FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4318203471> ?p ?o ?g. }

• W4318203471 endingPage "70" @default.
• W4318203471 startingPage "70" @default.
• W4318203471 abstract "Radial pulse signals are produced by the periodic ejection of blood from the heart, and physiological and pathological information of the human body can be analyzed by extracting the time-domain characteristics of pulse waves. However, since pulse signals are weak physiological signals on the body surface and complex, the acquisition of pulse characteristics using the traditional curvature method will produce a large error, which cannot meet the needs of pulse wave analysis in current clinical practice. To solve this problem, a multi-morphological pulse signal feature recognition algorithm based on the one-dimensional deep convolutional neural network (1D-DCNN) model is proposed. We used the multi-channel pulse diagnosis instrument independently developed by the team to collect radial pulse signals under continuous pressure of the test subjects and collected 115 subjects and extracted a total of 1300 single-cycle pulse signals and then divided these pulse signals into 6 different forms. Five types of pulse signal time-domain feature points were labeled, and five independent feature point datasets were labeled and formed five customized neural network models that were generated to train and identify the pulse feature point datasets independently. The results show that the correction coefficient (Radjusted2) of the multi-class pulse signal processing algorithm proposed in this paper for each type of feature point recognition reaches more than 0.92. The performance is significantly better than that of the traditional curvature method, which shows the accuracy and superiority of the proposed method. Therefore, the multi-class pulse signal characteristic parameter recognition model based on the 1D-DCNN model proposed in this paper can efficiently and accurately identify pulse time-domain characteristic parameters, which can be applied to discriminate time-domain pulse information in clinical practice and assist doctors in diagnosis." @default.
• W4318203471 created "2023-01-27" @default.
• W4318203471 creator A5005592260 @default.
• W4318203471 creator A5014194940 @default.
• W4318203471 creator A5015227833 @default.
• W4318203471 creator A5029722566 @default.
• W4318203471 creator A5038641400 @default.
• W4318203471 creator A5071672663 @default.
• W4318203471 creator A5080753060 @default.
• W4318203471 date "2023-01-26" @default.
• W4318203471 modified "2023-10-01" @default.
• W4318203471 title "Multi-Morphological Pulse Signal Feature Point Recognition Based on One-Dimensional Deep Convolutional Neural Network" @default.
• W4318203471 cites W1770625086 @default.
• W4318203471 cites W1998580216 @default.
• W4318203471 cites W2054077201 @default.
• W4318203471 cites W2132863420 @default.
• W4318203471 cites W2153896792 @default.
• W4318203471 cites W2181788522 @default.
• W4318203471 cites W2304049454 @default.
• W4318203471 cites W2763005247 @default.
• W4318203471 cites W2803284435 @default.
• W4318203471 cites W2900228664 @default.
• W4318203471 cites W2913146881 @default.
• W4318203471 cites W2969170900 @default.
• W4318203471 cites W2980127992 @default.
• W4318203471 cites W2981099508 @default.
• W4318203471 cites W2996132234 @default.
• W4318203471 cites W2999055219 @default.
• W4318203471 cites W3005744353 @default.
• W4318203471 cites W3025048319 @default.
• W4318203471 cites W3034167235 @default.
• W4318203471 cites W3082880506 @default.
• W4318203471 doi "https://doi.org/10.3390/info14020070" @default.
• W4318203471 hasPublicationYear "2023" @default.
• W4318203471 type Work @default.
• W4318203471 citedByCount "0" @default.
• W4318203471 crossrefType "journal-article" @default.
• W4318203471 hasAuthorship W4318203471A5005592260 @default.
• W4318203471 hasAuthorship W4318203471A5014194940 @default.
• W4318203471 hasAuthorship W4318203471A5015227833 @default.
• W4318203471 hasAuthorship W4318203471A5029722566 @default.
• W4318203471 hasAuthorship W4318203471A5038641400 @default.
• W4318203471 hasAuthorship W4318203471A5071672663 @default.
• W4318203471 hasAuthorship W4318203471A5080753060 @default.
• W4318203471 hasBestOaLocation W43182034711 @default.
• W4318203471 hasConcept C103824480 @default.
• W4318203471 hasConcept C104267543 @default.
• W4318203471 hasConcept C134652429 @default.
• W4318203471 hasConcept C138885662 @default.
• W4318203471 hasConcept C153180895 @default.
• W4318203471 hasConcept C154945302 @default.
• W4318203471 hasConcept C172321821 @default.
• W4318203471 hasConcept C195065555 @default.
• W4318203471 hasConcept C199360897 @default.
• W4318203471 hasConcept C2524010 @default.
• W4318203471 hasConcept C2776401178 @default.
• W4318203471 hasConcept C2779843651 @default.
• W4318203471 hasConcept C2780167933 @default.
• W4318203471 hasConcept C28719098 @default.
• W4318203471 hasConcept C31972630 @default.
• W4318203471 hasConcept C33923547 @default.
• W4318203471 hasConcept C41008148 @default.
• W4318203471 hasConcept C41895202 @default.
• W4318203471 hasConcept C50644808 @default.
• W4318203471 hasConcept C52622490 @default.
• W4318203471 hasConcept C554190296 @default.
• W4318203471 hasConcept C76155785 @default.
• W4318203471 hasConcept C81363708 @default.
• W4318203471 hasConcept C94915269 @default.
• W4318203471 hasConceptScore W4318203471C103824480 @default.
• W4318203471 hasConceptScore W4318203471C104267543 @default.
• W4318203471 hasConceptScore W4318203471C134652429 @default.
• W4318203471 hasConceptScore W4318203471C138885662 @default.
• W4318203471 hasConceptScore W4318203471C153180895 @default.
• W4318203471 hasConceptScore W4318203471C154945302 @default.
• W4318203471 hasConceptScore W4318203471C172321821 @default.
• W4318203471 hasConceptScore W4318203471C195065555 @default.
• W4318203471 hasConceptScore W4318203471C199360897 @default.
• W4318203471 hasConceptScore W4318203471C2524010 @default.
• W4318203471 hasConceptScore W4318203471C2776401178 @default.
• W4318203471 hasConceptScore W4318203471C2779843651 @default.
• W4318203471 hasConceptScore W4318203471C2780167933 @default.
• W4318203471 hasConceptScore W4318203471C28719098 @default.
• W4318203471 hasConceptScore W4318203471C31972630 @default.
• W4318203471 hasConceptScore W4318203471C33923547 @default.
• W4318203471 hasConceptScore W4318203471C41008148 @default.
• W4318203471 hasConceptScore W4318203471C41895202 @default.
• W4318203471 hasConceptScore W4318203471C50644808 @default.
• W4318203471 hasConceptScore W4318203471C52622490 @default.
• W4318203471 hasConceptScore W4318203471C554190296 @default.
• W4318203471 hasConceptScore W4318203471C76155785 @default.
• W4318203471 hasConceptScore W4318203471C81363708 @default.
• W4318203471 hasConceptScore W4318203471C94915269 @default.
• W4318203471 hasFunder F4320326972 @default.
• W4318203471 hasIssue "2" @default.
• W4318203471 hasLocation W43182034711 @default.
• W4318203471 hasOpenAccess W4318203471 @default.
• W4318203471 hasPrimaryLocation W43182034711 @default.

• next