A Novel Approach For Diagnosis Of Sleep Apnea |
Author(s): |
| R.C.Kokhila , PSNA college of engineering ; K.Ramamoorthy, PSNA college of engineering |
Keywords: |
| Autoregressive Modeling, SLEEP APNEA, Obstructive sleep apnea |
Abstract |
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Sleep Apnea is a recognize of abnormal breathing activities and limb movements on frequent disorder with detrimental health, performance and safety effects. The diagnosis of the disorder is mostly expensive. In this method we detect the four main features of respiratory signal. The automatic signal classification starts by extracting signal features from a 1 minute data segment through autoregressive modeling (AR) and other techniques. Four features are: signal energy, zero crossing frequency, dominant frequency estimated by AR and strength of dominant frequency based on AR. These features are then compared to threshold values and introduced to a series of conditions to determine the signal category for each specific feature. |
Other Details |
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Paper ID: IJSRDV3I2490 Published in: Volume : 3, Issue : 2 Publication Date: 01/05/2015 Page(s): 531-534 |
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