Abstract: Sleep analysis and its categories in sleep scoring system is considered to be helpful in an area of sleep research and sleep medicine. The scheduled study employs novel approach for computer assisted automated sleep scoring system using physiological signals and Artificial neural network. The data collected were recorded for seven hour, 30 second epoch for each subject. The data procured from the physiological signal was controlled and prepared to expel degenerated signals in order to extract essential data or features used for the study. As, it is known human body distributes its own electrical signals which is needed to be eliminated and these are known as artifacts and they are needed to be filtered out. In this study, signal filtering is achieved by using Butterworth Low-Pass filter. The features extracted were trained and classified using an Artificial Neural Network classifier. Even though, it is a highly complicated concept, using same in biomedical field when engaged with electrical signals which is obtained from body is novel. The accuracy estimated for the system was found to be good and thus the procedure can be very helpful in clinics, particularly useful for neurologist for diagnosing the sleep disorders.

Hemu Farooq, Anuj Jain, V.K. Sharma, Iflah Aijaz and Sheikh Mohammad Idrees, “A Novel Approach for Computer Assisted Sleep Scoring Mechanism using ANN” International Journal of Advanced Computer Science and Applications(IJACSA), 11(8), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110878

@article{Farooq2020,
title = {A Novel Approach for Computer Assisted Sleep Scoring Mechanism using ANN},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110878},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110878},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {8},
author = {Hemu Farooq and Anuj Jain and V.K. Sharma and Iflah Aijaz and Sheikh Mohammad Idrees}
}