FatigueSet: A Multi-modal Dataset
for Modeling Mental Fatigue
and Fatigability

Towards Modeling Mental Fatigue and Fatigability In The Wild

Fatigue is a multidimensional construct with experiential (e.g., feelings of tiredness), behavioral (e.g., performance deficits), and neurophysiological (e.g., increased EEG alpha and theta wave activity) dimensions. Modeling mental fatigue based on physiological signals is challenging due to a lack of understanding of the interplay between physical activity and mental performance, as well as the difficulty of measuring fatigue in naturalistic settings.

We present a dataset containing multimodal sensor data from four wearable sensors during controlled physical activity sessions. Researchers can use this data to characterize the effect of physical activity on mental fatigue, and to predict mental fatigue and fatigability using wearable devices.

Dataset Description

FatigueSet contains approximately thirteen hours of sensor data collected over 36 sessions (twelve each of low/medium/high activity). Data were recorded from 14 sensors on four wearable devices at different on-body locations:

Device Sensors
Nokia Bell Labs earable prototype Accelerometer
Muse S EEG Headband Electroencephalography
Zephyr BioHarness 3.0 chest band Electrocardiography
Breathing sensor
Posture sensor
Empatica E4 wristband Accelerometer
Blood volume pulse and IBI
Electrodermal activity
Skin temperature

Additionally, FatigueSet also contains subjective fatigue ratings and mental fatigability scores on two cognitive tasks - the Choice Reaction Time task and the 2-back task. For more details, please see the below publication.

Dataset Structure

The dataset is structured as below:

┗ [session_id]/
┗ <data files>

Each participant directory contains three subdirectories corresponding to each session. The format of data files in each session folder are described in README.md in the main folder. This file also describes the metadata and survey response files in the main folder.

If you use our dataset in your work, please cite the original publication below:

FatigueSet: A Multi-modal Dataset for Modeling Mental Fatigue and Fatigability
Manasa Kalanadhabhatta, Chulhong Min, Alessandro Montanari and Fahim Kawsar
In 15th International Conference on Pervasive Computing Technologies for Healthcare (Pervasive Health), December 6–8, 2021