ECG Signal Compression using Feature Points based on Curvature

Kim, Sung‐Wan; Ryu, Chunha; Yun, Byoung-Ju; Kim, Jeong-Hong; Choi, Byung-Jae; Park, Kil−Houm

doi:10.5391/jkiis.2010.20.5.624

Cited by 5 publications

(3 citation statements)

References 10 publications

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“…where ( ) f ε and ( ) f δ represent erosion and dilation, respectively [13]. In this paper, the background region is extracted by using the closing operation.…”

Section: Background Extractionmentioning

confidence: 99%

Cutting Blade Measurement of an Ultrasonic Cutting Machine Using Multi-Step Detection

et al. 2019

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An algorithm for measurement of the cutting blade of the ultrasonic vibration cutting machine used in an automation machine is proposed in this paper. The proposed algorithm, which is based upon a multi-step detection method, is developed for the accurate measurement of the cutting blade by exactly determining its rotation angle, length, and thickness. Instead of the commonly used Otsu method, we propose a new curvature-based adaptive binarization method, which provides more accurate details about the dimensions of the cutting blade. A region of interest containing the cutting blade from the acquired image is first extracted in the multi-step detection method, which is further processed to remove the noise, which increases the measurement reliability. An important feature of the proposed process is the restoration of the cutting blade’s tip data, which used to be lost during the fine noise-filtering process. The rotation angle and length are measured using the minimum rotated rectangle while the line fitting based upon the least square method is applied to increase the reliability of the thickness measurement. Experimental results validate the superiority of the proposed method over the conventional Otsu method.

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“…where ( ) f ε and ( ) f δ represent erosion and dilation, respectively [13]. In this paper, the background region is extracted by using the closing operation.…”

Section: Background Extractionmentioning

confidence: 99%

Cutting Blade Measurement of an Ultrasonic Cutting Machine Using Multi-Step Detection

et al. 2019

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“…Curvature refers to the deviation rate of a curve or a curved surface from a straight line or plane surface tangent to it [13]. The curvature value of the input ECG signal is calculated for the vertex selection, which has a larger curvature value than the threshold value.…”

Section: Vertex Selection Based On the Curvaturementioning

confidence: 99%

Electrocardiogram Signal Compression with Reconstruction via Radial Basis Function Interpolation Based on the Vertex

Ryu¹,

Kim²,

Choi³

et al. 2013

International Journal of Fuzzy Logic and Intelligent Systems

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Patients with heart disease need long-term monitoring of the electrocardiogram (ECG) signal using a portable electrocardiograph. This trend requires the miniaturization of data storage and faster transmission to medical doctors for diagnosis. The ECG signal needs to be utilized for efficient storage, processing and transmission, and its data must contain the important components for diagnosis, such as the P wave, QRS-complex, and T wave. In this study, we select the vertex which has a larger curvature value than the threshold value for compression. Then, we reconstruct the compressed signal using by radial basis function interpolation. This technique guarantees a lower percentage of root mean square difference with respect to the extracted sample points and preserves all the important features of the ECG signal. Its effectiveness has been demonstrated in the experiment using the Massachusetts Institute of Technology and Boston's Beth Israel Hospital arrhythmia database.

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“…직접 압축 방식은 심전도 신호 데이터의 값을 시 간 영역에서 해석하여 압축을 한다. 이 방법에는 Turning-Point, AZTEC, CORTES, FAN, DCPM, 곡률기 반 압축, B-spline 기반 압축 등이 있다 [6][7][8][9][10][11] …”

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ECG Signal Compression based on Adaptive Multi-level Code

Kim¹

2013

Journal of Korean Institute of Intelligent Systems

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ECG signal has the feature that is repeated in a cycle of P, Q, R, S, and T waves and is sampled at a high sampling frequency in general. By using the feature of periodic ECG signals, maximizing compression efficiency while minimizing the loss of important information for diagnosis is required. However, the periodic characteristics of such amplitude and period is not constant by measuring time and patients. Even though measured at the same time, the patient's characteristics display different periodic intervals. In this paper, an adaptive multi-level coding is provided by coding adaptively the dominant and non-dominant signal interval of the ECG signal. The proposed method can maximize the compression efficiency by using a multi-level code that applies different compression ratios considering information loss associated with the dominant signal intervals and non-dominant signal intervals. For the case of long time measurement, this method has a merit of maximizing compression ratio compared with existing compression methods that do not use the periodicity of the ECG signal and for the lossless compression coding of non-dominant signal intervals, the method has an advantage that can be stored without loss of information. The effectiveness of the ECG signal compression is proved throughout the experiment on ECG signal of MIT-BIH arrhythmia database.

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ECG Signal Compression using Feature Points based on Curvature

Cited by 5 publications

References 10 publications

Cutting Blade Measurement of an Ultrasonic Cutting Machine Using Multi-Step Detection

Cutting Blade Measurement of an Ultrasonic Cutting Machine Using Multi-Step Detection

Electrocardiogram Signal Compression with Reconstruction via Radial Basis Function Interpolation Based on the Vertex

ECG Signal Compression based on Adaptive Multi-level Code

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