A Survey of Wearable Devices and Challenges Seneviratne, Suranga; Yining Hu; Tham Nguyen ...
IEEE Communications surveys and tutorials,
01/2017, Letnik:
19, Številka:
4
Journal Article
Recenzirano
As smartphone penetration saturates, we are witnessing a new trend in personal mobile devices-wearable mobile devices or simply wearables as it is often called. Wearables come in many different forms ...and flavors targeting different accessories and clothing that people wear. Although small in size, they are often expected to continuously sense, collect, and upload various physiological data to improve quality of life. These requirements put significant demand on improving communication security and reducing power consumption of the system, fueling new research in these areas. In this paper, we first provide a comprehensive survey and classification of commercially available wearables and research prototypes. We then examine the communication security issues facing the popular wearables followed by a survey of solutions studied in the literature. We also categorize and explain the techniques for improving the power efficiency of wearables. Next, we survey the research literature in wearable computing. We conclude with future directions in wearable market and research.
Wearable sensors hold profound significance in our increasingly interconnected world, revolutionizing the way we monitor and manage our health, daily activities, and environments. These compact, ...unobtrusive tools have transcended the realm of mere gadgets to become indispensable tools for individuals and healthcare professionals alike. By continuously collecting data on vital signs, physical activity, sleep patterns, and more, wearables empower users to gain valuable insights into their well-being, facilitating proactive health management. Beyond preventive medicine, wearables find applications in diverse fields, from sports performance optimization to industrial safety monitoring, making them catalysts for transformative change in the way we live, work, and thrive. As technology continues to advance, the significance of wearables in enhancing our lives and pushing the boundaries of knowledge will only continue to grow. In this review, we focused on the recent advances in the field of wearables for continuous non-invasive monitoring of cardiovascular, body temperature and blood glucose. These sensors are commonly incorporated into garments or stylish accessories such as watches, allowing individuals to monitor different facets of their health, including metabolic processes and vital signs. In premise, the worldwide wearables market is undergoing substantial growth propelled by technological advancements, expanding applications, and the need for inventive preventive healthcare solutions. Despite existing challenges, the industry is well-positioned for ongoing expansion as it tackles these issues and pushes the frontiers of wearable technology.
Display omitted
•This review discusses the novel and most recent developments on continuous non-invasive wearable sensors.•Applications of wearable sensors for cardiovascular, temperature and blood glucose monitoring are presented.•Challenges and possible solutions associated with the wide availability of wearables were discussed.
This department provides an overview the progress the authors have made to the emerging area of embedded and mobile forms of on-device deep learning. Their work addresses two core technical ...questions. First, how should deep learning principles and algorithms be applied to sensor inference problems that are central to this class of computing? Second, what is required for current and future deep learning innovations to be efficiently integrated into a variety of mobile resource-constrained systems? Toward answering such questions, the authors describe phone, watch, and embedded prototypes that can locally run large-scale deep networks processing audio, images, and inertial sensor data. These prototypes are enabled with a variety of algorithmic and system-level innovations that vastly reduce conventional inference-time overhead of deep models.
This study makes use of a cohesive yet innovative research model to identify the determinants of the adoption of smart watches using constructs from the Technology Acceptance Model (TAM) and ...constructs of smartwatches, including effectiveness, content richness, and personal innovativeness. The chief objective of the study was to encourage the use of smartwatches for medical purposes so that the role of doctors can be made more effective and to facilitate access to patient records. Our conceptual framework highlights the association of TAM constructs (i.e., perceived usefulness and perceived ease of use) with the content richness, the construct of user satisfaction, and innovativeness. To measure the effectiveness of the smartwatch, an external factor based on the flow theory was added, which emphasizes the control over the smartwatch and the degree of involvement. The study employs data from 385 respondents involved in the field of medicine, such as doctors, patients, and nurses. The data were gathered through a survey and used for evaluation of the research model using partial least squares structural equation modeling (PLS-SEM) and machine learning (ML) models. The significance and performance of factors impacting THE adoption of smartwatches were also identified using Importance-Performance Map Analysis (IPMA). User satisfaction is the most important predictor of intention to adopt a medical smartwatch according to the ML and IPMA analyses. The fitting of the structural equation model to the sample showed a high dependence of user satisfaction on perceived usefulness and perceived ease of use. Furthermore, two critical factors, innovativeness and content richness, are demonstrated to enhance perceived usefulness. However, one should consider that perceived usefulness or behavioral intention could not be determined based on perceived ease of use. In general, the findings suggest that smartwatch usage could become critically important in the medical field as a mediator that allows doctors, patients, and other users to access essential information.
Activity-based wellness management is thought to be a powerful application for mobile health. It is possible to provide context-aware wellness services and track human activity thanks to accessing ...for multiple devices as well as gadgets that we use every day. Generally in smart gadgets like phones, watches, rings etc., the embedded sensors having a wealth data that can be incorporated to person task tracking identification. In a real-world setting, all researchers shown effective boosting algorithms can extract information in person task identification. Identifying basic person tasks such as talk, walk, sit along sleep. Our findings demonstrate that boosting classifiers perform better than conventional machine learning classifiers. Moreover, the feature engineering for differentiating an activity detection capability for smart phones and smart watches. For the purpose of improving the classification of fundamental human activities, upcoming mechanisms give the guidelines for identification for various sensors and wearable devices.
Wearable technologies are increasing both in number and variety enabling new ways for collecting personal data, as well as novel interaction modalities. Even though the Human-Computer Interaction ...(HCI) community has widely explored the potential applications of wearables, its theoretical contribution on this research field has been far from impressive. Most scholars and designers seem to rely on a series of dominant assumptions that look at wearables "from the outside" by focusing on their "external properties." When these assumptions are fully embraced at design-time, however, they may cloud opportunities for designing for the "internal aspects" of our everyday experience. In this article, I propose a theory that looks at wearables "from the inside,"giving a theoretical backdrop to all those wearable designs that pay attention to the internal aspects of interaction. By adopting a postphenomenological approach, I conceptualize wearable devices as "extensions" of our intentionality and introduce the "extension relation" to explain how wearables may alter how we relate to the world. In doing so, I propose a series of design considerations that aim to trace future research lines for all those wearables that are currently designed from an "externalistic" perspective.
Smart watches are trendy fashionable and wearable devices which were introduced in India in recent times. The main objective of this study is to understand the impact of social media in Islam on ...consumer buying behavior. The quantitative survey investigates the factors that influence user behavior towards smartwatches. Data of 160 respondents was collected and analyzed using SPSS and Microsoft Excel software. It has been observed that smart watches are trending in the digital age with the ability to replace smart phones. The findings of this study reveal various influencing factors such as friends, advertisements but most of the respondents are influenced by social factors to buy smart watches. The findings of this study will be useful for marketers and smart watch manufacturing companies to find out consumer perceptions of smart watches, and in Islamic studies this can be a da'wah facility in spreading goodness by optimizing developing technology.
This study sought to assess the performance of the Fitbit Charge HR, a consumer-level multi-sensor activity tracker, to measure physical activity and sleep in children.
59 healthy boys and girls aged ...9-11 years old wore a Fitbit Charge HR, and accuracy of physical activity measures were evaluated relative to research-grade measures taken during a combination of 14 standardized laboratory- and field-based assessments of sitting, stationary cycling, treadmill walking or jogging, stair walking, outdoor walking, and agility drills. Accuracy of sleep measures were evaluated relative to polysomnography (PSG) in 26 boys and girls during an at-home unattended PSG overnight recording. The primary analyses included assessment of the agreement (biases) between measures using the Bland-Altman method, and epoch-by-epoch (EBE) analyses on a minute-by-minute basis.
Fitbit Charge HR underestimated steps (~11.8 steps per minute), heart rate (~3.58 bpm), and metabolic equivalents (~0.55 METs per minute) and overestimated energy expenditure (~0.34 kcal per minute) relative to research-grade measures (p< 0.05). The device showed an overall accuracy of 84.8% for classifying moderate and vigorous physical activity (MVPA) and sedentary and light physical activity (SLPA) (sensitivity MVPA: 85.4%; specificity SLPA: 83.1%). Mean estimates of bias for measuring total sleep time, wake after sleep onset, and heart rate during sleep were 14 min, 9 min, and 1.06 bpm, respectively, with 95.8% sensitivity in classifying sleep and 56.3% specificity in classifying wake epochs.
Fitbit Charge HR had adequate sensitivity in classifying moderate and vigorous intensity physical activity and sleep, but had limitations in detecting wake, and was more accurate in detecting heart rate during sleep than during exercise, in healthy children. Further research is needed to understand potential challenges and limitations of these consumer devices.
Smart scales, smart watches, and smart rings with bioimpedance technology may create interference in patients with cardiac implantable electronic devices (CIEDs).
The purpose of this study was to ...determine interference at CIEDs with simulations and benchtop testing, and to compare the results with maximum values defined in the ISO 14117 electromagnetic interference standard for these devices.
The interference at pacing electrodes was determined by simulations on a male and a female computable model. A benchtop evaluation of representative CIEDs from 3 different manufacturers as specified in the ISO 14117 standard also was performed.
Simulations showed evidence of interference with voltage values exceeding threshold values defined in the ISO 14117 standard. The level of interference varied with the frequency and amplitude of the bioimpedance signal, and between male and female models. The level of interference generated with smart scale and smart rings simulations was lower than with smart watches. Across device manufacturers, generators demonstrated susceptibility to oversensing and pacing inhibition at different signal amplitudes and frequencies.
This study evaluated the safety of smart scales, smart watches, and smart rings with bioimpedance technology via simulation and testing. Our results indicate that these consumer electronic devices could interfere in patients with CIEDs. The present findings do not recommend the use of these devices in this population due to potential interference.
Purpose This study aimed to analyze the G-test results based on body composition and heart rate of fourth grade Air Force cadets, identify the relationships among body composition, heart rate, and ...G-resistance, and provide basic data for pilots and Air Force cadets to strengthen the G-tolerance. Methods This study used wearable devices to measure the heart rate and fatigue of 27 fourth-grade cadets of the Air Force Academy. Physical composition and physical fitness were assessed. Based on the measurement results, G-test result analysis and correlation analysis were performed. Results G-test results showed a steady heart rate (p=.015), deep sleep time (p<.001), and fatigue (p=.008) which have significant differences. Further, a 10-second heart rate at G-test (p<.001) and maximum heart rate (p<.001). There was also a statistically significant difference. Conclusions Effective G-test success for Air Force cadets would require improving aerobic performance, continuous fatigue, and physical fitness management. If various variables that affect G-test are analyzed and applied to physical education and physical training through continuous research over the next 2–3 years, it is expected to have a better outcome on the G-test success for every cadet.
PDF
