Automated Temporal Anomaly Detection in Digital Calendar Data for Enhanced Reality Orientation Therapy

**Abstract:** This paper proposes a novel system, Temporal Anomaly Detection Engine (TADE), leveraging advanced time series analysis and machine learning techniques to identify deviations from established usage patterns in digital calendar data for patients undergoing Reality Orientation Therapy (ROT). TADE analyzes calendar events – dates, times, durations, participant lists, and event descriptions – to detect anomalies indicative of cognitive decline, disorientation, or episodic memory lapses. The system integrates a hierarchical clustering approach with a novel probabilistic anomaly detection model to provide clinicians with real-time feedback on patient temporal awareness, facilitating personalized therapeutic interventions. TADE aims to significantly augment the efficacy of ROT by providing objective, quantifiable data on temporal perception deficits, ultimately improving patient outcomes and quality of life. --- *This document is a part of the Freederia Research Archive. Explore our complete collection of advanced research at [en.freederia.com](https://en.freederia.com), or visit our main portal at [freederia.com](https://freederia.com) to learn more about our mission and other initiatives.*