A novel angle extremum maximum method for recognition of pulse wave feature points. (June 2020)

• Record Type: Journal Article
• Authors: Hou, Jiena; Zhang, Yitao; Zhang, Shaolong; Geng, Xingguang; Zhang, Jun; Chen, Chuanglu; Zhang, Haiying
• Is Part Of: Computer methods and programs in biomedicine. Volume 189(2020)
• Publication Date: 2020-06
• Subjects: Pulse waves -- Feature point recognition -- Mathematical model -- Angle curve -- PVDF sensor; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2020.105321
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: We propose a novel method for recognition of pulse wave feature points based on angle mapping, which can amplify the changes in pulse waveform and provide better noise immunity. The accuracy of this method is discussed by using approximate pulse wave and mathematical model. This method is an efficient choice for the identification of unobvious feature points. This method can provide threshold standard for existence of unobvious feature points. Abstract: Background and objectives: Pulse wave is one of the biomedical signals that has been studied over the past years. Accurate recognition of feature points is the basis of verifying the connections between pulse waves and certain diseases. Therefore, the aim of the study is to discuss the use of angle mapping on feature points recognition. Methods: The mathematical method is based on the application of angle curve with parameter " k " on pulse wave. The data used is collected by PVDF sensor. Approximate curve and mathematical model are used for the discussion of the influence of parameter k and pulse wave amplitude by numerical calculation. The conclusion drawn from the numerical solution is that when k changes to maximize the angle extremum value, the corresponding position of angle extremum point is the feature point position. For the sampling rate f = 455Hz in this paper, k can be taken from 5 to 15. Results: We present the recognition results of unobvious feature points based on the "angle extremum maximum method" and corresponding angle values. The results are compared with traditional methods and the determination of angle threshold value is discussed. Conclusions: This method can be used for accurate and efficient feature points identification, and it can be better applied to pulse waves with noise or unobvious feature points.