A sensor-based wrist pulse signal processing and lung cancer recognition

Pulse diagnosis is an efficient method in traditional Chinese medicine for detecting the health status of a person in a non-invasive and convenient way. Jin's pulse diagnosis (JPD) is a very efficient recent development that is gradually recognized and well validated by the medical community in recent years. However, no acceptable results have been achieved for lung cancer recognition in the field of biomedical signal processing using JPD. More so, there is no standard JPD pulse feature defined with respect to pulse signals. Our work is designed mainly for care giving service conveniently at home to the people having lung cancer by proposing a novel wrist pulse signal processing method, having an insight from JPD. We developed an iterative slide window (ISW) algorithm to segment the de-noised signal into single periods. We analyzed the characteristics of the segmented pulse waveform and for the first time summarized 26 features to classify the pulse waveforms of healthy individuals and lung cancer patients using a cubic support vector machine (CSVM). The result achieved by the proposed method is found to be 78.13% accurate.

[1]  Bo Shen,et al.  Computerized Wrist Pulse Signal Diagnosis Using KPCA , 2010, ICMB.

[2]  Ching-Hsing Luo,et al.  Neural network study for standardizing pulse-taking depth by the width of artery , 2015, Comput. Biol. Medicine.

[3]  Sergio Escalera,et al.  On the Decoding Process in Ternary Error-Correcting Output Codes , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  D. Narayana Dutt,et al.  Study of wrist pulse signals using time domain spatial features , 2015, Comput. Electr. Eng..

[5]  Lu Wang,et al.  Multi-Gaussian fitting for pulse waveform using Weighted Least Squares and multi-criteria decision making method , 2013, Comput. Biol. Medicine.

[6]  W. Zuo,et al.  Wrist blood flow signal-based computerized pulse diagnosis using spatial and spectrum features , 2010 .

[7]  Henry T. Y. Yang,et al.  A correlation between pulse diagnosis of human body and health monitoring of structures , 2004 .

[8]  A. S. Ferreira,et al.  Pulse Waveform Analysis of Chinese Pulse Images and Its Association with Disability in Hypertension. , 2016, Journal of acupuncture and meridian studies.

[9]  Hen-Hong Chang,et al.  Regression analysis of radial artery pulse palpation as a potential tool for traditional Chinese medicine training education. , 2013, Complementary therapies in medicine.

[10]  Dongyu Zhang,et al.  Pulse Waveform Classification Using Support Vector Machine with Gaussian Time Warp Edit Distance Kernel , 2014, Comput. Math. Methods Medicine.

[11]  Chih-Jen Lin,et al.  Training and Testing Low-degree Polynomial Data Mappings via Linear SVM , 2010, J. Mach. Learn. Res..

[12]  Ching-Hsing Luo,et al.  How to standardize the pulse-taking method of traditional Chinese medicine pulse diagnosis , 2013, Comput. Biol. Medicine.

[13]  R. Velik.  An objective review of the technological developments for radial pulse diagnosis in Traditional Chinese Medicine , 2015 .

[14]  Geyong Min,et al.  Lifelogging Data Validation Model for Internet of Things Enabled Personalized Healthcare , 2018, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[15]  Wang Yiqin,et al.  Research on a Novel Three-Channel Self-pressurized Wrist Pulse Acquisition System , 2015, BIOSTEC 2015.

[16]  Ki-Young Shin,et al.  Development of a Radial Pulse Tonometric (RPT) Sensor with a Temperature Compensation Mechanism , 2013, Sensors.

[17]  Minvydas Ragulskis,et al.  Validation of Noninvasive MOEMS-Assisted Measurement System Based on CCD Sensor for Radial Pulse Analysis , 2013, Sensors.

[18]  Hui-yan Wang,et al.  A model for automatic identification of human pulse signals , 2008 .

[19]  David Zhang,et al.  Multiscale Sample Entropy Analysis of Wrist Pulse Blood Flow Signal for Disease Diagnosis , 2012, IScIDE.

[20]  David Zhang,et al.  Combination of Heterogeneous Features for Wrist Pulse Blood Flow Signal Diagnosis via Multiple Kernel Learning , 2012, IEEE Transactions on Information Technology in Biomedicine.

[21]  David Zhang,et al.  Wrist pulse signal diagnosis using modified Gaussian models and Fuzzy C-Means classification. , 2009, Medical engineering & physics.

[22]  Dingchang Zheng,et al.  Modeling carotid and radial artery pulse pressure waveforms by curve fitting with Gaussian functions , 2013, Biomed. Signal Process. Control..

[23]  Arthur de Sá Ferreira,et al.  Resonance phenomenon during wrist pulse-taking: A stochastic simulation, model-based study of the 'pressing with one finger' technique , 2013, Biomed. Signal Process. Control..

[24]  David Zhang,et al.  A robust signal preprocessing framework for wrist pulse analysis , 2016, Biomed. Signal Process. Control..

[25]  Ching-Hsing Luo,et al.  Using an array sensor to determine differences in pulse diagnosis—Three positions and nine indicators , 2014 .

[26]  Geyong Min,et al.  Advanced internet of things for personalised healthcare systems: A survey , 2017, Pervasive Mob. Comput..

[27]  Ching-Hsing Luo,et al.  Non-invasive holistic health measurements using pulse diagnosis: I. Validation by three-dimensional pulse mapping , 2016 .