Fluid intake is important for people to maintain body fluid homeostasis. Inadequate fluid intake leads to negative health consequences, such as headache, dizziness and urolithiasis. However, people in busy lifestyles usually forget to drink sufficient water and neglect the importance of fluid intake. Fluid intake management is important to assist people in adopting individual drinking behaviors. This work aims to propose a fluid intake monitoring system with a wearable inertial sensor using a hierarchical approach to detect drinking activities, recognize sip gestures and estimate fluid intake amount. Additionally, container-dependent amount estimation models are developed due to the influence of containers on fluid intake amount. The proposed fluid intake monitoring system could achieve 94.42% accuracy, 90.17% sensitivity, and 40.11% mean absolute percentage error (MAPE) for drinking detection, gesture spotting and amount estimation, respectively. Particularly, MAPE of amount estimation is improved approximately 10% compared to the typical approaches. The results have demonstrated the feasibility and the effectiveness of the proposed fluid intake monitoring system.

中文翻译：

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使用可穿戴惯性传感器进行液体摄入量管理的液体摄入量监测系统

液体摄入对于维持人体液的体内平衡非常重要。液体摄入不足会导致负面的健康后果，例如头痛，头晕和尿路结石。但是，忙碌的生活方式的人们通常会忘记喝足够的水，而忽略了摄入液体的重要性。液体摄入量管理对协助人们采取个体饮酒行为很重要。这项工作旨在提出一种带有可穿戴式惯性传感器的液体摄入量监控系统，该系统采用分层方法来检测饮酒活动，识别饮酒姿势并估计液体摄入量。另外，由于容器对流体摄入量的影响，开发了与容器有关的量估计模型。拟议的进水监控系统可以达到94.42％的准确度，90.17％的灵敏度和40。分别有11％的平均绝对百分比误差（MAPE）用于饮酒检测，手势识别和量估计。特别地，与典型方法相比，量估计的MAPE提高了大约10％。结果证明了所提出的流体摄入监测系统的可行性和有效性。