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The purpose of this paper is to investigate physiological indices related to comfort and health condition, based on which corresponding electronic equipment are selected and applied. A wearable monitoring system using sensor and liquid crystal display (LCD) techniques are then designed. Sensors are used to collect and transmit recording required signals from the wearer. A microcomputer with the type of AT89C52 is used to record and analyze the collected data. LCD is applied to display the health and comfort condition of the wearer.

A novel wearable monitoring system for the measurement of physiological indices and clothing microclimate is proposed in this study in order to monitoring both health and comfort condition of the wearer.

The proposed system provides reference for the application of sensor and display technologies in the field of smart clothing, which can be further applied to infant and child care, health care, home entertainment, military and industry.

This paper, first, investigated a framework of a wearable monitoring system considering both comfort and health condition and summarized the related physiological indices. The requirements of both comfort and health condition monitoring are analyzed to select appropriate electronic elements.

The purpose of this paper is to design a low-power human physiological parameters monitoring system which can monitor six vital parameters simultaneously based on wearable body sensor network.

This paper presents a low-power multiple physiological parameters monitoring system (MPMS) which comprises four subsystems. These are: electrocardiogram (ECG)/respiration (RESP) parameters monitoring subsystem with embedded algorithms; blood oxygen (SpO₂)/pulse rate (PR)/body temperature (BT)/blood pressure (BP) parameters monitoring subsystem with embedded algorithms; main control subsystem which is in charge of system-level power management, communication and interaction design; and upper computer software subsystem which manipulates system function and analyzes data.

Results have successfully demonstrated monitoring human ECG, RESP, PR, SpO₂, BP and BT simultaneously using the MPMS device. In addition, the power reduction technique developed in this work at the physical/hardware level is effective. Reliability of algorithms developed for monitoring these parameters is assessed by Fluke Prosim8 Vital Signs Simulators (produced by Fluke Corp. USA).

The MPMS device provides long-term health monitoring without interference from normal personal activities, which potentially allows applications in real-time daily healthcare monitoring, chronic diseases monitoring, elderly monitoring, human emotions recognization and so on.

First, a power reduction technique at the physical/hardware level is designed to realize low power consumption. Second, the proposed MPMS device enables simultaneously monitoring six key parameters. Third, unlike most monitoring systems in bulk size, the proposed system is much smaller (118 × 58 × 18.5 mm3, 140 g total weight). In addition, a comfortable smart shirt is fabricated to accommodate the portable device, offering reliable measurements.

Wearables are gaining prominence in the health-care industry and their use is growing. The elderly and other patients can use these wearables to monitor their vitals at home and have them sent to their doctors for feedback. Many studies are being conducted to improve wearable health-care monitoring systems to obtain clinically relevant diagnoses. The accuracy of this system is limited by several challenges, such as motion artifacts (MA), power line interference, false detection and acquiring vitals using dry electrodes. This paper aims to focus on wearable health-care monitoring systems in the literature and provides the effect of MA on the wearable system. Also presents the problems faced while tracking the vitals of users.

MA is a major concern and certainly needs to be suppressed. An analysis of the causes and effects of MA on wearable monitoring systems is conducted. Also, a study from the literature on motion artifact detection and reduction is carried out and presented here. The benefits of a machine learning algorithm in a wearable monitoring system are also presented. Finally, distinct applications of the wearable monitoring system have been explored.

According to the study reduction of MA and multiple sensor data fusion increases the accuracy of wearable monitoring systems.

This study also presents the outlines of design modification of dry/non-contact electrodes to minimize the MA. Also, discussed few approaches to design an efficient wearable health-care monitoring system.

Background: Every so often, one experiences different physically unstable situations which may lead to possibilities of suffering through vicious physiological risks and extents. Dynamic physiological activities are such a key metric that they are perceived by means of measuring galvanic skin response (GSR). GSR represents impedance of human skin that frequently changes based on different human respiratory and physical instability. Existing solutions, paved in literature and market, focus on the direct measurement of GSR by two sensor-attached leads, which are then parameterized against the standard printed circuit board mechanism. This process is sometimes cumbersome to use, resulting in lower user experience provisioning and adaptability in livelihood activities. The purpose of this study is to validate the novel development of the cost-effective GSR sensing system for affective usage for smart e-healthcare.

This paper proposes to design and develop a flexible circuit strip, populated with essential circuitry assemblies, to assess and monitor the level of GSR. Ordinarily, this flexible system would be worn on the back palm of the hand where two leads would contact two sensor strips worn on the first finger.

The system was developed on top of Pyralux. Initial goals of this work are to design and validate a flexible film-based GSR system to detect an individual’s level of human physiological activities by acquiring, amplifying and processing GSR data. The measured GSR value is visualized “24 × 7” on a Bluetooth-enabled smartphone via a pre-incorporated application. Conclusion: The proposed sensor-system is capable of raising the qualities such as adaptability, user experience, portability and ubiquity for possible application of monitoring of human psychodynamics in a more cost-effective way, i.e. less than US$50.

Several novel attributes are envisaged in the development process of the GSR system that made it different from and unique as compared to the existing alternatives. The attributes are as follows: (i) use of reproductive sensor-system fabrication process, (ii) use of flexible-substrate for hosting the system as proof of concept, (iii) use of miniaturized microcontroller, i.e. ATTiny85, (iv) deployment of energy-efficient passive electrical circuitry for noise filtering, (v) possible use case scenario of using CR2032 coin battery for provisioning powering up the system, (vi) provision of incorporation of internet of things (IoT)-cloud integration in existing version while fixing related APIs and (vii) incorporation of heterogeneous software-based solutions to validate and monitor the GSR output such as MakerPlot, Arduino IDE, Fritzing and MIT App Inventor 2.

This paper is a revised version R1 of the earlier reviewed paper. The proposed paper provides novel knowledge about the flexible sensor system development for GSR monitoring under IoT-based environment for smart e-healthcare.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

This paper presents a critical review of studies which map the urban environment using continuous physiological data collection. A conceptual model is consequently presented for mitigating urban stress at the city and the user level.

The study reviews relevant publications, examining the tools used for data collection and the methods used for data analysis and data fusion. The relationship between urban features and physiological responses is also examined.

The review showed that the continuous monitoring of physiological data in the urban environment can be used for location-aware stress detection and urban emotion mapping. The combination of physiological and contextual data helps researchers understand how the urban environment affects the human body. The review indicated a relationship between some urban features (green, land use, traffic, isovist parameters) and physiological responses, though more research is needed to solidify the existence of the identified links. The review also identified many theoretical, methodological and practical issues which hinder further research in this area.

While there is large potential in this field, there has been no review of studies which map continuously physiological data in the urban environment. This study covers this gap and introduces a novel conceptual model for mitigating urban stress.

Understanding how health status and physiological factors affect performance is a daunting task. This chapter will discuss physiological, behavioral, and psychological factors that influence or determine the capacity to fight, and will consider metrics that can be used to measure their status. The premise of this discussion is that there is a set of physiological and psychological factors that intimately affect performance and that the relative contribution of these variables is individually unique. These factors can be identified and assessed, and are amenable to modification. A fuller understanding of these variables can lead the effort to maintain and improve performance in the adverse and challenging environments of military operations.

Examines the seventeenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

To meet the increasing needs for ubiquitous healthcare, a mobile phone‐based system for monitoring multiple vital signs is under development. In this paper, design and implementation of the system architecture are described. The hierarchy of this system comprises three layers, which respectively handle multiple vital signs sensing, data/command communication via either wireless or wired means, and healthcare management. The fundamental basis of the sensing layer is a wearable cordless sensor device for monitoring vital signs without discomfort to the user during daily activities. The data communication layer performs bi‐directional information exchange between the sensing layer and the management layer. The uppermost management layer conducts data mining and analysis for risk factors assessment and healthcare. Overall considerations of implementation method and prototype fabrication are outlined. Finally, applicability to a variety of real‐world situations, and provision of customizable solutions not only for home healthcare but also for other vital signs‐related domains (such as emergency rescue and safety guarantee) are discussed. Three of the most promising applications based upon this system are described.

The purpose of this paper was to investigate the physiological cost of concrete construction activities.

Five concrete construction workers were recruited. The workers’ three-week heart rate (HR) data were collected in summer and autumn. In this paper, several HR indexes were used to investigate the physiological cost of work in concrete construction trades, including average working HR, relative HR and ratio of working HR to resting HR.

This paper measures how absolute and relative HRs vary throughout a workday and how working HR compares to resting HR for individual workers.

Field observations are usually extremely difficult as researchers need to overcome a number of barriers, including employers’ resistance to perceived additional liabilities, employees’ fear that their level of activity will be reported to managers and many other practical and technical difficulties. As these challenges increase exponentially with the number of employers, subjects and sites, this study was limited to a small number of subjects all working for the same employer on the same jobsite. Still, challenges are often unpredictable and lessons learned from this study are expected to guide both our and other researchers’ continuation of this work.

The time effect on the physiological cost of work has not been considered in previous studies. Thus, this study is noteworthy owing to the depth of the data collected rather than the breadth of the data.