{"title":"基于超宽频雷达的近场眼睑运动感应","authors":"Sunghwa Lee, Jiwon Seo","doi":"10.23919/ICCAS.2017.8204277","DOIUrl":null,"url":null,"abstract":"In this paper, we introduce a method for sensing intentional eyelid movement using an impulse radio ultra-wideband (IR-UWB) radar. Since it is the first step of the study, we assume that eyes are in the near-field and all the motions, except eyelid movement, are fixed. The measurement of eyelid movement can be utilized in a human computer interface or for the recognition of a driver's drowsiness. If the eyelids move up or down, the amplitude and frequency of radar signals change. We can observe these changes in a three-dimensional graph of raw radar data. Intentional eyelid movements produce some peaks or nulls on the graph. We used two methods to analyze the patterns of eyelid movement. Both methods involve fast Fourier transform (FFT) and exploit a pulse Doppler processing technique of radar signals. Thus, we can calculate the frequency of intentional eyelid movement using these methods. The calculated frequency corresponds to the number of peaks in the raw radar graph.","PeriodicalId":140598,"journal":{"name":"2017 17th International Conference on Control, Automation and Systems (ICCAS)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"IR-UWB radar based near-field intentional eyelid movement sensing under fixed head and body motions\",\"authors\":\"Sunghwa Lee, Jiwon Seo\",\"doi\":\"10.23919/ICCAS.2017.8204277\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we introduce a method for sensing intentional eyelid movement using an impulse radio ultra-wideband (IR-UWB) radar. Since it is the first step of the study, we assume that eyes are in the near-field and all the motions, except eyelid movement, are fixed. The measurement of eyelid movement can be utilized in a human computer interface or for the recognition of a driver's drowsiness. If the eyelids move up or down, the amplitude and frequency of radar signals change. We can observe these changes in a three-dimensional graph of raw radar data. Intentional eyelid movements produce some peaks or nulls on the graph. We used two methods to analyze the patterns of eyelid movement. Both methods involve fast Fourier transform (FFT) and exploit a pulse Doppler processing technique of radar signals. Thus, we can calculate the frequency of intentional eyelid movement using these methods. The calculated frequency corresponds to the number of peaks in the raw radar graph.\",\"PeriodicalId\":140598,\"journal\":{\"name\":\"2017 17th International Conference on Control, Automation and Systems (ICCAS)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 17th International Conference on Control, Automation and Systems (ICCAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/ICCAS.2017.8204277\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 17th International Conference on Control, Automation and Systems (ICCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/ICCAS.2017.8204277","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
IR-UWB radar based near-field intentional eyelid movement sensing under fixed head and body motions
In this paper, we introduce a method for sensing intentional eyelid movement using an impulse radio ultra-wideband (IR-UWB) radar. Since it is the first step of the study, we assume that eyes are in the near-field and all the motions, except eyelid movement, are fixed. The measurement of eyelid movement can be utilized in a human computer interface or for the recognition of a driver's drowsiness. If the eyelids move up or down, the amplitude and frequency of radar signals change. We can observe these changes in a three-dimensional graph of raw radar data. Intentional eyelid movements produce some peaks or nulls on the graph. We used two methods to analyze the patterns of eyelid movement. Both methods involve fast Fourier transform (FFT) and exploit a pulse Doppler processing technique of radar signals. Thus, we can calculate the frequency of intentional eyelid movement using these methods. The calculated frequency corresponds to the number of peaks in the raw radar graph.