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
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Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
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Lo trovi qui: Univ. Federico II | ||
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Sharing Cities Shaping Cities |
Autore | Arcidiacono Andrea |
Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
Descrizione fisica | 1 electronic resource (142 p.) |
Soggetto non controllato |
Airbnb and policy innovation
accessibility Airbnb and housing typologies informality Melbourne sharing economy bike sharing local communities Airbnb and planning Airbnb and domestic design mobility policy platform cooperativism urban regeneration Airbnb and governance emotions democratic quality sharing urban studies stress levels sharing platform digital participation social relations spatial agency critical autoethnography cohousing collaborative workplaces participation Bourdieu co-design coworking entrepreneurial action coworking spaces Melbourne Airbnb coworking business collaborative economy design-research sustainable mobility urban mobility architecture architectural and urban effects of Airbnb ageing physiological sensors GSR sharing economic social street matchmaking socio-spatial effects of Airbnb sharing economy urban galvanic skin response coproduction coworking space emotional layer |
ISBN | 3-03897-989-9 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910346850703321 |
Arcidiacono Andrea
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MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
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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
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Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
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Lo trovi qui: Univ. Federico II | ||
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