Predicting different dimensions of fatigue from speech data: a longitudinal study in shift workers

Shift work, or working outside of normal circadian cycles, is associated with both experience of fatigue and poorer long-term physical and mental health. However, current methods for assessing fatigue present several barriers to building understanding of how these risks develop over time within individuals. Here, we explore the potential of momentary speech activity-based fatigue measurement in a large, multi-lingual cohort of shift workers, using an intensive longitudinal study design (twice-daily measurement over two weeks in N = 1197 individuals from six different countries).

Paralinguistic speech features were used to predict different aspects of acute and chronic fatigue at each study time-point, with performance assessed in unseen (held-out) data. In the cross-sectional analysis, good (close to or exceeding current state-of-the-art) performance was achieved for both current sleep deprivation and self-reported sleepiness levels. The within-user analysis revealed robust increases in performance, yielding the ability to detect more subjective aspects of fatigue such as pervasive physical and mental exhaustion.

These findings offer preliminary support for the utility of using brief momentary speech samples as a low-burden, acceptable, and reliable measure of different aspects of fatigue in high-risk populations such as shift workers. We extend our gratitude to all the participants who generously dedicated their limited time and effort to our study. This work was supported by Innovate UK, the United Kingdom’s innovation agency, under Grant No. 10042845.

NC is part funded by the National Institute for Health and Care Research (NIHR) Biomedical Research Centre (BRC): Maudsley. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. Agnes Norbury, Alexandra Livia Georgescu, Ayla Pollmann, Emilia Molimpakis & Stefano Goria Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK NIHR Biomedical Research Centre: Maudsley, London, UK The authors declare that the research presented in this paper may be used in the development of products by the thymia Limited. thymia Limited has submitted applications for patents for digital health-tracking tools.At the time this work was undertaken, NC was a consultant to thymia Limited.

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