Breath Analysis for Medical Applications /
| Autores principales: | , , |
|---|---|
| Autor Corporativo: | |
| Formato: | eBook |
| Lenguaje: | English |
| Publicado: |
Singapore :
Springer Singapore : Imprint: Springer,
2017.
|
| Edición: | 1st ed. 2017. |
| Materias: |
Tabla de Contenidos:
- 1. Introduction
- 2. Literature Review
- 3. A Novel Breath Acquisition System Design
- 4. An LDA Based Sensor Selection Approach
- 5. Sensor Evaluation in a Breath Acquisition System
- 6. Improving the Transfer Ability of Prediction Models
- 7. Learning Classification and Regression Models for Breath Data with Drift based on Transfer Samples
- 8. A Transfer Learning Approach with Autoencoder for Correcting Instrumental Variation and Time-Varying Drift
- 9. Drift Correction using Maximum Independence Domain Adaptation
- 10. Feature Selection and Analysis on Correlated Breath Data
- 11. Breath Sample Identification by Sparse Representation-based Classification
- 12. Monitor Blood Glucose Levels via Sparse Representation Approach
- 13. Diabetics by Means of Breath Signal Analysis
- 14. A Breath Analysis System for Diabetes Screening and Blood Glucose Level Prediction. 15. A Novel Medical E-Nose Signal Analysis System
- 16. Book Review and Future Work.