Talukder B M S Bahar, Jovanov Emil, Schwebel David C, Evans W Douglas
Annu Int Conf IEEE Eng Med Biol Soc. 2018 Jul;2018:5142-5145. doi: 10.1109/EMBC.2018.8513459.
Unintentional child poisoning represents an increasingly important health issue in the United States and worldwide, partially due to increased use of drugs and food supplements. Biometric authentication is complex for pill bottles, but we propose a new method of user identification using touch capacitance during bottle-opening attempts. A smart pill bottle could generate an immediate warning to deter a child from opening the bottle and send an alert to parents/guardians. In this paper, we present principle of operation and implementation of a prototype "safe bottle We present the results of pilot testing with 5 adults and 3 children using support vector machine (SVM) and neural network (NN). From 232 bottle-opening events, our optimized NN generated no false detections of children as adults and four false detections of adults as children. Preliminary results indicate that smart pill bottles can be used to reliably detect children trying to open pill bottles and reduce risk of child-poisoning events.
在美国乃至全球，儿童意外中毒已成为一个日益重要的健康问题，部分原因是药品和食品补充剂的使用增加。对于药瓶而言，生物特征认证较为复杂，但我们提出了一种在尝试打开药瓶时利用触摸电容进行用户识别的新方法。智能药瓶可以立即发出警告，以阻止儿童打开药瓶，并向家长/监护人发送警报。在本文中，我们介绍了一款原型“安全药瓶”的工作原理和实现方法。我们展示了使用支持向量机（SVM）和神经网络（NN）对5名成年人和3名儿童进行试点测试的结果。在232次开瓶事件中，我们优化后的神经网络没有将儿童误检测为成年人，但有4次将成年人误检测为儿童。初步结果表明，智能药瓶可用于可靠地检测试图打开药瓶的儿童，并降低儿童中毒事件的风险。
