MedRem: an interactive medication reminder and tracking system on wrist devices
MedRem: an interactive medication reminder and tracking system on wrist devices
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MedRem：手腕设备上的交互式药物提醒和跟踪系统
DOI：
10.1109/wh.2016.7764555
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
J. Stankovic
中科院分区：
文献类型：
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作者：
M. A. S. Mondol;I. Emi;J. Stankovic
药物依从性是有效健康结果的关键。药物依从性差的主要原因之一是健忘，提醒系统通常用于解决这个问题。本文介绍了MedRem，一种新型的可穿戴手腕设备上的药物提醒和跟踪系统。该系统是方便和互动的，它是丰富的几个有用的功能。为了解决手腕设备的微小显示尺寸的限制，MedRem将语音识别和文本到语音功能沿着智能界面设计。用户使用语音命令以及使用设备上可用的显示器与系统交互。基于字典的训练方法被用于最先进的语音识别系统的顶部，以减少识别来自用户的命令的错误。该系统的评估为母语和非母语的英语。当使用现成的语音识别系统时，识别语音命令的错误率对于母语者和非母语者分别为6.43%和20.9%。MedRem通过基于字典的训练方法将两种类型的用户的错误减少到几乎为零。平均而言，仅需要1.25和15个训练命令，以实现本族语和非本族语者的这种性能，分别。
Medication adherence is pivotal for effective health outcomes. One of the main reasons behind poor medication adherence is forgetfulness, and reminder systems are often used in addressing the problem. This paper presents MedRem, a novel medication reminder and tracking system on wearable wrist devices. The system is handy and interactive, and it is enriched with several useful features. To address the limitations of the tiny display size of the wrist devices, MedRem incorporates speech recognition and text-to-speech features along with clever interface design. Users interact with the system using voice commands as well as using the display available on the device. A dictionary based training approach is used on top of the state of the art speech recognition systems to reduce the errors in recognizing the commands from the users. The system is evaluated for both native and non-native English speakers. The error rates for recognizing voice commands are 6.43% and 20.9% for the native and the non-native speakers, respectively, when a off-the-shelf speech recognition system is used. MedRem reduces the error to nearly zero for both types of users through a dictionary based training approach. On average, only 1.25 and 15 training commands are required to achieve this performance for the native and the non-native speakers, respectively.