{"title":"Doppler Sensor-Based Blink Duration Estimation by Spectrogram Analysis","authors":"Kohei Yamamoto, Kentaroh Toyoda, T. Ohtsuki","doi":"10.1109/ICC.2018.8422999","DOIUrl":null,"url":null,"abstract":"It is known that the blink duration is highly related to drowsiness, where the blink duration is the entire duration of one blink. Hence, it is important to measure the blink duration without any special wearable devices in various application, e.g., driver's monitoring. Although a Doppler sensor could be a key device to realize it, no such blink duration estimation method has been realized so far, since estimating the blink duration is difficult because of the low SNR (Signal to Noise Ratio) of the signal reflected from eyelids. In this paper, we propose a Doppler sensor-based method that estimates the duration, tblink, that is proportional to the actual blink duration. In the proposed method, a spectrogram is firstly calculated from a received signal, and then the timings when eyelids close and open are extracted from that. More specifically, tblink is calculated based on the center-of-gravity of the energy on a spectrogram. We conducted the experiments on five subjects to show the estimation accuracy of our proposed method. We confirmed that our method achieved the average correlation coefficient R of 0.95, furthermore, the average RMSE (Root Mean Square Error) of 46 ms.","PeriodicalId":387855,"journal":{"name":"2018 IEEE International Conference on Communications (ICC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Communications (ICC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICC.2018.8422999","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
It is known that the blink duration is highly related to drowsiness, where the blink duration is the entire duration of one blink. Hence, it is important to measure the blink duration without any special wearable devices in various application, e.g., driver's monitoring. Although a Doppler sensor could be a key device to realize it, no such blink duration estimation method has been realized so far, since estimating the blink duration is difficult because of the low SNR (Signal to Noise Ratio) of the signal reflected from eyelids. In this paper, we propose a Doppler sensor-based method that estimates the duration, tblink, that is proportional to the actual blink duration. In the proposed method, a spectrogram is firstly calculated from a received signal, and then the timings when eyelids close and open are extracted from that. More specifically, tblink is calculated based on the center-of-gravity of the energy on a spectrogram. We conducted the experiments on five subjects to show the estimation accuracy of our proposed method. We confirmed that our method achieved the average correlation coefficient R of 0.95, furthermore, the average RMSE (Root Mean Square Error) of 46 ms.