Abstract
Due to involvement of different types of noise, electrocardiogram signal needs robust techniques for its analysis. For that purpose, the theory of chaos analysis is applied as a feature extraction tool on different pathological datasets obtained from different cardiology laboratories. This paper presents the important observations on attractor plots obtained at different time delays. It facilitates the cardiologist in segregating the normal and abnormal subjects on the basis of measured heart rate. Using support vector machine, heart diseases are classified with mean-squared error of 0.023%. Two conditions, viz. normal and abnormal, are considered. The novelty of this paper is to use chaos analysis as an effective feature extraction tool for improving strength of healthcare professionals. The proposed technique shows detection error of 0.077%. The proposed method finds its major applications in regular screening of patient’s heart, heart dynamics observation during major heart therapy, etc.
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Gupta, V., Chaturvedi, Y., Kumar, P., Kanungo, A., Kumar, P. (2022). Attractor Plot as an Emerging Tool in ECG Signal Processing for Improved Health Informatics. In: Natarajan, S.K., Prakash, R., Sankaranarayanasamy, K. (eds) Recent Advances in Manufacturing, Automation, Design and Energy Technologies. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-16-4222-7_42
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