# A Review of Medication Adherence Monitoring Technologies +
## 4 A Review of Medication Adherence Monitoring Systems
### Vision-Based Systems  
Recently, research in computer vision and image processing has attracted much attention, leading to the development of many algorithms for human activity representation and classification [137]. So far, vision-based systems have been the basis for a number of important healthcare applications. In the context of human activity recognition within smart environments or \"Smart Homes\" [114], where ambient assistive living (AAL) technologies [2] exist; one choice for monitoring medication intake is to use vision modules for identifying and tracking inhabitants, motion, gestures, and subjects. In this section, we depict the current vision-based systems for medication intake monitoring and discuss their pros and cons. In [79], a computer vision system was proposed for monitoring medication habits. The system uses one camera installed in the medication area, which may include a group of medication bottles. The aim of this system was to track if the right medication is being taken by the user. In order for the system to work, it is required that only one user appears closely in the field of view of the camera during the medication taking session. Algorithms for skin color distinction have been used in order to distinguish between skin and non-skin colors. First, the systems extract all skin regions of the person in front of the camera. Then, this information is used for detecting hand/face (hand over mouth) occlusions and hand/hand (bottle twisting) occlusions. Researchers used four users in different environments to evaluate the system. Six out of eight pill taking events were successfully detected. Hence, they consider the sequence of bottle opening, hand-to-mouth, and bottle closing as a pill taking event. Another computer vision system for monitoring medication intake was developed by [PERSON] et al. [80]. The system considered multi-state scenarios including bottle opening, pill picking, pill swallowing, and bottle closing. It uses color classification algorithms for person detection and motion tracking by distinguishing the person's skin. In addition, colored bottles have been used for medication bottle detection. The recognition results were 90% classification accuracy for scenarios that differ from each other in the sequence of activities associated with medication taking. The work in [81] focused on developing a technique for background suppression of videos captured by low resolution cameras and using this technique for the monitoring of medication intake. However, the technique was only tested with one participant and no accuracy measurements were reported. Furthermore, the system's accuracy may get affected for different colored clothes worn by the participants, as the experiments have been conducted with a participant wearing dark colors compared to the background. Another similar vision-based system developed by [PERSON] et al. [82] used a multi-level approach for detecting and tracking mobile objects during medication intake. The face, the mouth, the hands, a glass of water, and the medication bottle were tracked in this system. To achieve this, detection and tracking techniques for background subtraction, skin regions' segmentation, and using color information for bottle detection are used. The average success rate of activity recognition was 98% from a population of three subjects. In later work, the authors directly use two cameras for the aim of occlusion handling [138]. In another approach, [PERSON] and [PERSON] [83] used skin detection and second order Hu moments for tracking body parts during medication taking. In addition, the Petri network was defined for modeling medication intake. From 12 video sequences of medication intake, the system was able to detect nine, as such, the authors suggested more additional features to be added to the system for further enhancement. Different from [82; 138], occlusion between hands was classified as bottle opening, while occlusion between either hands and the face was considered as pill swallowing.