{"title":"Advanced prediction method of biological tissue mechanical response based on hybrid prediction model.","authors":"Jing Yang, Changwei Shi, Lihua Yao, Yixun Fang, Yiming Huang","doi":"10.1177/09544119251327646","DOIUrl":null,"url":null,"abstract":"<p><p>The mechanical response of biological tissue is an important basis for evaluating its state during the surgical operation. Accurate prediction of mechanical response is helpful to improve the precision of surgical operation. In this paper, An advanced prediction method based on hybrid prediction model is proposed and used to predict the mechanical response of soft tissue. Firstly, the simulation model of soft tissue indentation experiment was established to obtain the mechanical response under continuous loading condition. The mechanical response of kindy tissue under discontinuous loading was obtained by the actual indentation experiment. Secondly, the mechanical response is predicted and the influence of loading parameters on the prediction accuracy is analyzed. The mechanical response under continuous loading was obtained by simulation, and the mechanical response under non-continuous loading was obtained by indentation experiment. The proposed advanced prediction method is verified by the obtained mechanical responses. The results show that the proposed method can predict the mechanical response of soft tissue well. The proposed prediction algorithm is helpful to predict the mechanical response in advance and avoid the potential tissue damage caused by surgical operation.</p>","PeriodicalId":20666,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine","volume":" ","pages":"9544119251327646"},"PeriodicalIF":1.7000,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1177/09544119251327646","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
引用次数: 0
Abstract
The mechanical response of biological tissue is an important basis for evaluating its state during the surgical operation. Accurate prediction of mechanical response is helpful to improve the precision of surgical operation. In this paper, An advanced prediction method based on hybrid prediction model is proposed and used to predict the mechanical response of soft tissue. Firstly, the simulation model of soft tissue indentation experiment was established to obtain the mechanical response under continuous loading condition. The mechanical response of kindy tissue under discontinuous loading was obtained by the actual indentation experiment. Secondly, the mechanical response is predicted and the influence of loading parameters on the prediction accuracy is analyzed. The mechanical response under continuous loading was obtained by simulation, and the mechanical response under non-continuous loading was obtained by indentation experiment. The proposed advanced prediction method is verified by the obtained mechanical responses. The results show that the proposed method can predict the mechanical response of soft tissue well. The proposed prediction algorithm is helpful to predict the mechanical response in advance and avoid the potential tissue damage caused by surgical operation.
期刊介绍:
The Journal of Engineering in Medicine is an interdisciplinary journal encompassing all aspects of engineering in medicine. The Journal is a vital tool for maintaining an understanding of the newest techniques and research in medical engineering.