Application of a Modified Entropy Computational Method in Assessing the Complexity of Pulse Wave Velocity Signals in Healthy and Diabetic Subjects
Using 1000 successive points of a pulse wave velocity (PWV) series, we previously distinguished healthy from diabetic subjects with multi-scale entropy (MSE) using a scale factor of 10. One major limitation is the long time for data acquisition (i.e., 20 min). This study aimed at validating the sens...
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MDPI AG
2014-07-01
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| Series: | Entropy |
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| Online Access: | http://www.mdpi.com/1099-4300/16/7/4032 |
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| author | Yi-Chung Chang Hsien-Tsai Wu Hong-Ruei Chen An-Bang Liu Jung-Jen Yeh Men-Tzung Lo Jen-Ho Tsao Chieh-Ju Tang I-Ting Tsai Cheuk-Kwan Sun |
| author_facet | Yi-Chung Chang Hsien-Tsai Wu Hong-Ruei Chen An-Bang Liu Jung-Jen Yeh Men-Tzung Lo Jen-Ho Tsao Chieh-Ju Tang I-Ting Tsai Cheuk-Kwan Sun |
| author_sort | Yi-Chung Chang |
| collection | DOAJ |
| description | Using 1000 successive points of a pulse wave velocity (PWV) series, we previously distinguished healthy from diabetic subjects with multi-scale entropy (MSE) using a scale factor of 10. One major limitation is the long time for data acquisition (i.e., 20 min). This study aimed at validating the sensitivity of a novel method, short time MSE (sMSE) that utilized a substantially smaller sample size (i.e., 600 consecutive points), in differentiating the complexity of PWV signals both in simulation and in human subjects that were divided into four groups: healthy young (Group 1; n = 24) and middle-aged (Group 2; n = 30) subjects without known cardiovascular disease and middle-aged individuals with well-controlled (Group 3; n = 18) and poorly-controlled (Group 4; n = 22) diabetes mellitus type 2. The results demonstrated that although conventional MSE could differentiate the subjects using 1000 consecutive PWV series points, sensitivity was lost using only 600 points. Simulation study revealed consistent results. By contrast, the novel sMSE method produced significant differences in entropy in both simulation and testing subjects. In conclusion, this study demonstrated that using a novel sMSE approach for PWV analysis, the time for data acquisition can be substantially reduced to that required for 600 cardiac cycles (~10 min) with remarkable preservation of sensitivity in differentiating among healthy, aged, and diabetic populations. |
| first_indexed | 2024-12-10T07:20:21Z |
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| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-12-10T07:20:21Z |
| publishDate | 2014-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-87513ab2348249e5bdb52ecf7aaa9ea02022-12-22T01:57:49ZengMDPI AGEntropy1099-43002014-07-011674032404310.3390/e16074032e16074032Application of a Modified Entropy Computational Method in Assessing the Complexity of Pulse Wave Velocity Signals in Healthy and Diabetic SubjectsYi-Chung Chang0Hsien-Tsai Wu1Hong-Ruei Chen2An-Bang Liu3Jung-Jen Yeh4Men-Tzung Lo5Jen-Ho Tsao6Chieh-Ju Tang7I-Ting Tsai8Cheuk-Kwan Sun9Graduate Institute of Communication Engineering, National Taiwan University, Taipei 10617, TaiwanDepartment of Electrical Engineering, National Dong Hwa University, Hualien 97401, TaiwanDepartment of Electrical Engineering, National Dong Hwa University, Hualien 97401, TaiwanDepartment of Electrical Engineering, National Dong Hwa University, Hualien 97401, TaiwanDepartment of Electrical Engineering, National Dong Hwa University, Hualien 97401, TaiwanResearch Center for Adaptive Data Analysis & Center for Dynamical Biomarkers and Translational Medicine, National Central University, Chungli 32001, TaiwanGraduate Institute of Communication Engineering, National Taiwan University, Taipei 10617, TaiwanDepartment of Internal Medicine, Hualien Hospital, Ministry of Health and Welfare, Hualien 97061, TaiwanDepartment of Emergency Medicine, E-Da Hospital, I-Shou University, Kaohsiung 82445, TaiwanDepartment of Emergency Medicine, E-Da Hospital, I-Shou University, Kaohsiung 82445, TaiwanUsing 1000 successive points of a pulse wave velocity (PWV) series, we previously distinguished healthy from diabetic subjects with multi-scale entropy (MSE) using a scale factor of 10. One major limitation is the long time for data acquisition (i.e., 20 min). This study aimed at validating the sensitivity of a novel method, short time MSE (sMSE) that utilized a substantially smaller sample size (i.e., 600 consecutive points), in differentiating the complexity of PWV signals both in simulation and in human subjects that were divided into four groups: healthy young (Group 1; n = 24) and middle-aged (Group 2; n = 30) subjects without known cardiovascular disease and middle-aged individuals with well-controlled (Group 3; n = 18) and poorly-controlled (Group 4; n = 22) diabetes mellitus type 2. The results demonstrated that although conventional MSE could differentiate the subjects using 1000 consecutive PWV series points, sensitivity was lost using only 600 points. Simulation study revealed consistent results. By contrast, the novel sMSE method produced significant differences in entropy in both simulation and testing subjects. In conclusion, this study demonstrated that using a novel sMSE approach for PWV analysis, the time for data acquisition can be substantially reduced to that required for 600 cardiac cycles (~10 min) with remarkable preservation of sensitivity in differentiating among healthy, aged, and diabetic populations.http://www.mdpi.com/1099-4300/16/7/4032multi-scale entropyscale factorpulse wave velocityagediabetes |
| spellingShingle | Yi-Chung Chang Hsien-Tsai Wu Hong-Ruei Chen An-Bang Liu Jung-Jen Yeh Men-Tzung Lo Jen-Ho Tsao Chieh-Ju Tang I-Ting Tsai Cheuk-Kwan Sun Application of a Modified Entropy Computational Method in Assessing the Complexity of Pulse Wave Velocity Signals in Healthy and Diabetic Subjects Entropy multi-scale entropy scale factor pulse wave velocity age diabetes |
| title | Application of a Modified Entropy Computational Method in Assessing the Complexity of Pulse Wave Velocity Signals in Healthy and Diabetic Subjects |
| title_full | Application of a Modified Entropy Computational Method in Assessing the Complexity of Pulse Wave Velocity Signals in Healthy and Diabetic Subjects |
| title_fullStr | Application of a Modified Entropy Computational Method in Assessing the Complexity of Pulse Wave Velocity Signals in Healthy and Diabetic Subjects |
| title_full_unstemmed | Application of a Modified Entropy Computational Method in Assessing the Complexity of Pulse Wave Velocity Signals in Healthy and Diabetic Subjects |
| title_short | Application of a Modified Entropy Computational Method in Assessing the Complexity of Pulse Wave Velocity Signals in Healthy and Diabetic Subjects |
| title_sort | application of a modified entropy computational method in assessing the complexity of pulse wave velocity signals in healthy and diabetic subjects |
| topic | multi-scale entropy scale factor pulse wave velocity age diabetes |
| url | http://www.mdpi.com/1099-4300/16/7/4032 |
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