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@article{143605,
        author = {Prof. Shaista Parveen, Prof. Kaveri shankar and Prof. Kaveri Shankar},
        title = {Monitoring of Respiratory Signals for the Detection of Apnea},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {2},
        number = {12},
        pages = {346-351},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=143605},
        abstract = {Monitoring of breathing dynamics is an essential diagnostic tool in various clinical environments, such as sleep diagnostics, intensive care and neonatal monitoring. This paper introduces an innovative signal analysis method that is capable of detecting the presence or absence of normal breathing. To analyse the breathing patterns, respiratory records are used. These records are easily available in the physionet data base. An apnea detection method that employs the chest impedance (volume of air) is developed. A filter is used for eliminating the noises from the signal and an envelope is created which helps to detect the breath cycles. This method has been applied to respiratory database of physionet and it is proved that compared to the presently used monitors this method gives substantial improvement in apnea detection. The results of analysis show the presence apnea in breathing patterns.},
        keywords = {Respiration, sleep apnea, Detrending, FFT, Hilbert transformation, Envelope generation.},
        month = {},
        }