Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Advanced Signal Processing in Wearable Sensors for Health Monitoring
| 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 | ||
| ||
Data Analytics and Applications of the Wearable Sensors in Healthcare
| Data Analytics and Applications of the Wearable Sensors in Healthcare |
| Autore | Syed Abdul Shabbir |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (498 p.) |
| Soggetto topico |
Humanities
Social interaction |
| Soggetto non controllato |
eHealth
wearable monitoring services integration IoT Telemedicine wearable sensors multivariate analysis longitudinal study functional decline exercise intervention accidental falls fall detection real-world signal analysis performance measures non-wearable sensors accelerometers cameras machine learning smart textiles healthcare talking detection activity recognition and monitoring patient health and state monitoring wearable sensing orientation-invariant sensing motion sensors accelerometer gyroscope magnetometer pattern classification artificial intelligence supervised machine learning predictive analytics hemodialysis non-contact sensor heart rate respiration rate heart rate variability time-domain features frequency-domain features principal component analysis behaviour analysis classifier efficiency personal risk detection one-class classification actigraphy encoding data compression denoising edge computing signal processing wearables activity monitoring citizen science cluster analysis physical activity sedentary behavior walking energy expenditure wearable device impedance pneumography neural network mechanocardiogram (MCG) smart clothes heart failure (HF) left ventricular ejection fraction (LVEF) technology acceptance model (TAM) physical activity classification free-living GENEactiv accelerometer Gaussian mixture model hidden Markov model wavelets skill assessment deep learning LSTM state space model probabilistic inference latent features human activity recognition MIMU genetic algorithm feature selection classifier optimization bispectrum entropy feature extraction heat stroke filtering algorithm physiological parameters exercise experiment biomedical signal processing wearable biomedical sensors wireless sensor network respiratory monitoring optoelectronic plethysmography biofeedback biomedical technology exercise therapy orthopedics mobile health qualitative human factors inertial measurement unit disease prevention occupational healthcare P-Ergonomics precision ergonomics musculoskeletal disorders wellbeing at work electrocardiogram conductive gels noncontact electrode myocardial ischemia pacemaker ventricular premature contraction upper extremity motion action research arm test activities of daily living IoT wearable monitor health posture analysis spinal posture wearable sensor embedded system recurrent neural networks physical workload wearable systems for healthcare machine learning for real-time applications actigraph body worn sensors clothing sensors cross correlation analysis healthcare movement sensing wearable devices calibration inertial measurement units human movement physical activity type real-life GPS GIS |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557288603321 |
|
Syed Abdul Shabbir
|
||
| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Signal Processing Using Non-invasive Physiological Sensors
| 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 | ||
| ||
Wearable Sensors in the Evaluation of Gait and Balance in Neurological Disorders
| 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 | ||
| ||