Fitness trackers have broadened the healthcare ecosystem and made self-tracking everyday physical activities possible. Features like heart rate monitoring can help detect health ailments, yet there is little evidence that suggests tracking health indicators and physical activities leads to long-term health behavior change. This proceeding analyzes areas of Human Factors that could be used to increase long-term user engagement. Feedback, information display, and specific design principles and case studies are discussed.

As medical devices become more technologically advanced, patients risk forgetting their training and missing critical steps. Existing literature explores ways to train patients on medical devices but does not quantify how long information is retained, which is essential for valid medical device testing before approval. The aim of the research presented is to validate a robust method of quantifying training decay research across multiple periods. Some participants were trained on an insulin pump and assigned to decay periods of one hour, one day, or one week. Additionally, an untrained cohort represented a theoretical maximum decay. Although results are not statistically significant due to a small sample size, task performance shows possible differences between time points and task types. Improvements and considerations translating this pilot study into a more extensive main study are also discussed.