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 achieved by...
Furkejuvvon:
| Materiálatiipa: | Online |
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| Giella: | eaŋgalasgiella |
| Almmustuhtton: |
MDPI - Multidisciplinary Digital Publishing Institute
2022
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| Fáttát: | |
| Liŋkkat: | ONIX_20220506_9783036537207_275 |
| Fáddágilkorat: |
Eai fáddágilkorat, Lasit vuosttaš fáddágilkora!
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| _version_ | 1869521096350367744 |
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| collection | Directory of Open Access Books |
| description | 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 achieved by developing non-invasive sensor systems, which can then be deployed in point of care, used at home or integrated into wearable devices for long-term data collection. Another factor that plays an integral part in a cost-effective healthcare system is the signal processing of the data recorded with non-invasive biomedical sensors. In this book, we aimed to attract researchers who are interested in the application of signal processing methods to different biomedical signals, such as an electroencephalogram (EEG), electromyogram (EMG), functional near-infrared spectroscopy (fNIRS), electrocardiogram (ECG), galvanic skin response, pulse oximetry, photoplethysmogram (PPG), etc. We encouraged new signal processing methods or the use of existing signal processing methods for its novel application in physiological signals to help healthcare providers make better decisions. |
| format | Online |
| id | doab-20.500.12854ir-81209 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-812092024-03-31T13:08:50Z Signal Processing Using Non-invasive Physiological Sensors Niazi, Imran Khan Naseer, Noman Santosa, Hendrik 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 thema EDItEUR::M Medicine and Nursing::MB Medicine: general issues::MBG Medical equipment and techniques 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 achieved by developing non-invasive sensor systems, which can then be deployed in point of care, used at home or integrated into wearable devices for long-term data collection. Another factor that plays an integral part in a cost-effective healthcare system is the signal processing of the data recorded with non-invasive biomedical sensors. In this book, we aimed to attract researchers who are interested in the application of signal processing methods to different biomedical signals, such as an electroencephalogram (EEG), electromyogram (EMG), functional near-infrared spectroscopy (fNIRS), electrocardiogram (ECG), galvanic skin response, pulse oximetry, photoplethysmogram (PPG), etc. We encouraged new signal processing methods or the use of existing signal processing methods for its novel application in physiological signals to help healthcare providers make better decisions. 2022-05-06T11:35:31Z 2022-05-06T11:35:31Z 2022 book ONIX_20220506_9783036537207_275 9783036537207 9783036537191 https://directory.doabooks.org/handle/20.500.12854/81209 eng image/jpeg Attribution 4.0 International https://mdpi.com/books/pdfview/book/5241 https://mdpi.com/books/pdfview/book/5241 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-3719-1 10.3390/books978-3-0365-3719-1 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036537207 9783036537191 222 Basel open access |
| spellingShingle | 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 thema EDItEUR::M Medicine and Nursing::MB Medicine: general issues::MBG Medical equipment and techniques Signal Processing Using Non-invasive Physiological Sensors |
| title | Signal Processing Using Non-invasive Physiological Sensors |
| title_full | Signal Processing Using Non-invasive Physiological Sensors |
| title_fullStr | Signal Processing Using Non-invasive Physiological Sensors |
| title_full_unstemmed | Signal Processing Using Non-invasive Physiological Sensors |
| title_short | Signal Processing Using Non-invasive Physiological Sensors |
| title_sort | signal processing using non invasive physiological sensors |
| topic | 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 thema EDItEUR::M Medicine and Nursing::MB Medicine: general issues::MBG Medical equipment and techniques |
| topic_facet | 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 thema EDItEUR::M Medicine and Nursing::MB Medicine: general issues::MBG Medical equipment and techniques |
| url | ONIX_20220506_9783036537207_275 |