Advanced Methods in Biomedical Signal Processing and Analysis
Editat de Kunal Pal, Samit Ari, Arindam Bit, Saugat Bhattacharyyaen Limba Engleză Paperback – 7 sep 2022
- Gives advanced methods in signal processing
- Includes machine and deep learning methods
- Presents experimental case studies
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Specificații
ISBN-13: 9780323859554
ISBN-10: 0323859550
Pagini: 432
Dimensiuni: 191 x 235 x 30 mm
Greutate: 0.74 kg
Editura: ELSEVIER SCIENCE
ISBN-10: 0323859550
Pagini: 432
Dimensiuni: 191 x 235 x 30 mm
Greutate: 0.74 kg
Editura: ELSEVIER SCIENCE
Public țintă
Biomedical engineering, signal processing, speech processing, and computer science researchers and graduate studentsCuprins
1. Feature engineering
2. Heart rate variability
3. Understanding the suitabillity of parametric modeling techniques in detecting the changes in the HRV signals acquired from cannabis consuming and nonconsuming Indian paddy-field workers
4. Patient-specific ECG beat classification using EMD and deep learning-based technique
5. Empirical wavelet transform and deep learning-based technique for ECG beat classification
6. Development of an Internet-of-Things (IoT)-based pill monitoring device for geriatric patients
7. Biomedical robotics
8. Combating COVID-19 by implying machine learning predictions and projections
9. Deep learning methods for analysis of neural signals: From conventional neural network to graph neural network
10. Improved extraction of the extreme thermal regions of breast IR images
11. New metrics to asses the subtle changes of the heart's electromagnetic field
12. The role of optimal and modified lead systems in electrocardiogram
13. Adaptive rate EEG processing and machine learning-based efficient recognition of epilepsy
14. Multimodal microscopy: A novel low-cost microscope designed for food and biological applications
2. Heart rate variability
3. Understanding the suitabillity of parametric modeling techniques in detecting the changes in the HRV signals acquired from cannabis consuming and nonconsuming Indian paddy-field workers
4. Patient-specific ECG beat classification using EMD and deep learning-based technique
5. Empirical wavelet transform and deep learning-based technique for ECG beat classification
6. Development of an Internet-of-Things (IoT)-based pill monitoring device for geriatric patients
7. Biomedical robotics
8. Combating COVID-19 by implying machine learning predictions and projections
9. Deep learning methods for analysis of neural signals: From conventional neural network to graph neural network
10. Improved extraction of the extreme thermal regions of breast IR images
11. New metrics to asses the subtle changes of the heart's electromagnetic field
12. The role of optimal and modified lead systems in electrocardiogram
13. Adaptive rate EEG processing and machine learning-based efficient recognition of epilepsy
14. Multimodal microscopy: A novel low-cost microscope designed for food and biological applications