Question

Please read the following IEEE paper for the topic details:

A Novel Dynamic Model to Predict Abnormal Oxygen Denaturation in Blood.

Briefly explain the purpose of this paper, the results, does the results make sense.

add https:// to the link:

files.fm/u/kjjzbsnf

Answer 1

The current paper talks about the biomedical monitoring system and the technological advancements in them. Pulse oximetry monitoring devices are used in general care units to record oxygen saturation levels in the blood of the patient. Significant postoperative complications are also monitored using oxygen desaturation index of 4 percent. Certain physiological signals are predicted by the monitoring techniques to understand the state of the patient after the operation. This study has considered a physiological signal to investigate the better model for predicting the abnormal events that occur before any medical complication that comes out after surgery.
Apart from several other models, the data-driven autoregressive model was frequently used to build the dynamic models from the physiological data. The authors mentioned that recently they have developed AR-10 model to collect the signals regarding the dynamics of oxygen desaturation levels and they seem to have used this model to predict abnormal as well as critical oxygen desaturation events.
The results section is explained by the authors that their AR-10 model did work well in predicting the signals regarding the dynamics of oxygen desaturation levels. They have constructed a dynamic model that could predict 20sec ahead of the abnormal event and compared the results with that of the standard AR-10 model anomaly. The rootmeansquareerror (RMSE) values computed for 20sec ahead prediction were also compared with that of the standard AR-10 model.
Although the RMSE was found to be increasing in the proposed model compared to that of the standard model, the proposed AR-10 model was observed to have better ability to capture the abnormal events of the oxygen desaturation of the patient's blood before any complication. The AR-10 model prediction sensitivity was found to have enhanced from 69.7% to 98.9%, which says that this model has the higher capacity to predict the clinically relevant events.
In conclusion, this paper talked about modeling and predicting the dynamics of the blood oxygenation signals. A new performance measurement technique has been used to identify the novel predictive model of the oxygen desaturation signals by optimizing the measurement.