| Autor: |
Aykut Erdamar, Tuncay Bayrak, Hikmet Firat, Murad Mutlu, Sadik Ardiç, Osman Erogul |
| Jazyk: |
English<br />Turkish |
| Rok vydání: |
2017 |
| Předmět: |
|
| Zdroj: |
Türk Uyku Tıbbı Dergisi, Vol 4, Iss 1, Pp 6-15 (2017) |
| Druh dokumentu: |
article |
| ISSN: |
2148-1504 |
| DOI: |
10.4274/jtsm.21931 |
| Popis: |
Objective In this work, a new methodology based on signal processing techniques for the quantitative analysis of uvulopalatal flap surgery is proposed. Clinical assessment studies of uvulopalatal flap surgery are based on not only the physician’s examination, but also the patient’s subjective feedback. Quantitative and objective evaluation studies are still lacking in the literature. Materials and Methods Full night sleep records were analyzed for 21 patients before and after the surgery. The proposed algorithm consists of two independent parts. In the first part, the heart rate variability and complexity of the electrocardiogram were calculated. The second part includes calculating the electroencephalogram sub-band energy. Afterwards, the statistical methods were applied in order to determine the correlation of clinical and experimental parameters. Results The low frequency/high frequency ratio and the sub-band energy of beta wave were significant for the patients having low post-operative delta sleep duration. Moreover, the sub-band energies of both alpha and beta waves, and theta wave were significant for the patients who had high post-operative delta sleep duration and blood oxygen saturation (SaO2)-parameter. Complexity was significant for the patients with low postoperative respiratory disturbance index and SaO2 parameter, and respiratory disturbance is correlated with snoring index. Conclusion Respiratory disturbance index, which is not significant according to the pre- and post-operative clinical findings, was found to be directly related to the complexity feature. The most important result of this work is that the pre-operative complexity feature is correlated with respiratory disturbance and snoring index. This means that complexity feature can be a predictor prior to surgery. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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