Electrodeposition-enabled,electrically-transduced sensors and biosensors

Electrodeposition and electropolymerization have emerged as versatile tools for the fabrication of chemical and biosensors. The literature in this area, published since 2017, is the main focus of this review. Electropolymerization has played a particularly prominent role in sensor development since its discovery in 1980 by Diaz at IBM. The ability to entrain receptors such as antibodies, engineered virus particles, and metal chelating agents into a conductive polymer sensing element during electropolymerization has proven to be a powerful means of preparing chemiresistors for a variety of analyses. Electrodeposition has also been used to prepare nanostructured metal indicator microelectrodes, enabling of a new modality for transducing biosensors. Electrodeposited metal nanowires have formed the basis for rapid and sensitive sensors for hydrogen gas. Electrodeposition has also been exploited as a powerful means for amplifying weak biosensor signals, extending their dynamic range. Opportunities for the application of electrodeposition and electropolymerization for chemical and biological sensor fabrication and function are discussed.     

Reduced graphene oxide supersonically sprayed on wearable fabric and decorated with iron oxide for supercapacitor applications

We demonstrate the fabrication of wearable supercapacitor electrodes.The electrodes were applied to wearable fabric by supersonically spraying the fabric with reduced graphene oxide(rGO)followed by decoration with iron oxide(Fe2O3)nanoparticles via a hydrothermal process.The integration of iron oxide with rGO flakes on wearable fabric demonstrates immense potential for applications in high-energy-storage devices.The synergetic impact of the intermingled rGO flakes and Fe2O3 nanoparticles enhances the charge transport within the composite electrode,ultimately improving the overall electrochemical performance.Taking advantage of the porous nature of the fabric,electrolyte diffusion into the active rGO and Fe2O3 materials was significantly enhanced and subsequently increased the electrochemical interfacial activities.The effect of the Fe2O3 concentration on the overall electrochemical performance was investigated.The optimal composition yields a specific capacitance of 360 F g-1 at a current density of 1A g-1 with a capacitance retention rate of 89％after 8500 galvanostatic cycles,confirming the long-term stability of the Fe2O3/rGO fabric electrode.     

Wearable computers: Information tool for the twentyfirst century

The wearable computer is a portable computer that is actually worn on the user's body. Ergonomics is therefore a vital feature of its design. Since humans naturally communicate with voice, a wearable computer also responds to the voice. Wearable computers and global wireless networks make it possible to bring exciting capabilities to the individual. Until recently, wearable computer development has been restricted to academic and military laboratories. Now, technological advances and reduced cost have ignited investor excitement about wearable computers. Wearable system applications in manufacturing, logistics, medicine, training, quality control, communications and even entertainment are now becoming widespread. The earliest development of wearable computers occurred in the 1960s. All of the elements of the modern wearable computer were in place in the Eudaemons system for predicting outcome on a roulette wheel. Since then, wearable computer development has paralleled advances in microprocessor technology. After addressing the important distinction between wearable and mobile computers, this paper will look at wearable computers as an information tool for industry. A short history of wearable computers will trace development from the early single application attempts to today's feature-rich systems. A discussion on current and anticipated applications is then followed by an overview of important related technologies. Finally, the paper will assess how wearable computers could impact twentyfirst century industry and society.     

Location-free haptic interaction for large-area social applications

In this paper, we discuss the potential of force perception technologies for realizing hand-held devices in the field of social systems. We propose and develop an interactive force-sensation-based navigation system for waiters based on a force perception technology that we have proposed. The navigation system consists of our new hand-held haptic interface and a camera-based position and posture identification system. Since the proposed compact haptic interface does not require external grounding, it can be used outside the laboratory and does not interrupt human activity. We verify the feasibility of the system in trials where we collected the responses of system users.     

Factors influencing the perceived usability of wearable chair exoskeleton with market segmentation: A structural equation modeling and K-Means Clustering approach

The sudden implementation of work-from-home setup has caused the rise of sedentary position among employees which led to an increase in development or worsening of musculoskeletal disorders. To help mitigate this problem, wearable assistive devices such as wearable chairs have been argued to be beneficial. Several studies have expounded on the benefit of using this, however little to no available device is yet present in the Philippines. To which, businesses and developers could capitalize on this aspect. This study examined the perceived usability of wearable chair exoskeleton in the Philippines by integrating the Unified Theory of Acceptance and Use of Technology (UTAUT2) and System Usability Scale (SUS). A questionnaire was developed and distributed to 365 residents in the Philippines to measure the factors and their relationship to perceived usability accurately. Indicators and measures used in the questionnaire were derived from existing literature on technology acceptance and usability evaluation. Partial least squares structural equation modeling (PLS-SEM) was used for this study. Results revealed that perceived usability was significantly influenced by usage behavior. At the same time, habit, hedonic motivation, and performance expectancy significantly influenced the behavioral intention of the wearable chair exoskeleton. K-Means clustering was also utilized to identify clusters of target users of the wearable chair in the country, such as high-value customers, core customers, and low-value customers. Results indicated that demographic factors such as females, 30 years old and below, earning Php45,000 and above monthly, and living in a city are highly likely to utilize the product. The findings of this study can be applied and extended as a theoretical framework for future researchers of consumer behavior and exoskeleton developers for enhancing the innovation and usability of this new technology. This study may also be used and capitalized by investors to strategize the development and marketing of the exoskeletons among industrial and teleworkers worldwide.     

Body-based interfaces

This research explores different ways to use features of one's own body for interacting with computers. Such "body-based" interfaces may find good uses in wearable computing or virtual reality systems as part of a 3D multi-modal interface in the future, freeing the user from holding interaction devices. Four types of body-based interfaces have been identified: Body-inspired metaphor (BIM); Body-as-interaction-surface (BAIS); Mixed mode (MM); and Object mapping (OM). These four body-based interfaces were applied to a few different applications (and associated tasks) and were tested for their performance and preference. It was generally found that, among the four, the BIM exhibited low error rates, but produced relatively longer task completion times and significant fatigue. The BAIS method had the contrasting character of higher error rates, but shorter task completion times and lower intuitiveness. The OM method exhibited high error rates, longer completion times, and much fatigue. Overall, the MM was superior in terms of both performance and preference as it combined the merits of the above three methods. Thus, it is expected, for applications with many associated tasks, a careful division of tasks among those that have natural semantic links to body parts and those that do not, is necessary to design the most performing body-based interface.     

Human Pacman: a mobile,wide-area entertainment system based on physical,social, and ubiquitous computing

Human Pacman is a novel interactive entertainment system that ventures to embed the natural physical world seamlessly with a fantasy virtual playground by capitalizing on mobile computing, wireless LAN, ubiquitous computing, and motion-tracking technologies. Our human Pacman research is a physical role-playing augmented-reality computer fantasy together with real human–social and mobile gaming. It emphasizes collaboration and competition between players in a wide outdoor physical area which allows natural wide-area human–physical movements. Pacmen and Ghosts are now real human players in the real world, experiencing mixed computer graphics fantasy–reality provided by using the wearable computers. Virtual cookies and actual tangible physical objects are incorporated into the game play to provide novel experiences of seamless transitions between real and virtual worlds. We believe human Pacman is pioneering a new form of gaming that anchors on physicality, mobility, social interaction, and ubiquitous computing.

微型传感器在汽车工程中的应用

介绍了基于微机电系统(MEMS)技术的微型传感器的特点和发展概况,以及应用在汽车发动机控制、安全系统等方面的微型传感器的原理、特点和主要技术参数.并简要介绍了高温微电子在汽车上的应用.同时,预测了未来汽车微型传感器的发展趋势和市场应用前景.     

Application level performance evaluation of wearable devices for stress classification with explainable AI

Stress has become one of the most prominent problems of modern societies and a key contributor to major health issues. Dealing with stress effectively requires detecting it in real-time, informing the user, and giving instructions on how to manage it. Over the past few years, wearable devices equipped with biosensors that can be utilized for stress detection have become increasingly popular. Since they come with various designs and technologies and acquire biosignals from different body locations, choosing a suitable device for a particular application has become a challenge for researchers and end-users. This study compares seven common wearable biosensors for stress detection applications. This was accomplished by collecting physiological sensor data during Baseline, Stress, Recovery, and Cycling sessions from 32 participants. Machine learning algorithms were used to classify four stress classes, and the results obtained from all wearables were compared. Following this, a state-of-the-art explainable artificial intelligence method was employed to clarify our models’ predictions and investigate the influence different features have on the models’ outputs. Despite the results showing that ECG wearables perform slightly better than the rest of the devices, adding a second biosignal (EDA) improved the results significantly, tipping the balance toward multisensor wearables. Finally, we concluded that although the output results of each model can be affected by various factors, in most cases, there is no significant difference in the accuracy of stress detection by different wearables. However, the decision to select a particular wearable for stress detection applications must be made carefully considering the trade-off between the users’ expectations and preferences and the pros and cons of each device.