Signal Processing Using Non-invasive Physiological Sensors

Signal Processing Using Non-invasive Physiological Sensors

Non-invasive biomedical sensors for monitoring physiological parameters from the human body for potential future therapies and healthcare solutions. Today, a critical factor in providing a cost-effective healthcare system is improving patients' quality of life and mobility, which can be achieve...

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Bibliographic Details
Format: eBook
Language:English
Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
Subjects:
Medical equipment and techniques
acoustic
AMR voice
auscultation sites
biomedical signal processing
blink
brain-computer interface
Brain-Computer Interface
channel of interest
channel selection
classification
computer aided diagnosis
congenital heart disease
convolution neural network (CNN)
convolutional neural network (CNN)
deep neural network
discrete wavelet transform
ECG
ECG derived respiration (EDR)
EEG
Electrocardiogram (ECG)
electroencephalogram (EEG)
electroencephalography
EMG
emotion recognition
empirical mode decomposition
eye blink
feature extraction
feature selection and reduction
functional near-infrared spectroscopy
GSR
home automation
human machine interface (HMI)
hybrid brain-computer interface (BCI)
hypertension
image gradient
image processing
long short-term memory (LSTM)
machine learning
mel-frequency cepstral coefficients
mental imagery
mobile
motor imagery
movement intention
movement-related cortical potential
multiscale principal component analysis
myoelectric control
neurorehabilitation
Open-CV
pattern recognition
phonocardiogram
physiological signals
pulse plethysmograph
quadriplegia
Raspberry Pi
reaction
reflex
region of interest
rehabilitation
respiratory rate (RR)
response
short-time Fourier transform (STFT)
sound
startle
statistical analysis
steady-state visually evoked potential (SSVEP)
stroke
successive decomposition index
support vector machines
wheelchair
z-score method
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