Min Zhang;Yanmei Wang;Peilun Li;Yadan Zhang;Min Xiang
{"title":"基于cram<s:1> - rao界的心磁传感器阵列心脏源定位性能评价","authors":"Min Zhang;Yanmei Wang;Peilun Li;Yadan Zhang;Min Xiang","doi":"10.1109/TIM.2025.3604125","DOIUrl":null,"url":null,"abstract":"Magnetocardiography (MCG) source localization plays a key role in estimating cardiac electrical activity and identifying abnormal activity locations for disease diagnosis. To improve estimation accuracy in clinical applications, evaluating the performance of MCG sensor arrays is crucial for selecting optimal configurations. Such evaluations have traditionally been conducted through various metrics. However, these metrics depend on specific estimation algorithms and fail to directly reflect how the sensor array influences the variance of parameter estimation. Furthermore, the diversity of estimation algorithms hinders the establishment of uniform assessment criteria. To overcome these challenges, we present an evaluation method for MCG arrays focused on minimizing the variance in source parameter estimation. The method leverages the Cramér–Rao bound (CRB), a theoretical limit on the variance of unbiased estimators and independent of the employed algorithm. Aided by the boundary element method (BEM), we derive the CRB framework for estimating cardiac source parameters using MCG data and quantify the effect of adding sensors on the CRB. In addition, we utilize the CRB to evaluate the performance of MCG arrays measuring different magnetic field components, quantifying the advantages of 3-D vector field measurements for source estimation. Compared to conventional radial measurements, 3-D vector measurements reduce the equivalent uncertainty radius by more than 25.62%. Finally, we apply the approach to optimize sensor arrangements when the number of sensors is limited. Overall, our results show that the CRB effectively evaluates MCG arrays across diverse configurations, making it applicable to various clinical and engineering applications.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-10"},"PeriodicalIF":5.9000,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Performance Evaluation of Magnetocardiography Sensor Arrays via Cramér–Rao Bound for Cardiac Source Localization\",\"authors\":\"Min Zhang;Yanmei Wang;Peilun Li;Yadan Zhang;Min Xiang\",\"doi\":\"10.1109/TIM.2025.3604125\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Magnetocardiography (MCG) source localization plays a key role in estimating cardiac electrical activity and identifying abnormal activity locations for disease diagnosis. To improve estimation accuracy in clinical applications, evaluating the performance of MCG sensor arrays is crucial for selecting optimal configurations. Such evaluations have traditionally been conducted through various metrics. However, these metrics depend on specific estimation algorithms and fail to directly reflect how the sensor array influences the variance of parameter estimation. Furthermore, the diversity of estimation algorithms hinders the establishment of uniform assessment criteria. To overcome these challenges, we present an evaluation method for MCG arrays focused on minimizing the variance in source parameter estimation. The method leverages the Cramér–Rao bound (CRB), a theoretical limit on the variance of unbiased estimators and independent of the employed algorithm. Aided by the boundary element method (BEM), we derive the CRB framework for estimating cardiac source parameters using MCG data and quantify the effect of adding sensors on the CRB. In addition, we utilize the CRB to evaluate the performance of MCG arrays measuring different magnetic field components, quantifying the advantages of 3-D vector field measurements for source estimation. Compared to conventional radial measurements, 3-D vector measurements reduce the equivalent uncertainty radius by more than 25.62%. Finally, we apply the approach to optimize sensor arrangements when the number of sensors is limited. Overall, our results show that the CRB effectively evaluates MCG arrays across diverse configurations, making it applicable to various clinical and engineering applications.\",\"PeriodicalId\":13341,\"journal\":{\"name\":\"IEEE Transactions on Instrumentation and Measurement\",\"volume\":\"74 \",\"pages\":\"1-10\"},\"PeriodicalIF\":5.9000,\"publicationDate\":\"2025-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Instrumentation and Measurement\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/11146531/\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Instrumentation and Measurement","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/11146531/","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Performance Evaluation of Magnetocardiography Sensor Arrays via Cramér–Rao Bound for Cardiac Source Localization
Magnetocardiography (MCG) source localization plays a key role in estimating cardiac electrical activity and identifying abnormal activity locations for disease diagnosis. To improve estimation accuracy in clinical applications, evaluating the performance of MCG sensor arrays is crucial for selecting optimal configurations. Such evaluations have traditionally been conducted through various metrics. However, these metrics depend on specific estimation algorithms and fail to directly reflect how the sensor array influences the variance of parameter estimation. Furthermore, the diversity of estimation algorithms hinders the establishment of uniform assessment criteria. To overcome these challenges, we present an evaluation method for MCG arrays focused on minimizing the variance in source parameter estimation. The method leverages the Cramér–Rao bound (CRB), a theoretical limit on the variance of unbiased estimators and independent of the employed algorithm. Aided by the boundary element method (BEM), we derive the CRB framework for estimating cardiac source parameters using MCG data and quantify the effect of adding sensors on the CRB. In addition, we utilize the CRB to evaluate the performance of MCG arrays measuring different magnetic field components, quantifying the advantages of 3-D vector field measurements for source estimation. Compared to conventional radial measurements, 3-D vector measurements reduce the equivalent uncertainty radius by more than 25.62%. Finally, we apply the approach to optimize sensor arrangements when the number of sensors is limited. Overall, our results show that the CRB effectively evaluates MCG arrays across diverse configurations, making it applicable to various clinical and engineering applications.
期刊介绍:
Papers are sought that address innovative solutions to the development and use of electrical and electronic instruments and equipment to measure, monitor and/or record physical phenomena for the purpose of advancing measurement science, methods, functionality and applications. The scope of these papers may encompass: (1) theory, methodology, and practice of measurement; (2) design, development and evaluation of instrumentation and measurement systems and components used in generating, acquiring, conditioning and processing signals; (3) analysis, representation, display, and preservation of the information obtained from a set of measurements; and (4) scientific and technical support to establishment and maintenance of technical standards in the field of Instrumentation and Measurement.