices are evaluated. Factors contributing to and impeding the use of wearable data for practical healthcare are summarized. Medical
and economic needs, technical progress due to market competition and scientific interest, and the need to monitor employees’ health stimulate the further introduction of wearable devices in diagnosing and treating diseases. Technical flaws and legal issues limit the use of data from wearable devices for practical healthcare.
... Sensor regangan memastikan estimasi gerakan ini secara efisien dan kemudian data yang diperoleh dapat digunakan untuk evaluasi laju respirasi (RR). Serat optik adalah salah satu bahan yang paling sering digunakan untuk keperluan ini karena kesederhanaan relatif dari pendekatan pengukuran dan pemrosesan serat optik dengan teknologi seperti tenun dan bordir [53,54]. ...
DEVELOPMENT OF SILICONE-BASED TEXTILE TECHNOLOGY INNOVATION - LITERATURE STUDY. The purpose of this review is to provide an overview of the key innovative pathways in developing silicone-based  textiles to date using resources available in the public domain regarding "smart textiles" which are translated into Indonesian as "Smart Textile" or "Textile Intelligent". The material of this paper is taken from various literatures which are textbooks (academic), commercial products and issued patents. Based on the literature obtained it is reported that silicone can be integrated into textiles, where integration can be achieved by inserting silicone into textile surfaces, and silicone are added at the textile or silicone manufacturing stage combined at the yarn stage. The integration method can affect the nature of the yarn network in fabrics / textiles, such as the flexibility of the fabric.
... The definition of "wearables" has shifted from technologies that are worn on the body to all kinds of technologies that are in contact with the body and facilitate personalized information processing [26,51]. In this study, we use the term to refer to both technologies that may be worn like a jacket or are simply attached to or wrap the body like a blanket or a brooch. ...
The design and development of playful wearable devices is a challenging and complicated problem. It entails not only multidisciplinary expertise but also a comprehensive understanding of player experience. There is a scarcity of evidence-based studies in current state-of-art literature that investigate general design practices and provide pragmatic design implications and suggestions based on solid user-centered research. To bridge the gap, we developed five experience prototypes based on the speculative design concepts from previous studies, and a Wizard of Oz experiment was conducted to elicit end users' feedback regarding general gaming experience as well as specific design themes in different gaming scenarios. The user experiment results were analyzed qualitatively following a rigorous thematic analysis, generating five major design implications as output. We believe this study will offer forward-looking insights to designers, developers and the research community, facilitating future work in this field.
... Smart wearables can collect data with very high sampling rates (e.g., some devices sample their sensors at 10 Hz, meaning that ten samples per second can be available) in a continuous fashion. So-called big data are quickly obtained by using these devices (Park et al. 2014), so AI methods are the primary choice to analyze such outputs and provide feedback to the users. Furthermore, AI methods can be based on machine learning or deep learning; the "learning" implies that the more data are collected, the better the accuracy becomes, making such techniques ideal for programs involving a constantly increasing number of available data. ...
Artificial intelligence (AI) systems have been widely applied to various contexts, including high-stake decision processes in healthcare, banking, and judicial systems. Some developed AI models fail to offer a fair output for specific minority groups, sparking comprehensive discussions about AI fairness. We argue that the development of AI systems is marked by a central paradox: the less participation one stakeholder has within the AI system’s life cycle, the more influence they have over the way the system will function. This means that the impact on the fairness of the system is in the hands of those who are less impacted by it. However, most of the existing works ignore how different aspects of AI fairness are dynamically and adaptively affected by different stages of AI system development. To this end, we present a use case to discuss fairness in the development of corporate wellness programs using smart wearables and AI algorithms to analyze data. The four key stakeholders throughout this type of AI system development process are presented. These stakeholders are called service designer, algorithm designer, system deployer, and end-user. We identify three core aspects of AI fairness, namely, contextual fairness, model fairness, and device fairness. We propose a relative contribution of the four stakeholders to the three aspects of fairness. Furthermore, we propose the boundaries and interactions between the four roles, from which we make our conclusion about the possible unfairness in such an AI developing process.
... Some of the known brands of WFT devices include smartwatches like Apple, Samsung, and Huawei watch, and digital wristbands such as Fitbit, GOQii, Xiaomi, Garmin, and Fastrack, among others (Zhu et al., 2017). WFT devices accounted for 26% of the wearable healthcare foster their willingness to attain fitness goals, facilitating preventive health care (Park et al., 2014). Furthermore, preventive healthcare can enable better health monitoring, thereby helping public policymakers achieve the United Nations Sustainability goal of improved health and wellbeing across all age groups (Papa et al., 2020). ...
Purpose
This paper aims to explore factors impacting wearable fitness tracking (WFT) device continued usage intention from perspectives of technology attributes (autonomy benefits), health attributes (self-health management benefits, diet-control benefits and health self-efficacy), and consumer attributes (age, gender, technological innovativeness, symbolic benefits, social benefits and hedonic benefits).
Design/methodology/approach
The study integrates constructs from the technology acceptance theories and the health promotion model to develop the research model and hypothesis. The empirical analysis was conducted using data from 217 respondents from India. Logistic regression was used to identify factors that discriminate between groups with low and high continued usage intentions.
Findings
Results indicate higher continued usage intention for WFT devices is driven by perceived benefits-health, autonomy, social and hedonic, and individual characteristics-technological innovativeness and perceived health self-efficacy. Further, perceived symbolic benefits, diet control benefits, age, and gender does not discriminate between the groups with low and high continued usage intentions.
Research limitations/implications
The results may be limited to the context of the sample and the factors considered. The study suggests future research areas.
Practical implications
The paper offers insights for marketers, governments, insurance firms, and related healthcare services on promoting higher usage of WFT devices to yield dual benefits of preventive healthcare and higher profitability.
Originality/value
The study extends existing research by examining factors across consumer, health, and technological domains in a single framework and adds to the limited research in the context of usage of WFT devices in developing countries.
... In the above sections, we have shown that LIG wearable sensors can be used to reliably collect physiological data that can be processed with an easily accessible HeartPy open source toolkit. Wearables can be used to perform several basic functions: sense, analyze, store, transmit, and utilize data [36]. Processing of the recorded physiological signals can be done either on the sensor (wearer) or at a remote location where higher processing power is available (e.g., healthcare provider). ...
The HeartPy Python toolkit for analysis of noisy signals from heart rate measurements is an excellent tool to use in conjunction with novel wearable sensors. Nevertheless, most of the work to date has focused on applying the toolkit to data measured with commercially available sensors. We demonstrate the application of the HeartPy functions to data obtained with a novel graphene-based heartbeat sensor. We produce the sensor by laser-inducing graphene on a flexible polyimide substrate. Both graphene on the polyimide substrate and graphene transferred onto a PDMS substrate show piezoresistive behavior that can be utilized to measure human heartbeat by registering median cubital vein motion during blood pumping. We process electrical resistance data from the graphene sensor using HeartPy and demonstrate extraction of several heartbeat parameters, in agreement with measurements taken with independent reference sensors. We compare the quality of the heartbeat signal from graphene on different substrates, demonstrating that in all cases the device yields results consistent with reference sensors. Our work is a first demonstration of successful application of HeartPy to analysis of data from a sensor in development.
... There are various definitions for the term WT or wearable devices, and it is an application area in which different disciplines are used together. Park et al. focused on the term wearable and stated that these devices are different from conventional clothing and provide personalized mobile information processing [2]. Coyle and Diamond stated that WTs should be soft, flexible, washable, and meet people's normal wearing expectations [3]. ...
Global difficulties, such as rising healthcare costs and staff shortages, have accelerated the transition to new wearable technologies in place of traditional healthcare services. With wearables, patients can be tracked regularly. In the study, wearable biomedical technologies were investigated according to their wearable structures as rigid, soft, and textile based. With the developing technology, it will be possible to get more comfortable, accurate, and better measurements by getting sensors from the textile surface. Resistive sensor, galvanic skin response, capacitive sensor, piezoelectric sensor, optical sensors, semiconductor sensors, and inertial measurement unit are the most used basic sensor types in health studies. In the study, information was given about the sensor types used in health applications. Biomedical applications are described only by classifying the upper-extremity region according to the sub-parts. When looking that are used on arm and hand are explained in the study. It is emphasized by researchers working in the textile field that to be presented as a final product, the wearable must meet natural clothing requirements. The trend toward commercialization is especially in adhesive wearables, integration of new sensor technologies, and miniaturization of wearables. Comfort and flexibility can be achieved using more textile techniques in future, which will greatly increase the usability and accuracy of the devices.
Nanomaterials have revolutionized sensor technology by offering enhanced sensitivity, selectivity, and miniaturization capabilities. However, the commercialization of nanomaterial‐based sensors remains challenging due to the complexities involved in bridging laboratory innovations to market‐ready products. This review article explores the various marketing strategies that can facilitate the successful commercialization of nanomaterials for sensor applications. It emphasizes the importance of understanding market needs, regulatory landscapes, and the value proposition of nanomaterials over traditional materials. The study also highlights the role of strategic partnerships, intellectual property management, and customer education in overcoming market entry barriers. Through a comprehensive analysis of case studies and industry practices, this review provides a framework for companies and researchers to effectively transition from lab‐scale innovations to commercially viable sensor products. The findings suggest that a well‐rounded marketing strategy, combined with robust product development and stakeholder engagement, is crucial for capitalizing on the unique benefits of nanomaterials in sensor applications.
Fine-grained human motion detection has become increasingly important with the growing popularity of human computer interaction (HCI). However, traditional gesture-based HCI systems often require the design of new operation modes rather than conforming to user habits, thus increasing system learning costs. In this paper, we present TapWristband, a novel wearable sensor-based vibration sensing system that detects finger tapping by measuring wrist vibrations. We first perform real-world experiments to collect measurements for modeling the effects of the tapping motion on wearable wristband sensors including piezoelectric transducer (PZT) and inertial measurement unit (IMU). We find that a damped vibration model can be used to represent the relaxing phase of a vibration response due to tapping motion. Thus, we propose a mutual cross-correlation-based event segmentation algorithm to extract the vibration signal during the relaxing phase. After that, we develop feature extraction and classification algorithms to recognize the tapping patterns of five fingers across twelve key locations of a keypad system. Finally, we performed extensive experiments with thirteen participants to evaluate our system. Experimental results show that our low-cost vibration sensing system can achieve an average accuracy of over
with a tapping speed of over 100 taps per minute in real-world tapping scenarios.
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.
Advances in brain-machine interfaces and wearable biomedical sensors for healthcare and human-computer interactions call for precision electrophysiology to resolve a variety of biopotential signals across the body that cover a wide range of frequencies, from the mHz-range electrogastrogram (EGG) to the kHz-range electroneurogram (ENG). Existing integrated wearable solutions for minimally invasive biopotential recordings are limited in detection range and accuracy due to trade-offs in bandwidth, noise, input impedance, and power consumption. This article presents a 16-channel wide-band ultra-low-noise neural recording system-on-chip (SoC) fabricated in 65nm CMOS for chronic use in mobile healthcare settings that spans a bandwidth of 0.001 Hz to 1 kHz through a featured sample-level duty-cycling (SLDC) mode. Each recording channel is implemented by a delta-sigma analog-to-digital converter (ADC) achieving 1.0
μ
V
rms
input-referred noise over 1Hz–1kHz bandwidth with a Noise Efficiency Factor (NEF) of 2.93 in continuous operation mode. In SLDC mode, the power supply is duty-cycled while maintaining consistently low input-referred noise levels at ultra-low frequencies (1.1
μ
V
rms
over 0.001Hz–1Hz) and 435 MΩ input impedance. The functionalities of the proposed SoC are validated with two human electrophysiology applications: recording low-amplitude electroencephalogram (EEG) through electrodes fixated on the forehead to monitor brain waves, and ultra-slow-wave electrogastrogram (EGG) through electrodes fixated on the abdomen to monitor digestion.
Emerging technologies and the benefits they bring with them are increasingly entering every pore of society. A new trend combining virtual reality (VR) with the real-world scenarios, which is reflected in mixed reality (MR) devices, primarily in the HoloLens headset, which allows users to explore the mixed reality world and control their movements (even without using their hands), are increasingly finding their way to education sector. The subject of this paper is the analysis of the impact and advantages of mixed reality (MR) devices in education, with a special focus on building communication and student cooperation in the learning process. This paper aims to inform education experts about the advantages of integrating these new technologies into the classroom to boost student motivation, enhance students' comprehension of the material being taught, and assist underachievers in overcoming obstacles to learning. The advent of immersive technologies has made it possible for students to learn remotely, which has shown to be very useful during the pandemic. Complex trainings, experiments, and group projects may now be conducted in virtual environment apart from reality, which can help students become more skilled and enthusiastic without worrying that the results will be less effective than they would be in a traditional setting.
Technology is changing our lives fundamentally by redefining our way of interacting with each other, performing transactions, commuting from one place to another, etc. Smart wearable technology is one of the areas in which explosive growth is witnessed in recent years. Smart wearable devices (SWD) are eventually going to become an integral part of human life, and the design discipline has clearly understood the potential of these devices. Traditionally, design discipline has always been responsive to the technology and material advances by coming up with their practical and innovative usages. In this, design education has played a crucial role by fostering designers to cope with the pace of technology change. However, contemporary design education lacks the explicit emphasis on the design of these new-age products. Since emerging technologies like SWD offer new prospects for designers to cultivate, enhance, and implement their thoughts and imaginations, a critical understanding of these present-day devices is highly required today for young upcoming designers. For that to happen, the need has arisen to relook at the current design curriculum. This paper tries to rationalize the significance of smart wearable device design for the current design curriculum and propose a systematic ideation method using the emotional design approach. Furthermore, an exploratory study was conducted with undergraduate design students to develop a structured approach to enhance the creativity of idea generation for SWD. Insights from this study would help design academicians to formulate guidelines for SWD design in the design curriculum.
The use of wearable devices has increased substantially in recent years. This, together with the rise of telemedicine, has led to the use of these types of devices in the healthcare field. In this work, we carried out a detailed study on the use of these devices (regarding the general trends); we analyzed the research works and devices marketed in the last 10 years. This analysis extracted relevant information on the general trend of use, as well as more specific aspects, such as the use of sensors, communication technologies, and diseases. A comparison was made between the commercial and research aspects linked to wearables in the healthcare field, and upcoming trends were analyzed.
Recent years have witnessed an increase in human life expectancy fueled by significant improvements in infrastructure, healthcare, and economies across the globe. Longer life spans have altered the world demographics resulting in a larger senior population compared with previous years. This trend has created the need for providing additional care and assistive services to support the ageing individuals. Innovative assistance techniques are especially necessary for elderly people who live on their own in their homes. Simultaneously, an explosive growth in IoT gadgets such as sensors and actuators have accelerated the development of smart homes which comprise various types of IoT systems that provide increased convenience to people with degenerating physical and cognitive abilities. Common examples of IoT systems that are being integrated into smart homes include home automation systems, home activity detectors, wearable sensor technologies for remote health management and so on. We identify the common needs of ageing and impaired individuals and then we review several IoT applications that can provide the required support. We further discuss some of the challenges that must be addressed to make these IoT systems more practical and reliable for everyday use.
Giyilebilir teknolojik ürünler her geçen gün giderek daha popüler hale gelmektedir. Özellikle yapay zeka teknolojilerinin de gelişimi ile makine öğrenmesinin önemi artmış ve bu süreç için ihtiyaç duyulan büyük verinin temininde giyilebilir teknolojiler kilit bir rol üstlenmektedir. Sürekli artan pazar hacmi göz önüne alındığında giyilebilir teknolojik ürünleri kullanan tüketicilerin davranışlarının incelenmesi teknoloji firmaları ve pazarlama yöneticileri açısından önem arz ettiği gibi genel olarak pazarlama faaliyetleri açısından da bu ürünleri kullanan tüketicilerin davranışlarının anlaşılması önem taşımaktadır. Diğer taraftan giyilebilir teknolojik ürünleri kullanan tüketicilerin bu ürünleri kullanmaya devam etme veya satın alma niyetlerini etkileyen unsurlar üzerinde yenilikçiliğin etkin rolünün de incelenmesi gereken konulardan biri olduğu değerlendirilmektedir. Bu kapsamda ele alınan bu çalışmada tüketicilerin giyilebilir teknolojik ürün satın alma niyetleri üzerinde etkisi olduğu düşünülen hedonik, faydacı ve algılanan ürün değerinin doğrudan satın alma niyeti üzerindeki etkisi ile tüketici yenilikçiliğinin bu etkileşimdeki düzenleyici rolü araştırılmıştır. 314 örneklemden elde edilen veri kullanılarak araştırmanın varsayımları doğrulayıcı faktör analizine tabi tutularak yapısal eşitlik modellemesi ile analiz edilmiştir. Ayrıca tüketici yenilikçinin düzenleyici rolü ise SPSS Process Macro programı ile incelenmiştir. Elde edilen bulgular tüketicilerin giyilebilir teknolojik ürün satın alma niyetleri üzerinde hedonik, faydacı ve algılanan ürün değerinin doğrudan etkisi olduğunu ortaya koymuştur. Diğer taraftan bu etki üzerinde tüketici yenilikçiliğinin düzenleyici rolüne bakıldığında ise hedonik ve faydacı değer ile satın alma niyeti arasındaki ilişkinin tüketici yenilikçiliği tarafından düzenlendiği değerlendirilebilir. Elde edilen bu sonuç tüketici yenilikçiliğinin yüksek olması durumunda hedonik ve faydacı değerin satın alma niyetine etkisinin daha fazla olduğunu ortaya koymuştur.
Recent developments in miniaturized electronic devices with sophisticated computational capabilities and remarkably low power communication technologies involve a tendency toward powering these devices with long cycle life, high energy efficiency, fast and cheap production and lightweight power sources. Integration of piezoelectric materials and novel fabrication techniques with conventional textile processes established the emergence of a wearable technology field which can fulfill this purpose. Mechanical energy harvesters are required for multiple applications such as structural health monitoring systems, self-powered wireless sensors, and harvesting energy from body movements inexpensively. Among the variety of materials exhibiting piezoelectricity, polymers are more considered due to their many excellent properties desirable in flexible piezoelectric generators. Hence, fiber-based electronic devices have the best features for human garments such as flexibility, stretchability, permeability and lightweight, and they are ideal interface platform options between the environment, electronic devices and human body. Hence, this chapter starts with the fundamentals of wearable technology and materials involved and then reviews recent developments in fiber-based self-powered systems and sensors with the special focus on the piezoelectric poly(vinylidene fluoride) polymer and barium titanium oxide ceramic. In addition, a number of strategies that may improve the piezoelectric generator performance are summarized. Furthermore, the global textile market industry and the high-performance end-user such as washability and durability were reviewed. Potential difficulties, challenges and opportunities in the field of fiber-based energy generators are also explored.
Wearable devices have grown exponentially in popularity in both consumer and industrial applications in recent years. Despite their stringent area and energy constraints, these devices are processing increasingly complex and data-rich workloads, necessitating innovative area- and energy-efficient computing solutions and architectures. This paper explores spin-transfer torque RAM (STT-RAM) as a candidate for designing area- and energy-efficient wearable processor caches. First, we analyze the memory footprints of 16 real-world wearable workloads and compare them to general-purpose benchmarks like SPEC 2017 and MiBench. Then, we analyze the wearable workloads’ memory characteristics to reveal that wearable workloads are highly read-intensive, making them less vulnerable than general-purpose workloads to the write latency/energy overheads inherent in STT-RAM caches. Our analysis also reveals that wearable workloads have low cache variability needs, and their cache blocks exhibit short and stable lifetimes. Against the background of this analysis, we explore the tradeoffs of STT-RAM cache architecture designs for the wearable workloads. Specifically, we explore a simple adaptable design that aims to optimize latency or energy, based on runtime needs, without introducing significant design or area overhead. Our analysis shows that STT-RAM caches offer much promise for energy- and area-efficient wearable computing, without introducing much performance overheads.
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