Department of Biomedical Engineering, National Yang-Ming University, Taipei 112, Taiwan.
Research Center for Information Technology Innovation, Academia Sinica, Taipei 115, Taiwan.
Sensors (Basel). 2020 Nov 22;20(22):6682. doi: 10.3390/s20226682.
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.
液体摄入对于维持人体体液平衡非常重要。液体摄入不足会导致头痛、头晕和尿路结石等健康问题。然而，生活节奏忙碌的人群通常会忘记饮用足够的水，忽视液体摄入的重要性。液体摄入管理对于帮助人们养成个体饮水行为非常重要。本工作旨在提出一种使用分层方法的可穿戴惯性传感器的液体摄入监测系统，以检测饮水活动、识别饮水口型和估计液体摄入量。此外，由于容器对液体摄入量的影响，开发了依赖于容器的量估计模型。所提出的液体摄入监测系统在饮水检测、口型识别和量估计方面的准确率分别达到了 94.42%、90.17%和 40.11%，平均绝对百分比误差（MAPE）。特别是，与典型方法相比，量估计的 MAPE 提高了约 10%。研究结果表明，所提出的液体摄入监测系统具有可行性和有效性。
