Personal Identification Using a Ballistocardiogram During Urination Obtained from a Toilet Seat
Personal Identification Using a Ballistocardiogram During Urination Obtained from a Toilet Seat
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DOI：
10.14326/abe.9.233
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
A. Nakagawa;Juhyon Kim;K. Nakajima
中科院分区：
文献类型：
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作者：
A. Nakagawa;Juhyon Kim;K. Nakajima
许多传感器已经被开发出来，用来测量厕所里的生理信息，用于医疗管理和疾病预防。这些传感器需要个人识别来对厕所使用者进行分类，假设有几个人使用同一个厕所。我们的目标是提供基于从马桶座圈获得的心血管生理信息的生物识别技术。与之前的研究一样，通过马桶座圈测量心电图，并进行个人识别。在这项研究中，我们开发了一种使用安装在马桶座下面的两个振动传感器的弹道心动图（BCG）监测系统。我们记录了7名健康男性排尿时的70个bcg。bgs的H、I、J、K、L峰清晰可见。从BCG的峰值中计算出振幅和间隔等26个特征。利用马氏距离进行个人识别，计算识别准确率和等误差率。平均识别准确率为92.2%，平均EER为34.1%。虽然EER不够低，但平均精度表明，使用马桶座圈的方法可以为医疗保健系统的应用提供足够的生物识别信息。
Many sensors have been developed to measure physiological information in the toilet for healthcare management and disease prevention. These sensors require personal identi cation to classify toilet users, assuming that several people use the same toilet. We aimed to provide biometrics based on cardiovascular physiological information obtained from a toilet seat. An electrocardiogram was measured by the toilet seat, and personal identi cation was performed, as in the previous study. In this study, we developed a ballistocardiographic (BCG) monitoring system using two vibration sensors installed beneath a toilet seat. We recorded 70 BCGs from seven healthy males during their urination. Peaks H, I, J, K, and L of the BCGs were clearly obtained. Twenty-six features such as amplitude and interval were calculated from the BCG peaks. Personal identi cation was performed using the Mahalanobis distance, and the accuracy of identi cation and equal error rate (EER) were calculated. The average identi cation accuracy was found to be 92.2%, and the average EER was found to be 34.1%. Although the EER was not suf ciently low, the average accuracy suggested that the proposed method using a toilet seat could provide adequate biometrics for application in the healthcare system.