Indoor Positioning and Prediction in Smart Elderly Care: Model, System and Applications

A Wandering Detection Method Based on Processing GPS Trajectories Using the Wavelet Packet Decomposition Transform for People with Cognitive Impairment

“…This ensures that the algorithm's performance remains unaffected when traversing any new path. Numerous wandering detection algorithms developed in previous studies [17,19,[25][26][27]29,[32][33][34][35][37][38][39][40][41][42], including machine-learning-based methods and next location prediction algorithms, rely on the patient's historical motion behaviors. However, there exists a potential disruption in the algorithm's performance when confronted with new behaviors that contradict the historical patterns.…”

“…Another promising method involves using wireless physiological sensors and wearable biosensors, including heart rate and blood pressure sensors, accelerometers, and gyroscopes, in conjunction with trajectory tracking techniques and machine learning algorithms such as deterministic tree-based algorithms to detect the occurrence of emotional arousal in the patient while wandering [35,36]. The use of advanced technologies such as the internet of things (IOT), Long-Short Term Memory (LSTM), neural networks, and the Gray model have also contributed to the accurate detection of wandering in another study of this group [37,38]. Furthermore, in [39], two time series processing techniques, the autocorrelation function and the partial autocorrelation function, used in conjunction with machine learning algorithms, were used to classify wandering patterns.…”