UWB-enabled Sensing for Fast and Effortless Blood Pressure Monitoring
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Blood Pressure (BP) is a critical vital sign to assess cardiovascular health. However, existing cuff-based and wearable-based BP measurement methods require direct contact between the user's skin and the device, resulting in poor user experience and limited engagement for regular daily monitoring of BP. In this paper, we propose a contactless approach using Ultra-WideBand (UWB) signals for regular daily BP monitoring. To remove components of the received signals that are not related to the pulse waves, we propose two methods that utilize peak detection and principal component analysis to identify aliased and deformed parts. Furthermore, to extract BP-related features and improve the accuracy of BP prediction, particularly for hypertensive users, we construct a deep learning model that extracts features of pulse waves at different scales and identifies the different effects of features on BP. We build the corresponding BP monitoring system named RF-BP and conduct extensive experiments on both a public dataset and a self-built dataset. The experimental results show that RF-BP can accurately predict the BP of users and provide alerts for users with hypertension. Over the self-built dataset, the mean absolute error (MAE) and standard deviation (SD) for SBP are 6.5 mmHg and 6.1 mmHg, and the MAE and SD for DBP are 4.7 mmHg and 4.9 mmHg.Keywords:
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Although wearable technologies incited by the “Internet of things” are gradually being presented, only a few studies have examined the adoption of wearable technologies. Despite its growing importance, wearable technologies has met with various challenges across the world, including limited adoption by potential consumers. Thus, this study empirically examines the antecedents of wearable technology adoption by potential consumers. Particularly, our result provide support for the importance of trust for overcoming hesitation and risk, related to wearable technology.
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Product characteristics of wearable devices have large impacts on users' initial trust as users intend to adopt wearable devices, which further impacts wearable devices' use intention. This paper aims at investigating the impacts of wearable device product characteristics on consumers' initial trust based on four factors: wearability, functionality, personalization, and integration. Through a questionnaire survey method, 328 valid questionnaires were obtained. The empirical analysis results from the structural equation model analysis show that wearability, functionality, and integration factors have significant impacts on the initial trust of wearable devices. The conclusions of the study can provide references for the future research on the initial trust of wearable devices, and point out the direction of product development for wearable device manufacturers.
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Wearable technology collectively describes some of the most exciting emerging technologies, encompassing smart gadgets, garments, jewelry, and other devices worn on the user's body. In recent years, high profile wearable devices such as the Google Glass, Apple Watch, and FitBit have captured both the public imagination and headlines. Wearable technology has the potential to change the world even more profoundly than other mobile technologies. The appearance of such high profile wearable devices in the end-consumer market has also lead to serious consideration of the implications of such technologies, previously limited to the pages of science fiction. The implications for security and privacy of individuals and organizations, and the potential dangers to both society and the economy, must be considered and addressed in order for wearable technology to successfully deliver upon its many promises. Through addressing such concerns, the pathway to a “wearable future” can be unlocked, and users can adopt wearable technology with confidence.
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With the rapid development of wearable technologies, wearable devices are gradually entering people's daily life. As a novel way of human-computer interaction, wearable devices have brought more and more convenience and assistance to people than ever before. In this paper, we firstly make a classification of wearable devices based on their functions and how they are worn. An introduction to the current development of wearable devices is also presented. Then, the challenges in the area of wearable devices and their possible solutions are discussed. Finally, the conclusions are drawn on the development and future trends of wearable devices and technologies.
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Together with the evolution of digital health care, the wearable electronics field has evolved rapidly during the past few years and is expected to be expanded even further within the first few years of the next decade. As the next stage of wearables is predicted to move toward integrated wearables, nanomaterials and nanocomposites are in the spotlight of the search for novel concepts for integration. In addition, the conversion of current devices and attachment-based wearables into integrated technology may involve a significant size reduction while retaining their functional capabilities. Nanomaterial-based wearable sensors have already marked their presence with a significant distinction while nanomaterial-based wearable actuators are still at their embryonic stage. This review looks into the contribution of nanomaterials and nanocomposites to wearable technology with a focus on wearable sensors and actuators.
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The advent of the Internet of Things (IoT) era has propelled the development of wearable technology. Wearable devices are widely used in medical, healthcare, sports, and safety applications, bringing more convenience to the living environment. Wearable devices can be worn on the body, collect body data using sensors, and process the collected data to obtain valuable information. IoT enables devices to connect and exchange and transmit data. Wearable devices in IoT can collect data for analysis and automatically adjust wearable device functions by connecting the obtained information to other devices. In this paper, we collect and organize articles on wearable devices used in IoT from 2017 to 2022 in terms of their applications, advantages, and disadvantages. We evaluate articles to identify wearable device application areas and evaluation criteria. Finally, we discussed the open issues of wearable devices and clarified how to face the future development and efforts of wearable devices in IoT.
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Abstract Invited for this month's cover picture is the group of Cheng Zhong. The cover picture shows the coming new era of flexible and wearable power sources for next‐generation wearable electronics. Read the full text of the Review at 10.1002/batt.202000115 .
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Wearable technology collectively describes some of the most exciting emerging technologies, encompassing smart gadgets, garments, jewelry, and other devices worn on the user's body. In recent years, high profile wearable devices such as the Google Glass, Apple Watch, and FitBit have captured both the public imagination and headlines. Wearable technology has the potential to change the world even more profoundly than other mobile technologies. The appearance of such high profile wearable devices in the end-consumer market has also lead to serious consideration of the implications of such technologies, previously limited to the pages of science fiction. The implications for security and privacy of individuals and organizations, and the potential dangers to both society and the economy, must be considered and addressed in order for wearable technology to successfully deliver upon its many promises. Through addressing such concerns, the pathway to a “wearable future” can be unlocked, and users can adopt wearable technology with confidence.
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With the development of smart mobile computer, more and more portable devices are coming into market that includes wearable devices.To evaluate the wearable devices, the wearable level is an important reference.In this paper, we proposed to evaluate wearable devices based on quality characteristics.However, the characteristics are usually unstable, historical sample size is small, index, show obvious non-normal distribution.These features make it hard to use the general statistical techniques for effective evaluation.A model based on support vector machine (SVM) is proposed to distinguish the wearable level.This paper introduces the current situation of wearable devices, descripts its classification and evaluation principle, and gives out the classification model and algorithm for wearable level.This work can be a beneficial reference to wearable standard.
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