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Smart, wearables devices on a miniature scale are becoming increasingly widely available, typically in the form of smart watches and other connected devices. Consequently, devices to assist in measurements such as electroencephalography (EEG), electrocardiogram (ECG), electromyography (EMG), blood pressure (BP), photoplethysmography (PPG), heart rhythm, respiration rate, apnoea, and motion detection are becoming more available, and play a significant role in healthcare monitoring. The industry is placing great emphasis on making these devices and technologies available on smart devices such as phones and watches. Such measurements are clinically and scientifically useful for real-time monitoring, long-term care, and diagnosis and therapeutic techniques. However, a pertaining issue is that recorded data are usually noisy, contain many artefacts, and are affected by external factors such as movements and physical conditions. In order to obtain accurate and meaningful indicators, the signal has to be processed and conditioned such that the measurements are accurate and free from noise and disturbances. In this context, many researchers have utilized recent technological advances in wearable sensors and signal processing to develop smart and accurate wearable devices for clinical applications. The processing and analysis of physiological signals is a key issue for these smart wearable devices. Consequently, ongoing work in this field of study includes research on filtration, quality checking, signal transformation and decomposition, feature extraction and, most recently, machine learning-based methods.
Technology: general issues --- History of engineering & technology --- automated dietary monitoring --- eating detection --- eating timing error analysis --- biomedical signal processing --- smart eyeglasses --- wearable health monitoring --- artificial neural network --- joint moment prediction --- extreme learning machine --- Hill muscle model --- online input variables --- Review --- ECG --- Signal Processing --- Machine Learning --- Cardiovascular Disease --- Anomaly Detection --- photoplethysmography --- motion artifact --- independent component analysis --- multi-wavelength --- continuous arterial blood pressure --- systolic blood pressure --- diastolic blood pressure --- deep convolutional autoencoder --- genetic algorithm --- electrocardiography --- vectorcardiography --- myocardial infarction --- long short-term memory --- spline --- multilayer perceptron --- pain detection --- stress detection --- wearable sensor --- physiological signals --- behavioral signals --- non-invasive system --- hemodynamics --- arterial blood pressure --- central venous pressure --- pulmonary arterial pressure --- intracranial pressure --- heart rate measurement --- remote HR --- remote PPG --- remote BCG --- blind source separation --- drowsiness detection --- EEG --- frequency-domain features --- multicriteria optimization --- machine learning --- automated dietary monitoring --- eating detection --- eating timing error analysis --- biomedical signal processing --- smart eyeglasses --- wearable health monitoring --- artificial neural network --- joint moment prediction --- extreme learning machine --- Hill muscle model --- online input variables --- Review --- ECG --- Signal Processing --- Machine Learning --- Cardiovascular Disease --- Anomaly Detection --- photoplethysmography --- motion artifact --- independent component analysis --- multi-wavelength --- continuous arterial blood pressure --- systolic blood pressure --- diastolic blood pressure --- deep convolutional autoencoder --- genetic algorithm --- electrocardiography --- vectorcardiography --- myocardial infarction --- long short-term memory --- spline --- multilayer perceptron --- pain detection --- stress detection --- wearable sensor --- physiological signals --- behavioral signals --- non-invasive system --- hemodynamics --- arterial blood pressure --- central venous pressure --- pulmonary arterial pressure --- intracranial pressure --- heart rate measurement --- remote HR --- remote PPG --- remote BCG --- blind source separation --- drowsiness detection --- EEG --- frequency-domain features --- multicriteria optimization --- machine learning
Choose an application
Smart, wearables devices on a miniature scale are becoming increasingly widely available, typically in the form of smart watches and other connected devices. Consequently, devices to assist in measurements such as electroencephalography (EEG), electrocardiogram (ECG), electromyography (EMG), blood pressure (BP), photoplethysmography (PPG), heart rhythm, respiration rate, apnoea, and motion detection are becoming more available, and play a significant role in healthcare monitoring. The industry is placing great emphasis on making these devices and technologies available on smart devices such as phones and watches. Such measurements are clinically and scientifically useful for real-time monitoring, long-term care, and diagnosis and therapeutic techniques. However, a pertaining issue is that recorded data are usually noisy, contain many artefacts, and are affected by external factors such as movements and physical conditions. In order to obtain accurate and meaningful indicators, the signal has to be processed and conditioned such that the measurements are accurate and free from noise and disturbances. In this context, many researchers have utilized recent technological advances in wearable sensors and signal processing to develop smart and accurate wearable devices for clinical applications. The processing and analysis of physiological signals is a key issue for these smart wearable devices. Consequently, ongoing work in this field of study includes research on filtration, quality checking, signal transformation and decomposition, feature extraction and, most recently, machine learning-based methods.
Technology: general issues --- History of engineering & technology --- automated dietary monitoring --- eating detection --- eating timing error analysis --- biomedical signal processing --- smart eyeglasses --- wearable health monitoring --- artificial neural network --- joint moment prediction --- extreme learning machine --- Hill muscle model --- online input variables --- Review --- ECG --- Signal Processing --- Machine Learning --- Cardiovascular Disease --- Anomaly Detection --- photoplethysmography --- motion artifact --- independent component analysis --- multi-wavelength --- continuous arterial blood pressure --- systolic blood pressure --- diastolic blood pressure --- deep convolutional autoencoder --- genetic algorithm --- electrocardiography --- vectorcardiography --- myocardial infarction --- long short-term memory --- spline --- multilayer perceptron --- pain detection --- stress detection --- wearable sensor --- physiological signals --- behavioral signals --- non-invasive system --- hemodynamics --- arterial blood pressure --- central venous pressure --- pulmonary arterial pressure --- intracranial pressure --- heart rate measurement --- remote HR --- remote PPG --- remote BCG --- blind source separation --- drowsiness detection --- EEG --- frequency-domain features --- multicriteria optimization --- machine learning --- n/a
Choose an application
Smart, wearables devices on a miniature scale are becoming increasingly widely available, typically in the form of smart watches and other connected devices. Consequently, devices to assist in measurements such as electroencephalography (EEG), electrocardiogram (ECG), electromyography (EMG), blood pressure (BP), photoplethysmography (PPG), heart rhythm, respiration rate, apnoea, and motion detection are becoming more available, and play a significant role in healthcare monitoring. The industry is placing great emphasis on making these devices and technologies available on smart devices such as phones and watches. Such measurements are clinically and scientifically useful for real-time monitoring, long-term care, and diagnosis and therapeutic techniques. However, a pertaining issue is that recorded data are usually noisy, contain many artefacts, and are affected by external factors such as movements and physical conditions. In order to obtain accurate and meaningful indicators, the signal has to be processed and conditioned such that the measurements are accurate and free from noise and disturbances. In this context, many researchers have utilized recent technological advances in wearable sensors and signal processing to develop smart and accurate wearable devices for clinical applications. The processing and analysis of physiological signals is a key issue for these smart wearable devices. Consequently, ongoing work in this field of study includes research on filtration, quality checking, signal transformation and decomposition, feature extraction and, most recently, machine learning-based methods.
automated dietary monitoring --- eating detection --- eating timing error analysis --- biomedical signal processing --- smart eyeglasses --- wearable health monitoring --- artificial neural network --- joint moment prediction --- extreme learning machine --- Hill muscle model --- online input variables --- Review --- ECG --- Signal Processing --- Machine Learning --- Cardiovascular Disease --- Anomaly Detection --- photoplethysmography --- motion artifact --- independent component analysis --- multi-wavelength --- continuous arterial blood pressure --- systolic blood pressure --- diastolic blood pressure --- deep convolutional autoencoder --- genetic algorithm --- electrocardiography --- vectorcardiography --- myocardial infarction --- long short-term memory --- spline --- multilayer perceptron --- pain detection --- stress detection --- wearable sensor --- physiological signals --- behavioral signals --- non-invasive system --- hemodynamics --- arterial blood pressure --- central venous pressure --- pulmonary arterial pressure --- intracranial pressure --- heart rate measurement --- remote HR --- remote PPG --- remote BCG --- blind source separation --- drowsiness detection --- EEG --- frequency-domain features --- multicriteria optimization --- machine learning --- n/a
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Although the design and management of manufacturing systems have been explored in the literature for many years now, they still remain topical problems in the current scientific research. The changing market trends, globalization, the constant pressure to reduce production costs, and technical and technological progress make it necessary to search for new manufacturing methods and ways of organizing them, and to modify manufacturing system design paradigms. This book presents current research in different areas connected with the design and management of manufacturing systems and covers such subject areas as: methods supporting the design of manufacturing systems, methods of improving maintenance processes in companies, the design and improvement of manufacturing processes, the control of production processes in modern manufacturing systems production methods and techniques used in modern manufacturing systems and environmental aspects of production and their impact on the design and management of manufacturing systems. The wide range of research findings reported in this book confirms that the design of manufacturing systems is a complex problem and that the achievement of goals set for modern manufacturing systems requires interdisciplinary knowledge and the simultaneous design of the product, process and system, as well as the knowledge of modern manufacturing and organizational methods and techniques.
Technology: general issues --- efficiency --- production processes --- machinery --- production maintenance --- logistic regression --- production process capability --- product quality --- monitoring of production processes --- process variables --- production planning optimization --- closed-loop green supply chain --- government subsidy --- stackelberg game --- re-manufacturing --- polish manufacturing company --- additive manufacturing technology --- questionnaire survey --- empirical research --- semi-Markov model --- Markov model --- empirical data distribution --- readiness --- production machines --- 8 disciplines method --- custom cable assemblies --- defects --- functional test --- customer satisfaction --- hard computing approach --- p-median problem --- generalized cell formation --- assembly-line balancing --- multi-objective optimization --- simulated annealing --- multilayer network --- production process design --- unit and small-lot production design for manufacturability --- fuzzy logic --- eco-design --- end-of-life treatment --- recycling --- solar power plant --- wind power plant --- life cycle analysis --- advanced industrial engineering --- modelling and simulation --- factory of the future --- smart factory --- manufacturing systems --- production planning optimisation --- decision support --- additive manufacturing --- fused filament fabrication --- CFR-PEEK --- optimal process parameters --- manufacturing performance --- multiple response optimization --- reconfigurable manufacturing system --- Petri net --- deadlock --- siphon --- supervisory controller --- reengineering --- simulation --- productivity --- batch processors --- real-time control --- dispatching --- wafer fabrication --- semiconductor manufacturing --- system-wide performance --- robust scheduling --- predictive scheduling --- machine failure --- failure prediction --- constraint programming --- constraint satisfaction problem --- cost estimation --- decision support systems --- multicriteria optimization --- production planning --- project management --- layout --- 3D printing devices --- methods of optimizing the arrangement of workstations --- car tire production process --- rubber industry --- environmental impact --- Life Cycle Assessment --- entire product lifecycle --- decision-making process --- lean maintenance --- effectiveness --- decision trees --- rough set theory --- n/a
Choose an application
Although the design and management of manufacturing systems have been explored in the literature for many years now, they still remain topical problems in the current scientific research. The changing market trends, globalization, the constant pressure to reduce production costs, and technical and technological progress make it necessary to search for new manufacturing methods and ways of organizing them, and to modify manufacturing system design paradigms. This book presents current research in different areas connected with the design and management of manufacturing systems and covers such subject areas as: methods supporting the design of manufacturing systems, methods of improving maintenance processes in companies, the design and improvement of manufacturing processes, the control of production processes in modern manufacturing systems production methods and techniques used in modern manufacturing systems and environmental aspects of production and their impact on the design and management of manufacturing systems. The wide range of research findings reported in this book confirms that the design of manufacturing systems is a complex problem and that the achievement of goals set for modern manufacturing systems requires interdisciplinary knowledge and the simultaneous design of the product, process and system, as well as the knowledge of modern manufacturing and organizational methods and techniques.
efficiency --- production processes --- machinery --- production maintenance --- logistic regression --- production process capability --- product quality --- monitoring of production processes --- process variables --- production planning optimization --- closed-loop green supply chain --- government subsidy --- stackelberg game --- re-manufacturing --- polish manufacturing company --- additive manufacturing technology --- questionnaire survey --- empirical research --- semi-Markov model --- Markov model --- empirical data distribution --- readiness --- production machines --- 8 disciplines method --- custom cable assemblies --- defects --- functional test --- customer satisfaction --- hard computing approach --- p-median problem --- generalized cell formation --- assembly-line balancing --- multi-objective optimization --- simulated annealing --- multilayer network --- production process design --- unit and small-lot production design for manufacturability --- fuzzy logic --- eco-design --- end-of-life treatment --- recycling --- solar power plant --- wind power plant --- life cycle analysis --- advanced industrial engineering --- modelling and simulation --- factory of the future --- smart factory --- manufacturing systems --- production planning optimisation --- decision support --- additive manufacturing --- fused filament fabrication --- CFR-PEEK --- optimal process parameters --- manufacturing performance --- multiple response optimization --- reconfigurable manufacturing system --- Petri net --- deadlock --- siphon --- supervisory controller --- reengineering --- simulation --- productivity --- batch processors --- real-time control --- dispatching --- wafer fabrication --- semiconductor manufacturing --- system-wide performance --- robust scheduling --- predictive scheduling --- machine failure --- failure prediction --- constraint programming --- constraint satisfaction problem --- cost estimation --- decision support systems --- multicriteria optimization --- production planning --- project management --- layout --- 3D printing devices --- methods of optimizing the arrangement of workstations --- car tire production process --- rubber industry --- environmental impact --- Life Cycle Assessment --- entire product lifecycle --- decision-making process --- lean maintenance --- effectiveness --- decision trees --- rough set theory --- n/a
Choose an application
Although the design and management of manufacturing systems have been explored in the literature for many years now, they still remain topical problems in the current scientific research. The changing market trends, globalization, the constant pressure to reduce production costs, and technical and technological progress make it necessary to search for new manufacturing methods and ways of organizing them, and to modify manufacturing system design paradigms. This book presents current research in different areas connected with the design and management of manufacturing systems and covers such subject areas as: methods supporting the design of manufacturing systems, methods of improving maintenance processes in companies, the design and improvement of manufacturing processes, the control of production processes in modern manufacturing systems production methods and techniques used in modern manufacturing systems and environmental aspects of production and their impact on the design and management of manufacturing systems. The wide range of research findings reported in this book confirms that the design of manufacturing systems is a complex problem and that the achievement of goals set for modern manufacturing systems requires interdisciplinary knowledge and the simultaneous design of the product, process and system, as well as the knowledge of modern manufacturing and organizational methods and techniques.
Technology: general issues --- efficiency --- production processes --- machinery --- production maintenance --- logistic regression --- production process capability --- product quality --- monitoring of production processes --- process variables --- production planning optimization --- closed-loop green supply chain --- government subsidy --- stackelberg game --- re-manufacturing --- polish manufacturing company --- additive manufacturing technology --- questionnaire survey --- empirical research --- semi-Markov model --- Markov model --- empirical data distribution --- readiness --- production machines --- 8 disciplines method --- custom cable assemblies --- defects --- functional test --- customer satisfaction --- hard computing approach --- p-median problem --- generalized cell formation --- assembly-line balancing --- multi-objective optimization --- simulated annealing --- multilayer network --- production process design --- unit and small-lot production design for manufacturability --- fuzzy logic --- eco-design --- end-of-life treatment --- recycling --- solar power plant --- wind power plant --- life cycle analysis --- advanced industrial engineering --- modelling and simulation --- factory of the future --- smart factory --- manufacturing systems --- production planning optimisation --- decision support --- additive manufacturing --- fused filament fabrication --- CFR-PEEK --- optimal process parameters --- manufacturing performance --- multiple response optimization --- reconfigurable manufacturing system --- Petri net --- deadlock --- siphon --- supervisory controller --- reengineering --- simulation --- productivity --- batch processors --- real-time control --- dispatching --- wafer fabrication --- semiconductor manufacturing --- system-wide performance --- robust scheduling --- predictive scheduling --- machine failure --- failure prediction --- constraint programming --- constraint satisfaction problem --- cost estimation --- decision support systems --- multicriteria optimization --- production planning --- project management --- layout --- 3D printing devices --- methods of optimizing the arrangement of workstations --- car tire production process --- rubber industry --- environmental impact --- Life Cycle Assessment --- entire product lifecycle --- decision-making process --- lean maintenance --- effectiveness --- decision trees --- rough set theory --- efficiency --- production processes --- machinery --- production maintenance --- logistic regression --- production process capability --- product quality --- monitoring of production processes --- process variables --- production planning optimization --- closed-loop green supply chain --- government subsidy --- stackelberg game --- re-manufacturing --- polish manufacturing company --- additive manufacturing technology --- questionnaire survey --- empirical research --- semi-Markov model --- Markov model --- empirical data distribution --- readiness --- production machines --- 8 disciplines method --- custom cable assemblies --- defects --- functional test --- customer satisfaction --- hard computing approach --- p-median problem --- generalized cell formation --- assembly-line balancing --- multi-objective optimization --- simulated annealing --- multilayer network --- production process design --- unit and small-lot production design for manufacturability --- fuzzy logic --- eco-design --- end-of-life treatment --- recycling --- solar power plant --- wind power plant --- life cycle analysis --- advanced industrial engineering --- modelling and simulation --- factory of the future --- smart factory --- manufacturing systems --- production planning optimisation --- decision support --- additive manufacturing --- fused filament fabrication --- CFR-PEEK --- optimal process parameters --- manufacturing performance --- multiple response optimization --- reconfigurable manufacturing system --- Petri net --- deadlock --- siphon --- supervisory controller --- reengineering --- simulation --- productivity --- batch processors --- real-time control --- dispatching --- wafer fabrication --- semiconductor manufacturing --- system-wide performance --- robust scheduling --- predictive scheduling --- machine failure --- failure prediction --- constraint programming --- constraint satisfaction problem --- cost estimation --- decision support systems --- multicriteria optimization --- production planning --- project management --- layout --- 3D printing devices --- methods of optimizing the arrangement of workstations --- car tire production process --- rubber industry --- environmental impact --- Life Cycle Assessment --- entire product lifecycle --- decision-making process --- lean maintenance --- effectiveness --- decision trees --- rough set theory
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