M. Abdelhady, J. Han, S. Majerus, L. Brody, M. Damaser
{"title":"从单通道膀胱压力记录估计逼尿肌压力","authors":"M. Abdelhady, J. Han, S. Majerus, L. Brody, M. Damaser","doi":"10.1109/SPMB55497.2022.10014843","DOIUrl":null,"url":null,"abstract":"Cystometry measures the behavior of the bladder and is frequently used to evaluate lower urinary tract abnormalities. Cystometry is conducted using two catheters, one in the bladder and the other in the vagina or rectum, which increases discomfort and complexity of the test. In this work we evaluated a method to estimate detrusor pressure (PDET), the pressure generated by a bladder contraction, from only a single catheter measuring vesical pressure (PVES). Using twenty urodynamic studies, we used statistical inference and wavelet multiresolution analysis to maximize the correlation coefficient $(R)$ between estimated PDET and calculated PDET after detecting and eliminating artifacts. Moreover, the estimator design considered a prospective real-time implementation. Root main square (RMS) error and correlation coefficient were used to evaluate algorithm accuracy in estimating $\\mathbf{P}_{\\text{DET}}$, while a statistical F -score evaluated the accuracy of artifact detection. The output of the proposed estimator compared with calculated PDET, and overall estimation performance showed that $RMS=10.7\\pm 2.1\\ \\text{cmH}_{2}\\mathrm{O}$ and $R=0.88\\pm$ 0.6 $(\\mathrm{N}=20)$. Moreover, detection accuracy for cough and Valsalva events were 99.5% and 84.30/0, respectively. We conclude that estimating PDET from PVES only is feasible making single channel cystometry a possibility.","PeriodicalId":261445,"journal":{"name":"2022 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Detrusor Pressure Estimation from Single Channel Bladder Pressure Recordings\",\"authors\":\"M. Abdelhady, J. Han, S. Majerus, L. Brody, M. Damaser\",\"doi\":\"10.1109/SPMB55497.2022.10014843\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cystometry measures the behavior of the bladder and is frequently used to evaluate lower urinary tract abnormalities. Cystometry is conducted using two catheters, one in the bladder and the other in the vagina or rectum, which increases discomfort and complexity of the test. In this work we evaluated a method to estimate detrusor pressure (PDET), the pressure generated by a bladder contraction, from only a single catheter measuring vesical pressure (PVES). Using twenty urodynamic studies, we used statistical inference and wavelet multiresolution analysis to maximize the correlation coefficient $(R)$ between estimated PDET and calculated PDET after detecting and eliminating artifacts. Moreover, the estimator design considered a prospective real-time implementation. Root main square (RMS) error and correlation coefficient were used to evaluate algorithm accuracy in estimating $\\\\mathbf{P}_{\\\\text{DET}}$, while a statistical F -score evaluated the accuracy of artifact detection. The output of the proposed estimator compared with calculated PDET, and overall estimation performance showed that $RMS=10.7\\\\pm 2.1\\\\ \\\\text{cmH}_{2}\\\\mathrm{O}$ and $R=0.88\\\\pm$ 0.6 $(\\\\mathrm{N}=20)$. Moreover, detection accuracy for cough and Valsalva events were 99.5% and 84.30/0, respectively. We conclude that estimating PDET from PVES only is feasible making single channel cystometry a possibility.\",\"PeriodicalId\":261445,\"journal\":{\"name\":\"2022 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPMB55497.2022.10014843\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPMB55497.2022.10014843","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detrusor Pressure Estimation from Single Channel Bladder Pressure Recordings
Cystometry measures the behavior of the bladder and is frequently used to evaluate lower urinary tract abnormalities. Cystometry is conducted using two catheters, one in the bladder and the other in the vagina or rectum, which increases discomfort and complexity of the test. In this work we evaluated a method to estimate detrusor pressure (PDET), the pressure generated by a bladder contraction, from only a single catheter measuring vesical pressure (PVES). Using twenty urodynamic studies, we used statistical inference and wavelet multiresolution analysis to maximize the correlation coefficient $(R)$ between estimated PDET and calculated PDET after detecting and eliminating artifacts. Moreover, the estimator design considered a prospective real-time implementation. Root main square (RMS) error and correlation coefficient were used to evaluate algorithm accuracy in estimating $\mathbf{P}_{\text{DET}}$, while a statistical F -score evaluated the accuracy of artifact detection. The output of the proposed estimator compared with calculated PDET, and overall estimation performance showed that $RMS=10.7\pm 2.1\ \text{cmH}_{2}\mathrm{O}$ and $R=0.88\pm$ 0.6 $(\mathrm{N}=20)$. Moreover, detection accuracy for cough and Valsalva events were 99.5% and 84.30/0, respectively. We conclude that estimating PDET from PVES only is feasible making single channel cystometry a possibility.