{"title":"一个基于matlab的工具,用于将fNIRS时间序列数据转换为homer3兼容格式","authors":"Chao Wang , Xiaojun Cheng , Shichao Liu","doi":"10.1016/j.neuri.2025.100205","DOIUrl":null,"url":null,"abstract":"<div><div>Functional Near-Infrared Spectroscopy (fNIRS) is increasingly used in cognitive neuroscience and clinical research, yet preprocessing raw time-series data remains challenging. We introduce a lightweight MATLAB tool to automate the conversion of fNIRS data into Homer3-compatible “*.nirs” format. Our solution targets non-SNIRF raw data and offers a standardized, user-friendly method to streamline fNIRS data preparation. This Technical Note describes the tool's design, workflow, and potential improvements for future development.</div></div>","PeriodicalId":74295,"journal":{"name":"Neuroscience informatics","volume":"5 2","pages":"Article 100205"},"PeriodicalIF":0.0000,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A MATLAB-based tool for converting fNIRS time-series data to Homer3-compatible formats\",\"authors\":\"Chao Wang , Xiaojun Cheng , Shichao Liu\",\"doi\":\"10.1016/j.neuri.2025.100205\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Functional Near-Infrared Spectroscopy (fNIRS) is increasingly used in cognitive neuroscience and clinical research, yet preprocessing raw time-series data remains challenging. We introduce a lightweight MATLAB tool to automate the conversion of fNIRS data into Homer3-compatible “*.nirs” format. Our solution targets non-SNIRF raw data and offers a standardized, user-friendly method to streamline fNIRS data preparation. This Technical Note describes the tool's design, workflow, and potential improvements for future development.</div></div>\",\"PeriodicalId\":74295,\"journal\":{\"name\":\"Neuroscience informatics\",\"volume\":\"5 2\",\"pages\":\"Article 100205\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-05-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neuroscience informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2772528625000202\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neuroscience informatics","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772528625000202","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A MATLAB-based tool for converting fNIRS time-series data to Homer3-compatible formats
Functional Near-Infrared Spectroscopy (fNIRS) is increasingly used in cognitive neuroscience and clinical research, yet preprocessing raw time-series data remains challenging. We introduce a lightweight MATLAB tool to automate the conversion of fNIRS data into Homer3-compatible “*.nirs” format. Our solution targets non-SNIRF raw data and offers a standardized, user-friendly method to streamline fNIRS data preparation. This Technical Note describes the tool's design, workflow, and potential improvements for future development.
Neuroscience informaticsSurgery, Radiology and Imaging, Information Systems, Neurology, Artificial Intelligence, Computer Science Applications, Signal Processing, Critical Care and Intensive Care Medicine, Health Informatics, Clinical Neurology, Pathology and Medical Technology