Measuring Fatigue through Heart Rate Variability and Activity Recognition: A Scoping Literature Review of Machine Learning Techniques

Abstract

A scoping literature review was conducted to summarize the current research trends in fatigue identification with applications to human activity recognition through the use of diverse commercially available accelerometers. This paper also provides a brief overview of heart rate variability and its effect on fatigue. The linkage between recognizing an individual’s unique physical activities, and its possible feedback to manage fatigue levels were explored. Overall, triangulation of heart rate variability and accelerometer data show promise in identify chronic cognitive and physical fatigue levels.