Abstract
Sleep Apnoea is a disorder characterized by abnormal pauses in breathing during sleep. Obstructive Sleep Apnoea is a condition where breathing is interrupted by a physical block to airflow despite respiratory effort. It is based on the fact that heart rate dynamics of a healthy person differs from that of a person suffering from OSA. The heart rate typically shows cyclic increases and decreases associated with the Apnoea phase and resumption of breathing. Identification of the oscillatory dynamics is done using the RR inter beat interval series. Hilbert transformation is applied to the sinus inter beat interval time series to derive the instantaneous amplitudes and frequencies of the series thus monitoring the presence or absence of OSA.
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Acknowledgments
We would like to offer our gratitude to Mr P. G. Kumaravelu, HOD of Department of Medical Electronics, MSRIT who gave us the support and encouragement during the course of the project. We are extremely grateful to Dr. Uma Maheshwari, M. S Ramaiah Memorial Hospital who helped us in Data acquisition. We would also like to thank Mr. Sanjay H. S, for helping and guiding us through this project. Most importantly we would like to thank Mr. Anand M, Research engineer, C Dot, Bangalore and Dr. Sethu Selvi, HOD, Department of Electronics and Communication, MSRIT whose help was provided during the signal processing part of the project.
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Aishwarya, A., Bharath, N.S., Swathi, M., Prabha, R. (2013). Detection of Obstructive Sleep Apnoea Using ECG Signal. In: Malathi, R., Krishnan, J. (eds) Recent Advancements in System Modelling Applications. Lecture Notes in Electrical Engineering, vol 188. Springer, India. https://doi.org/10.1007/978-81-322-1035-1_33
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DOI: https://doi.org/10.1007/978-81-322-1035-1_33
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