Advances in non-invasive biomedical signal sensing and processing with machine learning / / edited by Saeed Mian Qaisar, Humaira Nisar, and Abdulhamit Subasi |
Edizione | [1st ed. 2023.] |
Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2023] |
Descrizione fisica | 1 online resource (385 pages) |
Disciplina | 610.28 |
Soggetto topico |
Machine learning
Medical innovations Biosensors |
ISBN | 3-031-23239-9 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | 1. Introduction to non-invasive biomedical signals for healthcare -- 2. Signal Acquisition Preprocessing and Feature Extraction Techniques for Biomedical Signals -- 3. The Role of EEG as Neuro-Markers for Patients with Depression: A systematic Review -- 4. Brain-Computer Interface (BCI) Based on the EEG Signal Decomposition Butterfly Optimization and Machine Learning -- 5. Advances in the analysis of electrocardiogram in context of mass screening: technological trends and application of artificial intelligence anomaly detection -- 6. Application of Wavelet Decomposition and Machine Learning for the sEMG Signal based Gesture Recognition -- 7. Review of EEG Signals Classification using Machine Learning and Deep-learning Techniques -- 8. "Biomedical signal processing and artificial intelligence in EOG signals" -- 9. Peak Spectrogram and Convolutional Neural Network-based Segmentation and Classification for Phonocardiogram Signals -- 10. Eczema skin lesions segmentation using deep neural network (U-net) -- 11. Biomedical signal processing for automated detection of sleep arousals Based on Multi-Physiological Signals with Ensemble learning methods -- 12. Deep Learning Assisted Biofeedback -- 13. Estimations of Emotional Synchronization Indices for Brain regions using Electroencephalogram Signal Analysis -- 14. Recognition Enhancement of Dementia Patients’ Working Memory using Entropy-based Features and Local Tangent Space Alignment Algorithm. |
Record Nr. | UNINA-9910678252803321 |
Cham, Switzerland : , : Springer, , [2023] | ||
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Lo trovi qui: Univ. Federico II | ||
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Advances in non-invasive biomedical signal sensing and processing with machine learning / / edited by Saeed Mian Qaisar, Humaira Nisar, and Abdulhamit Subasi |
Edizione | [1st ed. 2023.] |
Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2023] |
Descrizione fisica | 1 online resource (385 pages) |
Disciplina | 610.28 |
Soggetto topico |
Machine learning
Medical innovations Biosensors |
ISBN | 3-031-23239-9 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | 1. Introduction to non-invasive biomedical signals for healthcare -- 2. Signal Acquisition Preprocessing and Feature Extraction Techniques for Biomedical Signals -- 3. The Role of EEG as Neuro-Markers for Patients with Depression: A systematic Review -- 4. Brain-Computer Interface (BCI) Based on the EEG Signal Decomposition Butterfly Optimization and Machine Learning -- 5. Advances in the analysis of electrocardiogram in context of mass screening: technological trends and application of artificial intelligence anomaly detection -- 6. Application of Wavelet Decomposition and Machine Learning for the sEMG Signal based Gesture Recognition -- 7. Review of EEG Signals Classification using Machine Learning and Deep-learning Techniques -- 8. "Biomedical signal processing and artificial intelligence in EOG signals" -- 9. Peak Spectrogram and Convolutional Neural Network-based Segmentation and Classification for Phonocardiogram Signals -- 10. Eczema skin lesions segmentation using deep neural network (U-net) -- 11. Biomedical signal processing for automated detection of sleep arousals Based on Multi-Physiological Signals with Ensemble learning methods -- 12. Deep Learning Assisted Biofeedback -- 13. Estimations of Emotional Synchronization Indices for Brain regions using Electroencephalogram Signal Analysis -- 14. Recognition Enhancement of Dementia Patients’ Working Memory using Entropy-based Features and Local Tangent Space Alignment Algorithm. |
Record Nr. | UNISA-996547951803316 |
Cham, Switzerland : , : Springer, , [2023] | ||
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Lo trovi qui: Univ. di Salerno | ||
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