Advanced Signal Processing in Wearable Sensors for Health Monitoring |
Autore | Abbod Maysam |
Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
Descrizione fisica | 1 electronic resource (206 p.) |
Soggetto topico |
Technology: general issues
History of engineering & technology |
Soggetto non controllato |
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 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910566462503321 |
Abbod Maysam | ||
Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
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Emotion and Stress Recognition Related Sensors and Machine Learning Technologies |
Autore | Kyamakya Kyandoghere |
Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
Descrizione fisica | 1 electronic resource (550 p.) |
Soggetto topico | Technology: general issues |
Soggetto non controllato |
subject-dependent emotion recognition
subject-independent emotion recognition electrodermal activity (EDA) deep learning convolutional neural networks automatic facial emotion recognition intensity of emotion recognition behavioral biometrical systems machine learning artificial intelligence driving stress electrodermal activity road traffic road types Viola-Jones facial emotion recognition facial expression recognition facial detection facial landmarks infrared thermal imaging homography matrix socially assistive robot EEG arousal detection valence detection data transformation normalization mental stress detection electrocardiogram respiration in-ear EEG emotion classification emotion monitoring elderly caring outpatient caring stress detection deep neural network convolutional neural network wearable sensors psychophysiology sensor data analysis time series analysis signal analysis similarity measures correlation statistics quantitative analysis benchmarking boredom emotion GSR classification sensor face landmark detection fully convolutional DenseNets skip-connections dilated convolutions emotion recognition physiological sensing multimodal sensing flight simulation activity recognition physiological signals thoracic electrical bioimpedance smart band stress recognition physiological signal processing long short-term memory recurrent neural networks information fusion pain recognition long-term stress electroencephalography perceived stress scale expert evaluation affective corpus multimodal sensors overload underload interest frustration cognitive load stress research affective computing human-computer interaction deep convolutional neural network transfer learning auxiliary loss weighted loss class center stress sensing smart insoles smart shoes unobtrusive sensing stress center of pressure regression signal processing arousal aging adults musical genres emotion elicitation dataset emotion representation feature selection feature extraction computer science virtual reality head-mounted display |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910557346003321 |
Kyamakya Kyandoghere | ||
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
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Signal Processing Using Non-invasive Physiological Sensors |
Autore | Niazi Imran Khan |
Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
Descrizione fisica | 1 electronic resource (222 p.) |
Soggetto topico | Medical equipment & techniques |
Soggetto non controllato |
movement intention
brain–computer interface movement-related cortical potential neurorehabilitation phonocardiogram machine learning empirical mode decomposition feature extraction mel-frequency cepstral coefficients support vector machines computer aided diagnosis congenital heart disease statistical analysis convolutional neural network (CNN) long short-term memory (LSTM) emotion recognition EEG ECG GSR deep neural network physiological signals electroencephalography Brain-Computer Interface multiscale principal component analysis successive decomposition index motor imagery mental imagery classification hybrid brain-computer interface (BCI) home automation electroencephalogram (EEG) steady-state visually evoked potential (SSVEP) eye blink short-time Fourier transform (STFT) convolution neural network (CNN) human machine interface (HMI) rehabilitation wheelchair quadriplegia Raspberry Pi image gradient AMR voice Open-CV image processing acoustic startle reaction response reflex blink mobile sound stroke EMG brain-computer interface myoelectric control pattern recognition functional near-infrared spectroscopy z-score method channel selection region of interest channel of interest respiratory rate (RR) Electrocardiogram (ECG) ECG derived respiration (EDR) auscultation sites pulse plethysmograph biomedical signal processing feature selection and reduction discrete wavelet transform hypertension |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910566473903321 |
Niazi Imran Khan | ||
Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
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Wearable Sensors in the Evaluation of Gait and Balance in Neurological Disorders |
Autore | Suppa Antonio |
Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
Descrizione fisica | 1 electronic resource (274 p.) |
Soggetto topico | History of engineering & technology |
Soggetto non controllato |
inertial measurement units
gait analysis biomedical signal processing pattern recognition step detection physiological signals Parkinson’s disease pathological gait turning analysis wearable sensors mobile gait analysis wearables inertial sensors traumatic brain injury dynamic balance gait disorders gait patterns head injury gait symmetry gait smoothness acceleration machine learning classification accelerometer GAITRite multi-regression normalization SVM random forest classifier balance gait transcranial direct current stimulation wearable electronics IMUs cueing posture rehabilitation cerebellar ataxia movement analysis personalized medicine stroke asymmetry trunk reliability validity aging reactive postural responses yaw perturbation kinematics postural stability dynamic posturography multiple sclerosis gait metrics test-retest reliability sampling frequency accelerometry autocorrelation harmonic ratio six-minute walk back school inertial sensor lower back pain stability timed up and go test gait assessment tri-axial accelerometer CV healthy subjects test-retest trajectory reconstruction stride segmentation dynamic time warping pedestrian dead-reckoning near falls loss of balance pre-impact fall detection activities of daily life bio-signals EEG EMG wireless sensors posturography Alzheimer’s disease vestibular syndrome diagnosis symptoms monitoring wearable home-monitoring |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910557446403321 |
Suppa Antonio | ||
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
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