Department of Ingegneria Elettrica Elettronica ed Informatica, University of Catania, 95124 Catania, Italy.
Sensors (Basel). 2020 Sep 1;20(17):4954. doi: 10.3390/s20174954.
Population ageing is having a direct influence on serious health issues, including hampered mobility and physical decline. Good habits in performing physical activities, in addition to eating and drinking, are essential to improve the life quality of the elderly population. Technological solutions, aiming at increasing awareness or providing reminders to eat/drink regularly, can have a significant impact in this scenario. These solutions enable the possibility to constantly monitor deviations from users' normal behavior, thus allowing reminders to be provided to users/caregivers. In this context, this paper presents a radio-frequency identification (RFID) system to monitor user's habits, such as the use of food, beverages, and/or drugs. The device was optimized to fulfill specifications imposed by the addressed application. The approach could be extended for the monitoring of home appliances, environment exploitation, and activity rate. Advantages of the approach compared to other solutions, e.g., based on cameras, are related to the low level of invasiveness and flexibility of the adopted technology. A major contribution of this paper is related to the wide investigation of system behavior, which is aimed to define the optimal working conditions of the system, with regards to the power budget, user (antenna)-tag reading range, and the optimal inter-tag distance. To investigate the performance of the system in tag detection, experiments were performed in a scenario replicating a home environment. To achieve this aim, specificity and sensitivity indexes were computed to provide an objective evaluation of the system performance. For the case considered, if proper conditions are meet, a specificity value of 0.9 and a sensitivity value of 1 were estimated.
人口老龄化正对严重的健康问题产生直接影响，包括行动不便和身体衰退。良好的身体活动习惯，加上饮食，对于提高老年人口的生活质量至关重要。旨在提高意识或定期提供饮食提醒的技术解决方案在这种情况下可以产生重大影响。这些解决方案使我们能够持续监控用户正常行为的偏差情况，从而为用户/护理人员提供提醒。在这种情况下，本文提出了一种射频识别（RFID）系统来监测用户的习惯，例如食物、饮料和/或药物的使用情况。该设备经过优化，以满足所涉及应用程序的规范要求。该方法可以扩展到监测家用电器、环境利用和活动率。与基于摄像头的其他解决方案相比，该方法的优势在于所采用技术的低侵入性和灵活性。本文的一个主要贡献是对系统行为进行了广泛的调查，旨在确定系统的最佳工作条件，包括功率预算、用户（天线）-标签读取范围和最佳标签间距离。为了研究系统在标签检测方面的性能，在模拟家庭环境的场景中进行了实验。为了实现这一目标，计算了特异性和敏感性指数，以对系统性能进行客观评估。对于所考虑的情况，如果满足适当的条件，则估计特异性值为 0.9，敏感性值为 1。
