Sleep State Scoring in Infants from Respiratory and Activity Measurements
| Autor: | Nadezhda A. Sazonova, Edward E. Sazonov, Bozhao Tan, Stephanie A. C. Schuckers, null CHIME study group |
|---|---|
| Rok vydání: | 2006 |
| Předmět: |
medicine.medical_specialty
Sleep state Polysomnography Acceleration Monitoring Ambulatory Motor Activity Electroencephalography Audiology Sensitivity and Specificity Pattern Recognition Automated Artificial Intelligence medicine Humans Plethysmograph Diagnosis Computer-Assisted medicine.diagnostic_test business.industry Infant Reproducibility of Results Eye movement Respiratory Function Tests Activity measurements Respiratory measurements Respiratory Mechanics Physical therapy Sleep Stages Sleep (system call) business Algorithms |
| Zdroj: | EMBC |
| DOI: | 10.1109/iembs.2006.259719 |
| Popis: | Sleep state scoring usually relies on polysomnographic measurements, which include electroencephalogram (EEG), electromyogram (EMG), electro-oculogram (EOG), two or three lead chest electrocardiogram (ECG), and may include other measurements. Overall, polysomnography is an intrusive procedure not well tolerated by infants and elderly. The goal of this research is to study possibility of automatic sleep state scoring from less intrusive measurements such as activity measurements and respiratory measurements by inductive plethysmography. The study is based on the Collaborative Home Infant Monitoring Evaluation (CHIME) dataset. Results demonstrate that the suggested approach is capable of scoring sleep states (awake, rapid eye movement and quiet sleep) with good accuracy. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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