Requirement Analysis and Architecture Design for Ubiquitous Healthcare Service Systems

Yang, WonSeob; Hwang, Kyung Soon; Lee, Keon Myung; Lee, Kyung Mi; Kim, Wun-Jae; Yun, Seok Jung

doi:10.5391/ijfis.2007.7.3.209

Cited by 8 publications

(1 citation statement)

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“…A high performance processor with mass storage is necessary to precisely digitize the ECG data, which leads to the difficulty in developing portable ECG devices because of limited resources. In addition, the ECG data must be managed with efficiency for long-term monitoring of the patient's heart condition [1][2][3]. Therefore, data compression needs to be employed for efficient storage, processing and transmission.…”

Section: Introductionmentioning

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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Section: Introductionmentioning

confidence: 99%