# A Simple AMC Antenna for Liquid Monitoring in an Infusion Bag
## 1 Introduction  
With the fast development of wireless communication and medical technologies, intelligent devices have been widely used for implant surgery [1, 2], medical assistance [3], and health monitoring [4, 5]. In a hospital, the monitoring of an infusion bag is essential to prevent the backflow of blood. Usually, patients check the state of the infusion bag by themselves, calling the nurse to change the infusion bag or remove the needle. However, patients in the ICU may not have the ability to check the status of infusion bags by themselves and therefore, need the help of others. This increases the working loads of the nurses who take care of numerous patients with dense infusion bags. Therefore, it is necessary to develop a reliable, efficient, and simple intelligent technology to monitor the state of infusion bags remotely, as shown in Figure 1.  
Figure 1: Infusion bags and the proposed sensor in an application scenario. The techniques for monitoring the liquid in infusion bags mainly include photoelectric sensors, image processing, and capacitive systems. The photoelectric approach utilizes optical sensors (e.g., an infrared transmitter and receiver), a microprocessor for data processing, and an alert system such as a buzzer or an LCD screen [6; 7; 8; 9; 10]. Wireless sensing enabled by Wi-Fi or SMS were proposed in [7; 8]. However, optical sensors may yield inaccuracies due to environmental variables. Enhancements in photoelectric sensing through image processing were explored in [11; 12], where computer vision analysis was employed to assess the liquid's state. This method, while precise, adds complexity through the necessary image processing modules and algorithm development, resulting in high costs. The capacitive detection methods used in [13; 14] determined liquid depletion by measuring the changes in capacitive voltage from the devices attached to or embedded in the infusion bags. With advancements in wireless sensing, recent works tried to exploit wireless signals. For example, microwave time-domain reflectometry (TDR) and radio-frequency (RF) signals are employed for liquid monitoring. A system combining microwave TDR measurements with non-invasive sensing elements for the automated monitoring of intravenous (IV) infusions was proposed in [15]. Additionally, RFID tag-based sensors have been proposed for monitoring IV fluid levels [16; 17; 18]. However, the above techniques all require complex and expensive supporting electronic equipment. Another proposed detection system, used in [19], estimates liquid weight using sensor nodes to activate alarms, though the diverse weight of different infusion bags could be challenging for calibration. In liquid monitoring, antennas provide wireless sensing and communication within ISM bands like 2.4 GHz and 5.8 GHz, supporting global license-free operations and compatibility with Wi-Fi and Bluetooth [20; 21]. For example, a 2.4 GHz planar microstrip sensor [22] detects liquid adulteration such as that in milk by analysing dielectric permittivity changes. In [23], a microwave liquid detection method operating at 2.45 GHz employs an EBG structure for accurate liquid dielectric characterization. However, current technologies primarily focus on liquid levels, composition, or flow rates, rather than simply detecting the presence or absence of a liquid, and they are often complex, expensive, and sensitive to environmental conditions. AMC technology enhances radiation performance in electromagnetic devices, enabling the creation of high-sensitivity sensors with simple systems [24; 25; 26; 27; 28; 29; 30]. The AMC-based antenna sensor proposed in [27] achieved 1.89% sensitivity with an error rate below 3.516% in permittivity measurements. In [28], an AMC array antenna improved the gain, reduced the return loss, and improved the accuracy and sensitivity for the non-contact detection of water and ethanol in oil. Additionally, AMC structures also enhance sensor isolation from environmental interference [31; 32; 33].