Relevant bibliographies by topics / Smart and Wearable Devices

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Smart and Wearable Devices'

Author: Grafiati
Published: 9 March 2023

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Journal articles on the topic "Smart and Wearable Devices"

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Shakhakarmi, Niraj. "Next Generation Wearable Devices." International Journal of Interdisciplinary Telecommunications and Networking 6, no. 2 (2014): 25–51. http://dx.doi.org/10.4018/ijitn.2014040102.

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The next generation wearable devices are Smart health monitoring device and Smart sousveillance hat which are capable of using wearable sensors for measuring physiological information, sousveillanace, navigation, as well as smart device to smart device communications over cellular coverage. Smart health monitoring device collect and observe different health related information deploying biosensors and can predict health problems. Smart sousveillance hat provides the brainwaves based fatigue state, training and sousveillance around the wearer. The next generation wearable smart devices deploy the device to device communications in LTE assisted networks with D2D server, D2D Application server and D2D enhanced LTE signalling for D2D service management, spectrum utilization and broad cellular coverage, which make them portable, social, commercial and sustainable. Thus, the wearable device technology will merge with the smart communications besides the health and wellness. Furthermore, the simulation and performance evaluation shows that LTE-D2D wearable smart device communications provides two times more energy efficiency than LTE-UEs cellular communications. The LTE-D2D data rate is also found significantly higher with higher D2D-SINR for lower relative mobility (= 30m/s) and lower D2D distance (<400m) between devices.
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Chakrabarti, Shweta, Nupur Biswas, Lawrence D. Jones, Santosh Kesari, and Shashaanka Ashili. "Smart Consumer Wearables as Digital Diagnostic Tools: A Review." Diagnostics 12, no. 9 (2022): 2110. http://dx.doi.org/10.3390/diagnostics12092110.

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The increasing usage of smart wearable devices has made an impact not only on the lifestyle of the users, but also on biological research and personalized healthcare services. These devices, which carry different types of sensors, have emerged as personalized digital diagnostic tools. Data from such devices have enabled the prediction and detection of various physiological as well as psychological conditions and diseases. In this review, we have focused on the diagnostic applications of wrist-worn wearables to detect multiple diseases such as cardiovascular diseases, neurological disorders, fatty liver diseases, and metabolic disorders, including diabetes, sleep quality, and psychological illnesses. The fruitful usage of wearables requires fast and insightful data analysis, which is feasible through machine learning. In this review, we have also discussed various machine-learning applications and outcomes for wearable data analyses. Finally, we have discussed the current challenges with wearable usage and data, and the future perspectives of wearable devices as diagnostic tools for research and personalized healthcare domains.
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Nataliia, MARCHUK, OSIIEVSKA Valentyna, and MIKHAILOVA Halyna. "CLASSIFICATION OF WEARABLE ELECTRONIC DEVICES." INTERNATIONAL SCIENTIFIC-PRACTICAL JOURNAL "COMMODITIES AND MARKETS" 40, no. 4 (2021): 68–78. http://dx.doi.org/10.31617/tr.knute.2021(40)07.

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Background. Today smart watches, fitness bracelets, smart rings are must-have accessory for everyone who cares about their health. It is projected that the average annual growth of the wearable device market in 2021–2026 will be 18 %, which is respectively reflected in this segment of the Ukrainian market. Well-known electronics stores use different approaches to group the range of wearable devices, as there are no single standards to classify these products. The aim of this article is to develop a classification of wearable devices and to identify the classification featuresfor smart watches and fitness bracelets based on the analysis of the assortment presented in online stores. Materials and methods. Methods of logical analysis, generalization of scientific literature, statistical data of export and import of wearable devices were applied. Data on their assortment and grouping in well-known retail chains were used to create a classification. Results. Based on the analysis of the world market of electronic goods and the assortment of well-known retail chains, the authors propose a classification of goods related to wearable devices. In particular, there is a division of wearable devices into 7 groups (wrist devices, head devices, smart clothes, smart shoes, smart jewelry, wearable devices, medical devices), these groups include subgroups, categories and subcategories. Only a few types of wearable devices are sold on the Ukrainian market – smart watches, fitness bracelets, virtual reality glasses and smart rings. However, only two retail chains allocate these products separately in the product group "Wearable Products", the others form a large product group "Gadgets…", which according to the authors is not entirely correct, as the latter differ significantly in purpose and characteristics. Since the range of smart watches and fitness bracelets is quite wide and includes hundreds of types, it is proposed to use a number of classification features that clearly distinguish them by their functionality. Conclusion. With the COVID-19 pandemic, the wearable devices market seg­ment will continue to grow. Restrictions on mobility and an individual’s desire to monitor vital signs of their health during a pandemic will be the main factors that will influence the market for these devices. The classification of goods related to wearable devices has been developed. The classification features for smart watches and fitness bracelets, the range of which includes hundreds of types, are proposed. It is established that the main difference between smart watches and a fitness bracelets is a wider functionality of the first and a much longer battery life of the latter.
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Idoga, E. P., and A. I. Adamu. "Understanding Smart Wearable Sensors Technology: Impact on Human Health and Fitness." Journal of Applied Sciences and Environmental Management 24, no. 7 (2020): 1261–65. http://dx.doi.org/10.4314/jasem.v24i7.19.

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In the field of health care management, smart wearable devices and its supporting technologies have tremendously made a name all around the globe. Smart watches and other sensor trackers are practically being used by various people and its usage has shown to be accompanied with lots of benefits. This technology was envisaged to play a vital role in the healthcare needs of people; especially with applications in the healthcare sector. The objective of this study, therefore, is to evaluate the technological impact of wearable sensors in human health and fitness (HHF). A web based survey was used for data collection for the period of one month. Emails were sent to registered members of a particular gym who uses any of the smart wearable sensors in keeping fit. The study findings indicate that among the smart wearable devices examined, smart wristwatches (45.6%) appears to be the most commonly used wearable sensor device followed by smart wrist bands (34.7%), smart textiles (10.7%) and smart rings (9.1%). This signifies that a large number of people can effortlessly use SWSs and devices and are optimistic about its support in their daily healthcare/fitness needs. Users are positive on the technological prospects of SWSs and devices; although there is a gap between personal motivation to use wearable devices and trust in the confidentiality and privacy of data generated.
 Keywords: Devices, Health, Fitness, Wearable, Sensors
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Nimi W. S., P. Subha Hency Jose, and Jegan R. "Review on Reliable and Quality Wearable Healthcare Device (WHD)." International Journal of Reliable and Quality E-Healthcare 10, no. 4 (2021): 1–25. http://dx.doi.org/10.4018/ijrqeh.2021100101.

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This paper presents a brief review on present developments in wearable devices and their importance in healthcare networks. The state-of-the-art system architecture on wearable healthcare devices and their design techniques are reviewed and becomes an essential step towards developing a smart device for various biomedical applications which includes diseases classifications and detection, analyzing nature of the bio signals, vital parameters measurement, and e-health monitoring through noninvasive method. From the review on latest published research papers on medical wearable device and bio signal analysis, it can be concluded that it is more important and very essential to design and develop a smart wearable device in healthcare environment for quality signal acquisition and e-health monitoring which leads to effective measures of multiparameter extractions. This will help the medical practitioners to understand the nature of patient health condition easily by visualizing a quality signal by smart wearable devices.
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Amft, Oliver. "Smart Eyeglasses, e-Textiles, and the Future of Wearable Computing." Advances in Science and Technology 100 (October 2016): 141–50. http://dx.doi.org/10.4028/www.scientific.net/ast.100.141.

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Where a decade a ago mostly visions and bulky carry-on devices existed, today several wearable computing products could be found. For example, activity trackers are already selling in convenience stores. The development does neither mean that the core innovations of the wearable computing vision are realised, nor that there will be any successful wearable device beyond those activity trackers. The product announcements and explorations, such as Google Glass, have identified key challenges that are urging further research investments. The lessons to learn from those recent developments are discussed here, leading to an approach towards multi-function materials and wearable devices. Two projects are described that implement a multi-function approach. In the SimpleSkin project, a generic fabric is developed to realise different sensor functions, controlled via software apps in a Garment OS. The same fabric material is used in smart eyeglasses to realise temple-integrated electrodes. Whereas SimpleSkin aims at skin-attached wearables, the smart eyeglasses developed here closely resemble regular glasses and thus could become publicly accepted wearable accessories. Moving towards wearable technology that is truly embedded into everyday life opens a series of new health support applications that are sketched here, based on the concept of smart eyeglasses.
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Zhang, Yang, Wenyan Sun, and Jia Chen. "Application of Embedded Smart Wearable Device Monitoring in Joint Cartilage Injury and Rehabilitation Training." Journal of Healthcare Engineering 2022 (January 7, 2022): 1–11. http://dx.doi.org/10.1155/2022/4420870.

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Joint injuries cause varying degrees of damage to joint cartilage. The purpose of this paper is to study the application of embedded smart wearable device monitoring in articular cartilage injury and rehabilitation training. This paper studies what an embedded system is and what a smart wearable device is and also introduces the rehabilitation training method of articular cartilage injury. We cited an embedded matching cost algorithm and an improved AD-Census. The joint cartilage damage and rehabilitation training are monitored. Finally, we introduced the types of smart wearable devices and different types of application fields. The results of this paper show that, after an articular cartilage injury, the joint function significantly recovers using the staged exercise rehabilitation training based on embedded smart wearable device monitoring. We concluded that, from 2013 to 2020, smart wearable devices are very promising in the medical field. In 2020, the value will reach 20 million US dollars.
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Xia, Junfei, Shirin Khaliliazar, Mahiar Max Hamedi, and Sameer Sonkusale. "Thread-based wearable devices." MRS Bulletin 46, no. 6 (2021): 502–11. http://dx.doi.org/10.1557/s43577-021-00116-1.

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Abstract One-dimensional substrates such as textile fibers and threads offer an excellent opportunity to realize sensors, actuators, energy harvesters/storage, microfluidics, and advanced therapies. A new generation of wearable devices made from smart threads offer ultimate flexibility and seamless integration with the human body and the garments that adorn them. This article reviews the state of the art in thread-based wearable devices for monitoring human activity and performance, diagnoses and manages medical conditions, and provides new and improved human–machine interfaces. In the area of new and improved human–machine interfaces, it discusses novel computing platforms enabled using thread-based electronics and batteries/capacitors. For physical activity monitoring, a review of wearable devices using strain sensing threads is provided. Thread-based devices that can monitor health from biological fluids such as total analysis systems, wearable sweat sensing patches, and smart sutures/smart bandages are also included. The article concludes with an outlook on how fibers and threads are expected to impact and revolutionize the next generation of wearable devices. Knowledge gaps and emerging opportunities are presented. Graphic Abstract
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Yin, Yunlei, Cheng Guo, Hong Li, Hongying Yang, Fan Xiong, and Dongyi Chen. "The Progress of Research into Flexible Sensors in the Field of Smart Wearables." Sensors 22, no. 14 (2022): 5089. http://dx.doi.org/10.3390/s22145089.

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In modern society, technology associated with smart sensors made from flexible materials is rapidly evolving. As a core component in the field of wearable smart devices (or ‘smart wearables’), flexible sensors have the advantages of excellent flexibility, ductility, free folding properties, and more. When choosing materials for the development of sensors, reduced weight, elasticity, and wearer’s convenience are considered as advantages, and are suitable for electronic skin, monitoring of health-related issues, biomedicine, human–computer interactions, and other fields of biotechnology. The idea behind wearable sensory devices is to enable their easy integration into everyday life. This review discusses the concepts of sensory mechanism, detected object, and contact form of flexible sensors, and expounds the preparation materials and their applicability. This is with the purpose of providing a reference for the further development of flexible sensors suitable for wearable devices.
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Tabassum, Madeeha, Qasim Zia, Yongfeng Zhou, Yufei Wang, Michael J. Reece, and Lei Su. "A Review of Recent Developments in Smart Textiles Based on Perovskite Materials." Textiles 2, no. 3 (2022): 447–63. http://dx.doi.org/10.3390/textiles2030025.

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Metal halide perovskites (MHPs) are thought to be among the most promising materials for smart electronic textiles because of their unique optical and electrical characteristics. Recently, wearable perovskite devices have been developed that combine the excellent properties of perovskite with those of textiles, such as flexibility, light weight, and facile processability. In this review, advancements in wearable perovskite devices (e.g., solar cells, photodetectors, and light-emitting diodes) concerning their device architectures, working mechanisms, and fabrication techniques have been discussed. This study also highlights the technical benefits of integrating MHPs into wearable devices. Moreover, the application challenges faced by wearable perovskite optoelectronic devices—from single devices to roll-to-roll manufacturing, stability and storage, and biosafety—are briefly discussed. Finally, future perspectives on using perovskites for other wearable optoelectronic devices are stated.
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Dissertations / Theses on the topic "Smart and Wearable Devices"

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Beck-Norén, Gustav. "Cross-platform Development for Wearable Devices." Thesis, Linköpings universitet, Programvara och system, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-119453.

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The market for wearable devices is continuously growing and has seen an in- crease in interest and demand this past year, specifically smartwatch devices. With several big players entering and trying to take place in the market the number of devices and platforms grow. This leads to device and software fragmentation like the one seen in the world of smartphones. In this paper I discuss and compare the two smartwatch platforms Android Wear and Apple Watch in terms of possibilities, limitations and differences. Research is done to find cross-platform development possibilities for these platforms. Extensive theoretical background of both APIs is researched and presented. An app for both smartwatch platforms is developed with integration of the WebSocket protocol to function as a remote control for a Video-On-Demand web service. This is done to showcase the cross-platform possibilities and differences of the platforms. As a result the biggest differences are out- lined and a conclusion is made that cross-platform development for these platforms can be challenging but is possible on certain levels.
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Gatouillat, Arthur. "Towards smart services with reusable and adaptable connected objects : An application to wearable non-invasive biomedical sensors." Thesis, Lyon, 2018. http://www.theses.fr/2018LYSEI123/document.

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La prolifération des objets communicants fixes et mobiles soulève la question de leur intégration dans les environnements quotidiens, par exemple dans le cadre de la e-santé ou de la domotique. Les principaux défis soulevés relèvent de l’interconnexion et de la gestion de la masse de donnée produite par ces objets intelligents. Notre premier objectif est d’adopter une démarche des couches basses vers les couches hautes pour faciliter l’intégration de ces objets à des services intelligents. Afin de développer celle-ci, il est nécessaire de d’étudier le processus de conception des objets intelligents indépendamment de considérations matérielles et logicielles, au travers de la considération de leur propriétés cyber-physiques. Pour mener à bien la réalisation de services intelligents à partir d’objets connectés, les deux axes de recherche suivant seront développés : la définition d’une méthode de conception orientée service pour les objets connectés intégrant une dimension formelle ainsi de valider le comportement de ceux-ci, l’auto-adaptation intelligente dans un contexte évolutif permettant aux objets de raisonner sur eux même au travers d’un langage déclaratif pour spécifier les stratégies d’adaptation. La validation de ces contributions s’effectuera par le biais du développement et de l’expérimentation à grandeur nature d’un service de diagnostic médical continu basé sur la collecte de données médicales en masse par des réseaux non-intrusifs de capteurs biomédicaux portables sur le corps humain<br>The rapid growth of fixed and mobile smart objects raises the issue of their integration in everyday environment, e.g. in e-health or home-automation contexts. The main challenges of these objects are the interoperability, the handling of the massive amount of data that they generate, and their limited resources. Our goal is to take a bottom-up approach in order to improve the integration of smart devices to smart services. To ensure the efficient development of our approach, we start with the study of the design process of such devices regardless of specific hardware or software through the consideration of their cyber-physical properties. We thus develop two research directions: the specification of a service-oriented design method for smart devices with formal considerations in order to validate their behavior, and the proposal of a self-adaptation framework in order to handle changing operating context through self-reasoning and the definition of a declarative self-adaptation objectives specification language. The testing of these contributions will be realized through the development of a large-scale experimental framework based on a remote diagnostics case-study relying on non-invasive wearable biomedical sensors
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D'Elia, Roberto. "Architetture per smart health: il caso FitStadium." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amslaurea.unibo.it/9616/.

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L'obiettivo della tesi è progettare un'architettura abilitante per scenari smart health, concentrandosi sulla parte end-user (non sulla parte server-cloud), ossia sperimentando l'ambito dei wearable devices e facendo riferimento al binomio fitness-Apple Watch, comodo perchè presente nell'azienda FitStadium che ci fornisce motivazioni, requisiti e goals. Nel primo capitolo si analizzeranno le soluzioni offerte attualmente dal mercato per la realizzazione di servizi legati al fitness, focalizzandosi in particolare sulle architetture proposte e come quest'ultime possano convivere con l'ecosistema FitStadium. Il secondo capitolo è riservato invece all'approfondimento delle tecnologie Apple, che verranno utilizzate concretamente per la realizzazione del caso di studio. Ancora una volta si farà attenzione alle possibilità architetturali offerte da queste tecnologie. Nel terzo capitolo viene trattato nella sua interezza il caso di studio, analizzandone in particolare lo stato pre e post tesi. Verrà cioè descritta l'applicazione implementata insieme alla presentazione di un'architettura abilitante anche per gli scenari smart health. Infine, all'interno del capito 4 viene descritto più precisamente il concetto di smart health e il percorso che ha condotto alla sua definizione.
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Hlavačka, Martin. "Zpracování dat ze senzorů wearable zařízení pomocí strojového učení." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2019. http://www.nusl.cz/ntk/nusl-403139.

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The goal of this master's thesis is to analyze the situation of wearable devices with the Android Wear operating system and recognition capabilities of various movement activities using neural networks. The primary focus is therefore on identifying and describing the most appropriate tool for recognizing dynamic movements using machine learning methods based on data obtained from this type of devices. The practical part of the thesis then comments on the implementation of a stand-alone Android Wear application capable of recording and formatting data from sensors, training the neural network in a designed external desktop tool, and then reusing trained neural network for motion recognition directly on the device.
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Eguchi, Kana. "Easy-to-Use Biosignal Monitoring: Wearable Device for Muscle Activity Measurement during Sleep in Daily Life." Doctoral thesis, Kyoto University, 2020. http://hdl.handle.net/2433/253414.

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京都大学<br>0048<br>新制・課程博士<br>博士(情報学)<br>甲第22578号<br>情博第715号<br>新制||情||123(附属図書館)<br>京都大学大学院情報学研究科社会情報学専攻<br>(主査)教授 黒田 知宏, 教授 守屋 和幸, 教授 吉川 正俊<br>学位規則第4条第1項該当<br>Doctor of Informatics<br>Kyoto University<br>DFAM
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Macias, Macias Raul. "Towards Wearable Spectroscopy Bioimpedance Applications Power Management for a Battery Driven Impedance Meter." Thesis, Högskolan i Borås, Institutionen Ingenjörshögskolan, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-19428.

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In recent years, due to the combination of technological advances in the fields ofmeasurement instrumentation, communications, home-health care and textile-technology thedevelopment of medical devices has shifted towards applications of personal healthcare.There are well known the available solutions for heart rate monitoring successfully providedby Polar and Numetrex. Furthermore new monitoring applications are also investigated. Amongthese non-invasive monitoring applications, it is possible to find several ones enable bymeasurements of Electrical Bioimpedance.Analog Devices has developed the AD5933 Impedance Network Analyzer which facilitatesto a large extent the design and implementation of Electrical Bioimpedance Spectrometers in amuch reduced space. Such small size allows the development of a fully wearable bioimpedancemeasurement.With the development of a Electrical Bioimpedance-enable wearable medical device in focusfor personal healthcare monitoring, in this project, the issue of power management has beentargeted and a battery-driven Electrical Bioimpedance Spectrometer based in the AD5933 hasbeen implemented. The resulting system has the possibility to operate with a Li-Po battery with apower autonomy over 17 hours.
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Riedel, Ralph, Franziska Schmalfuss, Michael Bojko, and Sebastian Mach. "Flexible Automatisierung in Abhängigkeit von Mitarbeiterkompetenzen und –beanspruchung." Universitätsbibliothek Chemnitz, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-231812.

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Industrie 4.0 und aktuelle Entwicklungen in dem Bereich der produzierenden Unternehmen erfordern hohe Anpassungsleistungen von Menschen und von Maschinen gleichermaßen. In Smart Factories werden Produktionsmitarbeiter zu Wissensarbeitern. Dazu bedarf es neben neuen, intelligenten, technischen Lösungen auch neuer Ansätze für Arbeitsorganisation, Trainings- und Qualifizierungskonzepte, die mit adaptierbaren technischen Systemen flexibel zusammenarbeiten. Das durch die EU geförderte Projekt Factory2Fit entwickelt Lösungen für die Mensch-Technik-Interaktion in automatisierten Produktionssystemen, welche eine hohe Anpassungsfähigkeit an die Fähigkeiten, Kompetenzen und Präferenzen der individuellen Mitarbeiter bieten und damit gleichzeitig den Herausforderungen einer höchst kundenindividuellen Produktion gewachsen sind. Im vorliegenden Beitrag werden die grundlegenden Ziele und Ideen des Projektes vorgestellt sowie die Ansätze des Quantified-self im Arbeitskontext, die adaptive Automatisierung inklusive der verschiedenen Level der Automation sowie die spezifische Anwendung des partizipatorischen Designs näher beleuchtet. In den nächsten Arbeitsschritten innerhalb des Projektes gilt es nun, diese Konzepte um- und einzusetzen sowie zu validieren. Die interdisziplinäre Arbeitsweise sowie der enge Kontakt zwischen Wissenschafts-, Entwicklungs- und Anwendungspartnern sollten dazu beitragen, den Herausforderungen bei der Realisierung erfolgreich zu begegnen und zukunftsträchtige Smart Factory-Lösungen zu implementieren. Das Projekt Factory2Fit wird im Rahmen von Horizon 2020, dem EU Rahmenprogramm für Forschung und Innovation (H2020/2014-2020), mit dem Förderkennzeichen 723277 gefördert.
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Scavongelli, Cristiano. "Sviluppo di strumenti di progettazione e simulazione ad alto livello di sistemi elettronici: applicazione a reti wireless." Doctoral thesis, Università Politecnica delle Marche, 2015. http://hdl.handle.net/11566/242936.

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Negli ultimi anni, le reti wireless sono diventate una realtà onnipresente, affidabile e ben accetta. Questo è particolarmente vero per reti come il Bluetooth e il Wi-Fi, che oggi si incontrano praticamente ovunque e vengono usate per le applicazioni più disparate. In molti casi, quando si usa un chip commerciale, il progetti-sta può limitarsi a lavorare sui livelli più alti della pila dei protocolli e limitarsi ad implementare il livello ap-plicazione. In altri casi, il progettista deve scendere giù lungo la pila e lavorare ad un livello più basso, sul quale può vedere e controllare alcuni parametri di rete cui non può avere accesso dal livello applicazione. Capita, ad esempio, quando una delle specifiche del sistema da progettare è il real-time, oppure il data rate richiesto è elevato e l’allocazione della banda disponibile va ottimizzata al massimo. I simulatori esistenti di solito consentono al progettista di lavorare solo con descrizioni molto astratte del sistema, nascondendo al-cuni parametri (come il packet error rate, la potenza sul canale, i pacchetti persi e così via) che invece in molte applicazioni è importante conoscere. Per questo motivo, lo scopo di questa tesi è presentare un nuovo tipo di simulatore Bluetooth che sia più vicino a quella che sarà l’implementazione vera e propria del sistema finale. Descriveremo alcune applicazioni, come la trasmissione di audio real-time, e vedremo come queste applicazioni possano essere adattate anche a standard diversi dal Bluetooth, come l’802.15.4, mediante l’introduzione di un opportuno (e migliorato) vocoder. A sostegno della progettazione del simulatore, presen-teremo un ambiente di sviluppo grafico che permette di disegnare i sistemi da progettare e di visualizzare le forme d’onda a debugging time, oltre che eseguire il comune debug su codice.<br>In recent years, wireless networks have become an ubiquitous, affordable and well-accepted reality. This is particularly true for networks such as Bluetooth and Wi-Fi, which today are almost everywhere and are used for the most different applications. In many cases, when using an off-the-shelf chip, the designer can limit himself to work on the highest levels of the protocol stack and to simply implement the application layer. In other cases, the designer must go down through the stack and work on a lower level where he can see and control some network parameters that he cannot access from the application layer. It happens, for instance, when he has to design a real-time system, or when the required data-rate is high and the available bandwidth allocation must be accurately tailored. Existing simulators usually let the designer work only with very abstract system description, hiding some parameters (such as the packet error rate, the signal power, the corrupted packets, and so on) which many applications have to be aware of. For this reason, the goal of this thesis is to present a new kind of Bluetooth simulator which matches closely the real world implementation of the desired system. We will describe some applications, such as the real-time audio transmission, and we’ll see how these applications can be adapted for other wireless standards, such as the IEEE 802.15.4, with the introduction of a well chosen (and improved) speech vocoder. As a design-helping tool we will present a graphical design environment that let the user draw the system he wants to design, and see the waveform while the debugging is in progress.
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Bashri, Mohd Saiful Riza. "Wearable devices for microwave head diagnostic systems." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/33243.

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Although current head imaging technologies such as magnetic resonance imaging (MRI) and computed tomography (CT) are capable of providing accurate diagnosis of brain injuries such as stroke and brain tumour, they have several limitations including high cost, long scanning time, bulky and mostly stationary. On the other hand, radar-based microwave imaging technology can offer a low cost, non-invasive and non-ionisation method to complement these existing imaging techniques. Moreover, a compact and wearable device for microwave head imaging is required to facilitate frequent or real-time monitoring of a patient by providing more comfort to the patient. Therefore, a wearable head imaging device would be a significant advantage compared to the existing wideband microwave head sensing devices which typically utilise rigid antenna structure. Furthermore, the wearable device can be integrated into different microwave imaging setups such as real-time wearable head imaging systems, portable systems and conventional stationary imaging tools for use in hospitals and clinics. This thesis presents the design and development of wearable devices utilising flexible antenna arrays and compact radio frequency (RF) switching circuits for wideband microwave head imaging applications. The design and characterisation of sensing antennas using flexible materials for the wearable head imaging device are presented in the first stage of this study. There are two main variations of monopole antennas that have been developed in this research, namely trapezoidal and elliptical configurations. The antennas have been fabricated using different flexible substrate materials such as flexible FR-4, polyethylene terephthalate (PET) and textile. Wideband performances of the antennas have been achieved by optimising their co-planar waveguide feeding line structures. Importantly, the efficiencies of the fabricated antennas have been tested using a realistic human head phantom by evaluating their impedance matching performances when operating in close proximity to the head phantom. The second stage of the study presents the development of wearable antenna arrays using the proposed flexible antennas. The first prototype has been built using an array of 12 flexible antennas and a conformal absorbing material backed with a conductive sheet to suppress the back lobe radiation of the monopole antennas. Additionally, the absorber also acts as a mounting base to hold the antennas where the wearable device can be comfortably worn like a hat during the measurement and monitoring processes. The effect of mutual coupling between adjacent antennas in the array has been investigated and optimised. However, the use of the absorbing material makes the device slightly rigid where it can only be fitted on a specific head size. Thus, a second prototype has been developed by using a head band to realise a stretchable configuration that can be mounted on different sizes of human heads. Furthermore, due to the stretchable characteristic of the prototype, the antennas can be firmly held in their positions when measurements are made. In addition, fully textile based sensing antennas are employed in this prototype making it perfectly suitable for monitoring purposes. Low cost and compact switching circuits to provide switching mechanism for the wearable antenna array are presented in the third stage of this study. The switching circuit is integrated with the antenna array to form a novel wearable microwave head imaging device eliminating the use of external bulky switching network. The switching circuit has been built using off-the-shelf components where it can be controlled wirelessly over Bluetooth connection. Then, a new integrated switching circuit prototype has been fabricated using 6-layer printed circuit board (PCB) technology. For the purpose of impedance matching for the radio-frequency (RF) routing lines on the circuit, a wideband Microstrip-to-Microstrip transition is utilised. The final stage of this study investigates the efficacy and sensitivity of the proposed wearable devices by performing experiments on developed realistic human head phantoms. Initially, a human head phantom has been fabricated using food-based ingredients such as tap water, sugar, salt, and agar. Subsequently, lamb's brains have been used to improve the head phantom employed in the experiments to better mimic the heterogeneous human brain. In terms of imaging process, an interpolation technique developed using experimental data has been proposed to assist the localisation of a haemorrhage stroke location using the confocal delay-and-sum algorithm. This new technique is able to provide sensible accuracy of the location of the blood clot inside the brain. The wearable antenna arrays using flexible antennas and their integrations with compact and low cost switching circuits reported in this thesis make valuable contribution to microwave head imaging field. It is expected that a low-cost, compact and wearable radar-based microwave head imaging can be fully realised in the future for wide range of applications including static scanning setup in hospitals, portable equipment in ambulances and as a standalone wearable head monitoring system for remote and real-time monitoring purposes.
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Taji, Bahareh. "Signal Quality Assessment in Wearable ECG Devices." Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/38851.

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There is a current trend towards the use of wearable biomedical devices for the purpose of recording various biosignals, such as electrocardiograms (ECG). Wearable devices have different issues and challenges compared to nonwearable ones, including motion artifacts and contact characteristics related to body-conforming materials. Due to this susceptibility to noise and artifacts, signals acquired from wearable devices may lead to incorrect interpretations, including false alarms and misdiagnoses. This research addresses two challenges of wearable devices. First, it investigates the effect of applied pressure on biopotential electrodes that are in contact with the skin. The pressure affects skin–electrode impedance, which impacts the quality of the acquired signal. We propose a setup for measuring skin–electrode impedance during a sequence of applied calibrated pressures. The Cole–Cole impedance model is utilized to model the skin–electrode interface. Model parameters are extracted and compared in each state of measurement with respect to the amount of pressure applied. The results indicate that there is a large change in the magnitude of skin–electrode impedance when the pressure is applied for the first time, and slight changes in impedance are observed with successive application and release of pressure. Second, this research assesses the quality of ECG signals to reduce issues related to poor-quality signals, such as false alarms. We design an algorithm based on Deep Belief Networks (DBN) to distinguish clean from contaminated ECGs and validate it by applying real clean ECG signals taken from the MIT-BIH arrhythmia database of Physionet and contaminated signals with motion artifacts at varying signal-to-noise ratios (SNR). The results demonstrate that the algorithm can recognize clean from contaminated signals with an accuracy of 99.5% for signals with an SNR of -10 dB. Once low- and high-quality signals are separated, low-quality signals can undergo additional pre-processing to mitigate the contaminants, or they can simply be discarded. This approach is applied to reduce the false alarms caused by poor-quality ECG signals in atrial fibrillation (AFib) detection algorithms. We propose a signal quality gating system based on DBN and validate it with AFib signals taken from the MIT-BIH Atrial Fibrillation database of Physionet. Without gating, the AFib detection accuracy was 87% for clean ECGs, but it markedly decreased as the SNR decreased, with an accuracy of 58.7% at an SNR of -20 dB. With signal quality gating, the accuracy remained high for clean ECGs (87%) and increased for low SNR signals (81% for an SNR of -20 dB). Furthermore, since the desired level of quality is application dependent, we design a DBN-based algorithm to quantify the quality of ECG signals. Real ECG signals with various types of arrhythmias, contaminated with motion artifacts at several SNR levels, are thereby classified based on their SNRs. The results show that our algorithm can perform a multi-class classification with an accuracy of 99.4% for signals with an SNR of -20 dB and an accuracy of 91.2% for signals with an SNR of 10 dB.
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Books on the topic "Smart and Wearable Devices"

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Lay-Ekuakille, Aimé, and Subhas Chandra Mukhopadhyay, eds. Wearable and Autonomous Biomedical Devices and Systems for Smart Environment. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15687-8.

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Lay-Ekuakille, Aimé. Wearable and Autonomous Biomedical Devices and Systems for Smart Environment: Issues and Characterization. Springer Berlin Heidelberg, 2010.

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McCann, J., and D. Bryson. Smart clothes and wearable technology. Woodhead Publishing, 2009.

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Kilani, Dima, Baker Mohammad, Mohammad Alhawari, Hani Saleh, and Mohammed Ismail. Power Management for Wearable Electronic Devices. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-37884-4.

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The wonderful world of wearable devices. Rosen Publishing's Rosen Central, 2015.

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Gargiulo, Gaetano D., and Ganesh R. Naik, eds. Wearable/Personal Monitoring Devices Present to Future. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-5324-7.

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Davis, Michael, Michael Kirwan, Walter Maclay, and Harry Pappas. Closing the Care Gap with Wearable Devices. Productivity Press, 2022. http://dx.doi.org/10.4324/9781003304036.

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Alhawari, Mohammad, Baker Mohammad, Hani Saleh, and Mohammed Ismail. Energy Harvesting for Self-Powered Wearable Devices. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-62578-2.

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Mokhtari, Fatemeh. Self-Powered Smart Fabrics for Wearable Technologies. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-06481-4.

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Xiaoming, Tao, and Textile Institute, eds. Wearable electronics and photonics. Woodhead, 2003.

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Book chapters on the topic "Smart and Wearable Devices"

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Marriam, Ifra, Mike Tebyetekerwa, Hiran Chathuranga, Shengyuan Yang, and Cheng Yan. "Fabrication Techniques for Wearable Batteries." In Smart and Flexible Energy Devices. CRC Press, 2022. http://dx.doi.org/10.1201/9781003186755-22.

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Sakthi, A. Siva, Abinaya Inbamani, Ramya Elango, et al. "Healthcare Solutions Using Wearable Devices." In Smart and Secure Internet of Healthcare Things. CRC Press, 2022. http://dx.doi.org/10.1201/9781003239895-1.

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Volety, Rohit, and P. Geethanjali. "Smart Home Automation Using Wearable Technology." In Wearable/Personal Monitoring Devices Present to Future. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-5324-7_11.

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Banafa, Ahmed. "The Smart Platform: Wearable Computing Devices (WCD)." In Quantum Computing and Other Transformative Technologies. River Publishers, 2023. http://dx.doi.org/10.1201/9781003339175-44.

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Velázquez, Ramiro. "Wearable Assistive Devices for the Blind." In Wearable and Autonomous Biomedical Devices and Systems for Smart Environment. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15687-8_17.

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Li, Zhe, Yaxi Chen, and Wenrong Tan. "DroneMyo: Proactive Control of Unmanned Aerial Vehicle Based on Wearable Devices." In Smart Graphics. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53838-9_20.

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Yang, Yu, Sijun Yu, Yuwen Hao, Xiao Xu, and Huiliang Liu. "The SWOT Analysis of the Wearable Devices in Smart Health Applications." In Smart Health. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59858-1_1.

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Rinaldi, Alessandra, Claudia Becchimanzi, and Francesca Tosi. "Wearable Devices and Smart Garments for Stress Management." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-96071-5_92.

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Jia, Yingzhen, and Tianle Yin. "Application of Smart Wearable Devices in Elderly Care." In The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-89508-2_79.

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Amanatides, Chelsea, Stephen Hansen, Ariana S. Levitt, et al. "Wearable Smart Garment Devices for Passive Biomedical Monitoring." In Biomedical Signal Processing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-67494-6_4.

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Conference papers on the topic "Smart and Wearable Devices"

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Mavroidis, C., J. Nikitczuk, B. Weinberg, et al. "Smart Portable Rehabilitation Devices." In ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-85517.

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In this paper we present several new advancements in the area of smart rehabilitation devices that have been developed by the Northeastern University Robotics and Mechatronics Laboratory. They are all compact, wearable and portable devices and boast re-programmable, real time computer controlled functions as the central theme behind their operation. The sensory information and computer control of the three described devices make for highly efficient and versatile systems that represent a whole new breed in wearable rehabilitation devices. Their applications range from active-assistive rehabilitation to resistance exercise and even have applications in gait training. The three devices described are: a transportable continuous passive motion elbow device, a wearable electro-rheological fluid based knee resistance device, and a wearable electrical stimulation and biofeedback knee device.
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Wei, Ding, and Chen Lin. "Smart Wellness Wearable Devices." In 2022 3rd International Conference on Language, Art and Cultural Exchange（ICLACE 2022). Atlantis Press, 2022. http://dx.doi.org/10.2991/assehr.k.220706.075.

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Xu, Weitao. "Mobile Applications Based on Smart Wearable Devices." In SenSys '15: The 13th ACM Conference on Embedded Network Sensor Systems. ACM, 2015. http://dx.doi.org/10.1145/2809695.2822525.

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da Silva, Jonathan Cristovão Ferreira, Vicente José Peixoto de Amorim, Pedro Sebastião de Oliveira Lazaroni, Ricardo Augusto Rabelo Oliveira, and Mateus Coelho Silva. "Towards novel smart wearable sensors to classify subject-specific human walking activities." In Anais Estendidos do Simpósio Brasileiro de Engenharia de Sistemas Computacionais. Sociedade Brasileira de Computação - SBC, 2022. http://dx.doi.org/10.5753/sbesc_estendido.2022.228153.

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In this century, smart devices are increasingly present in our lives, such as at work, sports, or household chores. In this context, we have wearable devices that can help people with health monitoring or physical performance in sports activities. With the integration of artificial intelligence (AI), these wearable devices can identify injuries in athletes or care for the elderly in rehabilitation from human activity recognition (HAR). AI techniques are commonly applied for pattern recognition, such as image classification or HAR. In this context, we seek to develop a smart wearable device to recognize walking activities. In order to improve the identification of these tasks through AI algorithms, we propose the fusion of data between four sensors called SPUs. Each SPU has NodeMCU ESP-32 and BNO080 IMU hardware in its architecture. The data from these hardware provides information in high precision. A zero W raspberry pi collected this information. After extracting and manipulating this data, we trained a deep learning model. The model accuracy was higher than 92% reaching an overall accuracy of 97%. Therefore, the smart wearable device showed a new tool for recognizing walking activity, which could be applied in the future to recognize more complex tasks.
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Gultekin, Buse, Ozge Taylan Moral, and Volkan Kilic. "TDOA Based Indoor Localization of Wearable Smart Devices." In 2021 29th Signal Processing and Communications Applications Conference (SIU). IEEE, 2021. http://dx.doi.org/10.1109/siu53274.2021.9477968.

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Alshaal, Salah Eddin, Stylianos Michael, Andreas Pamporis, Herodotos Herodotou, George Samaras, and Panayiotis Andreou. "Enhancing Virtual Reality Systems with Smart Wearable Devices." In 2016 17th IEEE International Conference on Mobile Data Management (MDM). IEEE, 2016. http://dx.doi.org/10.1109/mdm.2016.60.

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Weaver, Kyle, Dylan Shumway, Tae-Heon Yang, Young-Min Kim, and Jeong-Hoi Koo. "Investigation of Variable Stiffness Effects on Radial Pulse Measurements Using Magneto-Rheological Elastomers." In ASME 2019 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/smasis2019-5708.

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Abstract Current wearable technologies strive to incorporate more medical functionalities in wearable devices for tracking health conditions and providing information for timely medical treatments. Beyond tracking of a wearer’s physical activities and basic vital signs, the advancement of wearable healthcare devices aspires to continuously monitor health parameters, such as cardiovascular indicators. To properly monitor cardiovascular health, the wearables should accurately measure blood pressure in real-time. However, current devices on the market are not validated for continuous monitoring of blood pressure at a clinical level. To develop wearable healthcare devices such applications, they must be validated by considering various parameters, such as the effects of varying skin properties. Being located between the blood vessel and the wearable device, the skin can affect the sensor readings of the device. The primary goal of this study is to investigate the effect of skin property on the radial pulse measurements. To this end, a range of artificial vein-inserted skin samples with varying properties is fabricated using Magneto-Rheological Elastomers (MRE), materials whose mechanical properties can be altered by external magnetic fields. The samples include layers to simulate the structure of skin and a silicone vein for the pulse to pass through. Note that they are not intended to represent real human skin-vein properties but created to vary a range of stiffness properties to carry out the study. Experiments are performed using a cam system capable of generating realistic human pulse waveforms to pass through the samples. During the indentation testing, the sample is compressed using a dynamic mechanical analyzer (DMA) to record experienced surface pressure, allowing the pulse patterns to be studied. Various samples are used to probe the effects of base resin hardness, iron content, and magnetic field. A pressure sensor incorporated in the cam simulator is used to benchmark the internal pulse pressure of the vein while the DMA indents the sample in order to note the pulse pressures being passed through the sample. Test results show that the properties of the skin influence the resulting pulse behaviors, particularly the ratio of the recorded pulse pressures from the sensor and the DMA.
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Jung, Euichul, Young Joo Jang, and Whang Jae Lee. "Study on Preferred Gestural Interaction of Playing Music for Wrist Wearable Devices." In Applied Human Factors and Ergonomics Conference. AHFE International, 2021. http://dx.doi.org/10.54941/ahfe100581.

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Recently, many gesture-based interactive devices have been developed. Gesture is one of the most intuitive and natural ways to communicate each other, so gesture recognition technology is becoming huge issues in interaction design. Wrist wearable devices such as smart watches, Nike FuelBand, and Samsung Galaxy Gear are vitalized on the market, and there are attempts to control the wrist wearable devices with gestural interaction. In order to design more user-centered devices, development of gesture standards which gesture is appropriate for which operation becomes very important. In particular, there are two different situations gesture interaction is required: 1) people control objects that exist around then such as TV and vehicle, and 2) people control objects put on their body such as smart watch. This paper assumes that the two different situations may require different gesture interactions. The goal of this paper is to reveal preferred gesture interaction for wrist wearable devices. The function of playing music is selected for the experiment because it is most common and popular function on almost all digital devices. This paper consists of three parts: 1) collect existing gesture signal conventions and categorize them, 2) conduct a survey to find out preferred gestures for each function of playing music in two different situations, and 3) analyze the result for defining the most preferred gesture interactions and considering rationales for designing gesture interaction for wrist wearable device.
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Zhao, Xiaoyue, Zoubeida Ounaies, Samuel Rosset, and Iain Anderson. "A Study on the Performance of a Novel Hybrid Triboelectric-Dielectric Elastomer Generator Based on PDMS Composites." In ASME 2021 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/smasis2021-67134.

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Abstract Dielectric elastomer generators (DEGs) have been developed to harvest mechanical energy from various sources, such as human motion, water and wind. In particular, DEGs possess potential in wearable applications since they are light, flexible, and have high energy density. However, the requirement of an external circuit with high bias voltage that is used to polarize the dielectric elastomer limits their applications. On the other hand, triboelectric devices gained particular attention in the area of wearable electronics recently due to their good flexibility, portability and cost effectiveness. In addition, triboelectric devices can generate relatively high voltage, which could potentially polarize the dielectric elastomer in the DEG. In this study, a novel hybrid triboelectric-DEG structure is proposed to take advantage of the positive attributes of both. The triboelectric device part of the triboelectric-DEG, which is composed of a single-wall carbon nanotube (SWCNT)-ionic liquid (IL)-PDMS composite and a Teflon film, was fabricated and tested experimentally. The SWCNT-IL-PDMS composite is flexible and its electrical conductivity is high enough to transfer charges without an electrode, which makes the novel hybrid triboelectric-DEG a completely soft and independent energy harvester. The open-circuit voltage of the triboelectric device part reached to 114V, which is high enough to prime a DEG in a self-priming circuit configuration. Based on the experimental results of the triboelectric device part, the configuration and connection of the novel triboelectric-DEG were designed and the energy density was predicted. The resulting triboelectric-DEG can offset the shortcoming of conventional DEGs and greatly increase the feasibility of such device in wearable and mobile applications, to make polymer-based self-powered wearables a reality.
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You, Guoping, Liying Zhu, and Jie He. "Research on Smart Health Services Based on Wearable Devices." In 2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). IEEE, 2019. http://dx.doi.org/10.1109/iaeac47372.2019.8997990.

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Reports on the topic "Smart and Wearable Devices"

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Etemadi, Mozziyar, Will McGrath, Shuvo Roy, and Bjoern Hartmann. Fabryq: Using Phones as Smart Proxies to Control Wearable Devices from the Web. Defense Technical Information Center, 2014. http://dx.doi.org/10.21236/ada611853.

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Chaparadza, Diana. An Analysis of Patient-Generated Health Data in Assisting Nurses and Physicians to Better Treat Patients with Hypertension. University of Tennessee Health Science Center, 2020. http://dx.doi.org/10.21007/chp.hiim.0080.

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Patient Generated Health Data (PGHD is not new but it has gained more attention these past years due to the advent of smart devices, remote monitoring devices and many applications on various smart devices. PGHD reflects medications and treatment, lifestyle choices, and health history. Unlike traditional medical visits, where clinicians collect and manage data within their offices, PGHD is collected by patients throughout the course of their day and provides an insight of how they are responding to treatments or lifestyle choices. Examples include blood glucose monitoring or blood pressure readings using home health equipment, exercise and diet tracking using mobile applications or wearable devices such as the Fitbit or other smart watches.
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Sofronova, Daniela, and Radostina A. Angelova. A Method for Testing of the Conductivity Decay of Threads for Embedded Wearable Electronic Devices in Smart Textiles. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, 2020. http://dx.doi.org/10.7546/crabs.2020.02.15.

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Nam, Changhyun, and Young-A. Lee. Validation of the Wearable Acceptability Range Scale for Smart Apparel. Iowa State University. Library, 2019. http://dx.doi.org/10.31274/itaa.8295.

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Franklin, Joshua M., Gema Howell, Scott Ledgerwood, and Jaydee L. Griffith. Security analysis of first responder mobile and wearable devices. National Institute of Standards and Technology, 2020. http://dx.doi.org/10.6028/nist.ir.8196.

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Howell, Gema. Security Guidance for First Responder Mobile and Wearable Devices. National Institute of Standards and Technology, 2022. http://dx.doi.org/10.6028/nist.ir.8235.

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Gavrila, Serban, Clement Seveillac, and Vlad Korolev. Smart cards and mobile handheld devices :. National Institute of Standards and Technology, 2005. http://dx.doi.org/10.6028/nist.ir.7206.

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Zhao, Yan. Mesoporous silica nanoparticles as smart and safe devices for regulating blood biomolecule levels. Office of Scientific and Technical Information (OSTI), 2011. http://dx.doi.org/10.2172/1029552.

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Hogaboam, Liliya. Assessment of Technology Adoption Potential of Medical Devices: Case of Wearable Sensor Products for Pervasive Care in Neurosurgery and Orthopedics. Portland State University Library, 2000. http://dx.doi.org/10.15760/etd.6093.

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Evans, Jon, Ian Porter, Emma Cockcroft, Al-Amin Kassam, and Jose Valderas. Collecting linked patient reported and technology reported outcome measures for informing clinical decision making: a scoping review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2021. http://dx.doi.org/10.37766/inplasy2021.10.0038.

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Review question / Objective: We aim to map out the existing research where concomitant use of patient reported and technology reported outcome measures is used for patients with musculoskeletal conditions. Condition being studied: Musculoskeletal disorders (MSD) covering injuries or disorders of the muscles, nerves, tendons, joints, cartilage, and spinal discs. Musculoskeletal manifestations of joint pathology. Eligibility criteria: 1) Peer-reviewed primary studies and literature reviews. Grey literature not included. 2) Studies which include co-administration of Patient-Reported Outcomes (PROMs) AND wearable electronic devices (e.g. fitness trackers, accelerometers, gyroscopes, pedometers smartphones, smartwatches) in musculoskeletal manifestations of joint pathology. Studies are EXCLUDED which feature wearable electronic devices but not concomitant/real time capturing of PROMs (e.g. they are recorded retrospectively/ at different timepoints). 3) Studies in languages other than English will be excluded unless a translation is available.
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