Wearable Sensors for Monitoring the Physiological and Biochemical Profile of the Athlete

Athletes are continually seeking new technologies and therapies to gain a competitive edge to maximize their health and performance. Athletes have gravitated toward the use of wearable sensors to monitor their training and recovery. Wearable technologies currently utilized by sports teams monitor both the internal and external workload of athletes. However, there remains an unmet medical need by the sports community to gain further insight into the internal workload of the athlete to tailor recovery protocols to each athlete. The ability to monitor biomarkers from saliva or sweat in a noninvasive and continuous manner remain the next technological gap for sports medical personnel to tailor hydration and recovery protocols per the athlete. The emergence of flexible and stretchable electronics coupled with the ability to quantify biochemical analytes and physiological parameters have enabled the detection of key markers indicative of performance and stress, as reviewed in this paper

State of the art of audio- and video based solutions for AAL

Working Group 3. Audio- and Video-based AAL ApplicationsIt is a matter of fact that Europe is facing more and more crucial challenges regarding health and social care due to the demographic change and the current economic context. The recent COVID-19 pandemic has stressed this situation even further, thus highlighting the need for taking action. Active and Assisted Living (AAL) technologies come as a viable approach to help facing these challenges, thanks to the high potential they have in enabling remote care and support. Broadly speaking, AAL can be referred to as the use of innovative and advanced Information and Communication Technologies to create supportive, inclusive and empowering applications and environments that enable older, impaired or frail people to live independently and stay active longer in society. AAL capitalizes on the growing pervasiveness and effectiveness of sensing and computing facilities to supply the persons in need with smart assistance, by responding to their necessities of autonomy, independence, comfort, security and safety. The application scenarios addressed by AAL are complex, due to the inherent heterogeneity of the end-user population, their living arrangements, and their physical conditions or impairment. Despite aiming at diverse goals, AAL systems should share some common characteristics. They are designed to provide support in daily life in an invisible, unobtrusive and user-friendly manner. Moreover, they are conceived to be intelligent, to be able to learn and adapt to the requirements and requests of the assisted people, and to synchronise with their specific needs. Nevertheless, to ensure the uptake of AAL in society, potential users must be willing to use AAL applications and to integrate them in their daily environments and lives. In this respect, video- and audio-based AAL applications have several advantages, in terms of unobtrusiveness and information richness. Indeed, cameras and microphones are far less obtrusive with respect to the hindrance other wearable sensors may cause to one’s activities. In addition, a single camera placed in a room can record most of the activities performed in the room, thus replacing many other non-visual sensors. Currently, video-based applications are effective in recognising and monitoring the activities, the movements, and the overall conditions of the assisted individuals as well as to assess their vital parameters (e.g., heart rate, respiratory rate). Similarly, audio sensors have the potential to become one of the most important modalities for interaction with AAL systems, as they can have a large range of sensing, do not require physical presence at a particular location and are physically intangible. Moreover, relevant information about individuals’ activities and health status can derive from processing audio signals (e.g., speech recordings). Nevertheless, as the other side of the coin, cameras and microphones are often perceived as the most intrusive technologies from the viewpoint of the privacy of the monitored individuals. This is due to the richness of the information these technologies convey and the intimate setting where they may be deployed. Solutions able to ensure privacy preservation by context and by design, as well as to ensure high legal and ethical standards are in high demand. After the review of the current state of play and the discussion in GoodBrother, we may claim that the first solutions in this direction are starting to appear in the literature. A multidisciplinary 4 debate among experts and stakeholders is paving the way towards AAL ensuring ergonomics, usability, acceptance and privacy preservation. The DIANA, PAAL, and VisuAAL projects are examples of this fresh approach. This report provides the reader with a review of the most recent advances in audio- and video-based monitoring technologies for AAL. It has been drafted as a collective effort of WG3 to supply an introduction to AAL, its evolution over time and its main functional and technological underpinnings. In this respect, the report contributes to the field with the outline of a new generation of ethical-aware AAL technologies and a proposal for a novel comprehensive taxonomy of AAL systems and applications. Moreover, the report allows non-technical readers to gather an overview of the main components of an AAL system and how these function and interact with the end-users. The report illustrates the state of the art of the most successful AAL applications and functions based on audio and video data, namely (i) lifelogging and self-monitoring, (ii) remote monitoring of vital signs, (iii) emotional state recognition, (iv) food intake monitoring, activity and behaviour recognition, (v) activity and personal assistance, (vi) gesture recognition, (vii) fall detection and prevention, (viii) mobility assessment and frailty recognition, and (ix) cognitive and motor rehabilitation. For these application scenarios, the report illustrates the state of play in terms of scientific advances, available products and research project. The open challenges are also highlighted. The report ends with an overview of the challenges, the hindrances and the opportunities posed by the uptake in real world settings of AAL technologies. In this respect, the report illustrates the current procedural and technological approaches to cope with acceptability, usability and trust in the AAL technology, by surveying strategies and approaches to co-design, to privacy preservation in video and audio data, to transparency and explainability in data processing, and to data transmission and communication. User acceptance and ethical considerations are also debated. Finally, the potentials coming from the silver economy are overviewed.publishedVersio

Human performance in rail: determining the potential of physiological data from wearable technologies

This research focuses on how personal data from wearable physiological measures can be used to assess the Mental Workload (MWL) of staff in the rail industry. Automation technologies are being implemented in the rail industry to improve operational performance and capacity. These new technologies are changing the role of staff. This research considers how temporal physiological data present an opportunity to supplement existing workload assessment methods to measure the impact of these technology changes. The research explores how wearable physiological measures could be applied in live operations to collect real-time data with minimal task interference. Whilst the research focuses on railway signallers, the research has implications for other roles in the rail industry and other industries. The research included three studies and two literature reviews. The initial industry interview study identified the benefit of more continuous data to assess human performance, including successful performance. A detailed review of candidate technologies was then performed solely on physiological measures to extend the knowledge in this area. To assess the potential of physiological measures to provide this continuous data, a simulation study of railway signalling tasks was conducted with an Electrodermal Activity (EDA) wrist strap for alertness and stress and a Heart Rate Variability (HRV) chest strap for uncertainty and increased MWL. The limited application of these measures in rail research provided a suitable research gap for the research to pursue. The simulation study found physiological data provided visibility of individuals’ personal experience of workload. The interplay of EDA, HRV, task demand and subjective workload over time were visible in the storyboard for each participant. The simulation study provided two key contributions to the thesis. Firstly, EDA identified moments in workload during the task, indicating moments of realisation, and periods of uncertainty, or strain due to time pressure. Such data could be used in staff debriefs to better understand their workload, and tailor training. Secondly, average HRV had a strong negative correlation with average subjective workload. HRV could provide a real time indicator of workload and provide visibility of staff effort to managers. The final study was an interview and survey study of staff perspectives on the potential use of these measures. This study replaced a live trial which could not proceed during COVID-19 related restrictions. The study found wearable devices suit use in the live operational environment, with the wrist strap rated the most suitable due to low distraction. Trust emerged as a key factor for staff to accept the use of wearables, particularly if named data is shared. Tangible benefits that lead to improvement in operations was identified as one way to build this trust. An additional contribution of the thesis, drawing on all studies and literature reviews, was to propose a new theoretical perspective on MWL, based on physiological data. A Novelty of Events and Autonomic State (NEAS) model is proposed as a preliminary conceptualisation. It shows how individuals may vary in the impact workload has on their performance and how physiological data may be used to identify this. The concept of Novelty of Events includes aspects of tasks that an individual has not performed before, including those introduced by new technology or procedures. The NEAS model suggests how support in the form of tailored training, or shift breaks, could be used to support improved human performance. Following on from this thesis, a priority for further empirical work would be to trial EDA using a wrist strap that uses a repeated measures approach to determine to what extent individual physiological data changes over time

Human performance in rail: determining the potential of physiological data from wearable technologies

This research focuses on how personal data from wearable physiological measures can be used to assess the Mental Workload (MWL) of staff in the rail industry. Automation technologies are being implemented in the rail industry to improve operational performance and capacity. These new technologies are changing the role of staff. This research considers how temporal physiological data present an opportunity to supplement existing workload assessment methods to measure the impact of these technology changes. The research explores how wearable physiological measures could be applied in live operations to collect real-time data with minimal task interference. Whilst the research focuses on railway signallers, the research has implications for other roles in the rail industry and other industries. The research included three studies and two literature reviews. The initial industry interview study identified the benefit of more continuous data to assess human performance, including successful performance. A detailed review of candidate technologies was then performed solely on physiological measures to extend the knowledge in this area. To assess the potential of physiological measures to provide this continuous data, a simulation study of railway signalling tasks was conducted with an Electrodermal Activity (EDA) wrist strap for alertness and stress and a Heart Rate Variability (HRV) chest strap for uncertainty and increased MWL. The limited application of these measures in rail research provided a suitable research gap for the research to pursue. The simulation study found physiological data provided visibility of individuals’ personal experience of workload. The interplay of EDA, HRV, task demand and subjective workload over time were visible in the storyboard for each participant. The simulation study provided two key contributions to the thesis. Firstly, EDA identified moments in workload during the task, indicating moments of realisation, and periods of uncertainty, or strain due to time pressure. Such data could be used in staff debriefs to better understand their workload, and tailor training. Secondly, average HRV had a strong negative correlation with average subjective workload. HRV could provide a real time indicator of workload and provide visibility of staff effort to managers. The final study was an interview and survey study of staff perspectives on the potential use of these measures. This study replaced a live trial which could not proceed during COVID-19 related restrictions. The study found wearable devices suit use in the live operational environment, with the wrist strap rated the most suitable due to low distraction. Trust emerged as a key factor for staff to accept the use of wearables, particularly if named data is shared. Tangible benefits that lead to improvement in operations was identified as one way to build this trust. An additional contribution of the thesis, drawing on all studies and literature reviews, was to propose a new theoretical perspective on MWL, based on physiological data. A Novelty of Events and Autonomic State (NEAS) model is proposed as a preliminary conceptualisation. It shows how individuals may vary in the impact workload has on their performance and how physiological data may be used to identify this. The concept of Novelty of Events includes aspects of tasks that an individual has not performed before, including those introduced by new technology or procedures. The NEAS model suggests how support in the form of tailored training, or shift breaks, could be used to support improved human performance. Following on from this thesis, a priority for further empirical work would be to trial EDA using a wrist strap that uses a repeated measures approach to determine to what extent individual physiological data changes over time

Industrial Applications: New Solutions for the New Era

This book reprints articles from the Special Issue "Industrial Applications: New Solutions for the New Age" published online in the open-access journal Machines (ISSN 2075-1702). This book consists of twelve published articles. This special edition belongs to the "Mechatronic and Intelligent Machines" section

Aerospace medicine and biology: A continuing bibliography with indexes, supplement 239, December 1982

This bibliography lists 318 reports, articles and other documents introduced into the NASA scientific and technical information system in November 1982

Non-Intrusive Subscriber Authentication for Next Generation Mobile Communication Systems

Merged with duplicate record 10026.1/753 on 14.03.2017 by CS (TIS)The last decade has witnessed massive growth in both the technological development, and the consumer adoption of mobile devices such as mobile handsets and PDAs. The recent introduction of wideband mobile networks has enabled the deployment of new services with access to traditionally well protected personal data, such as banking details or medical records. Secure user access to this data has however remained a function of the mobile device's authentication system, which is only protected from masquerade abuse by the traditional PIN, originally designed to protect against telephony abuse. This thesis presents novel research in relation to advanced subscriber authentication for mobile devices. The research began by assessing the threat of masquerade attacks on such devices by way of a survey of end users. This revealed that the current methods of mobile authentication remain extensively unused, leaving terminals highly vulnerable to masquerade attack. Further investigation revealed that, in the context of the more advanced wideband enabled services, users are receptive to many advanced authentication techniques and principles, including the discipline of biometrics which naturally lends itself to the area of advanced subscriber based authentication. To address the requirement for a more personal authentication capable of being applied in a continuous context, a novel non-intrusive biometric authentication technique was conceived, drawn from the discrete disciplines of biometrics and Auditory Evoked Responses. The technique forms a hybrid multi-modal biometric where variations in the behavioural stimulus of the human voice (due to the propagation effects of acoustic waves within the human head), are used to verify the identity o f a user. The resulting approach is known as the Head Authentication Technique (HAT). Evaluation of the HAT authentication process is realised in two stages. Firstly, the generic authentication procedures of registration and verification are automated within a prototype implementation. Secondly, a HAT demonstrator is used to evaluate the authentication process through a series of experimental trials involving a representative user community. The results from the trials confirm that multiple HAT samples from the same user exhibit a high degree of correlation, yet samples between users exhibit a high degree of discrepancy. Statistical analysis of the prototypes performance realised early system error rates of; FNMR = 6% and FMR = 0.025%. The results clearly demonstrate the authentication capabilities of this novel biometric approach and the contribution this new work can make to the protection of subscriber data in next generation mobile networks.Orange Personal Communication Services Lt

Semantic models of scenes and objects for service and industrial robotics

What may seem straightforward for the human perception system is still challenging for robots. Automatically segmenting the elements with highest relevance or salience, i.e. the semantics, is non-trivial given the high level of variability in the world and the limits of vision sensors. This stands up when multiple ambiguous sources of information are available, which is the case when dealing with moving robots. This thesis leverages on the availability of contextual cues and multiple points of view to make the segmentation task easier. Four robotic applications will be presented, two designed for service robotics and two for an industrial context. Semantic models of indoor environments will be built enriching geometric reconstructions with semantic information about objects, structural elements and humans. Our approach leverages on the importance of context, the availability of multiple source of information, as well as multiple view points showing with extensive experiments on several datasets that these are all crucial elements to boost state-of-the-art performances. Furthermore, moving to applications with robots analyzing object surfaces instead of their surroundings, semantic models of Carbon Fiber Reinforced Polymers will be built augmenting geometric models with accurate measurements of superficial fiber orientations, and inner defects invisible to the human-eye. We succeeded in reaching an industrial grade accuracy making these models useful for autonomous quality inspection and process optimization. In all applications, special attention will be paid towards fast methods suitable for real robots like the two prototypes presented in this thesis

State of the Art of Audio- and Video-Based Solutions for AAL

It is a matter of fact that Europe is facing more and more crucial challenges regarding health and social care due to the demographic change and the current economic context. The recent COVID-19 pandemic has stressed this situation even further, thus highlighting the need for taking action. Active and Assisted Living technologies come as a viable approach to help facing these challenges, thanks to the high potential they have in enabling remote care and support. Broadly speaking, AAL can be referred to as the use of innovative and advanced Information and Communication Technologies to create supportive, inclusive and empowering applications and environments that enable older, impaired or frail people to live independently and stay active longer in society. AAL capitalizes on the growing pervasiveness and effectiveness of sensing and computing facilities to supply the persons in need with smart assistance, by responding to their necessities of autonomy, independence, comfort, security and safety. The application scenarios addressed by AAL are complex, due to the inherent heterogeneity of the end-user population, their living arrangements, and their physical conditions or impairment. Despite aiming at diverse goals, AAL systems should share some common characteristics. They are designed to provide support in daily life in an invisible, unobtrusive and user-friendly manner. Moreover, they are conceived to be intelligent, to be able to learn and adapt to the requirements and requests of the assisted people, and to synchronise with their specific needs. Nevertheless, to ensure the uptake of AAL in society, potential users must be willing to use AAL applications and to integrate them in their daily environments and lives. In this respect, video- and audio-based AAL applications have several advantages, in terms of unobtrusiveness and information richness. Indeed, cameras and microphones are far less obtrusive with respect to the hindrance other wearable sensors may cause to one’s activities. In addition, a single camera placed in a room can record most of the activities performed in the room, thus replacing many other non-visual sensors. Currently, video-based applications are effective in recognising and monitoring the activities, the movements, and the overall conditions of the assisted individuals as well as to assess their vital parameters. Similarly, audio sensors have the potential to become one of the most important modalities for interaction with AAL systems, as they can have a large range of sensing, do not require physical presence at a particular location and are physically intangible. Moreover, relevant information about individuals’ activities and health status can derive from processing audio signals. Nevertheless, as the other side of the coin, cameras and microphones are often perceived as the most intrusive technologies from the viewpoint of the privacy of the monitored individuals. This is due to the richness of the information these technologies convey and the intimate setting where they may be deployed. Solutions able to ensure privacy preservation by context and by design, as well as to ensure high legal and ethical standards are in high demand. After the review of the current state of play and the discussion in GoodBrother, we may claim that the first solutions in this direction are starting to appear in the literature. A multidisciplinary debate among experts and stakeholders is paving the way towards AAL ensuring ergonomics, usability, acceptance and privacy preservation. The DIANA, PAAL, and VisuAAL projects are examples of this fresh approach. This report provides the reader with a review of the most recent advances in audio- and video-based monitoring technologies for AAL. It has been drafted as a collective effort of WG3 to supply an introduction to AAL, its evolution over time and its main functional and technological underpinnings. In this respect, the report contributes to the field with the outline of a new generation of ethical-aware AAL technologies and a proposal for a novel comprehensive taxonomy of AAL systems and applications. Moreover, the report allows non-technical readers to gather an overview of the main components of an AAL system and how these function and interact with the end-users. The report illustrates the state of the art of the most successful AAL applications and functions based on audio and video data, namely lifelogging and self-monitoring, remote monitoring of vital signs, emotional state recognition, food intake monitoring, activity and behaviour recognition, activity and personal assistance, gesture recognition, fall detection and prevention, mobility assessment and frailty recognition, and cognitive and motor rehabilitation. For these application scenarios, the report illustrates the state of play in terms of scientific advances, available products and research project. The open challenges are also highlighted. The report ends with an overview of the challenges, the hindrances and the opportunities posed by the uptake in real world settings of AAL technologies. In this respect, the report illustrates the current procedural and technological approaches to cope with acceptability, usability and trust in the AAL technology, by surveying strategies and approaches to co-design, to privacy preservation in video and audio data, to transparency and explainability in data processing, and to data transmission and communication. User acceptance and ethical considerations are also debated. Finally, the potentials coming from the silver economy are overviewed

Thermal protection properties of aerogel-coated Kevlar woven fabrics

This paper investigated the thermal properties of aerogel-coated Kevlar fabrics under both the ambient temperature and high temperature with laser radiation. It is found that the aerogels combined with a Kevlar fabric contribute to a higher thermal insulation value. Under laser radiation with high temperature, the aerogel content plays a vital role on the surface temperature of the fabrics. At laser radiations with pixel time 330 μs, the surface temperatures of the aerogel coated Kevlar fabrics are 400-440°C lower than that of the uncoated fabric. Results also show that the fabric temperature is directly proportional to pixel time. It can be concluded that the Kevlar fabrics coated with silica aerogel provides better thermal protection under high temperature