MAUS: A Dataset for Mental Workload Assessment on N-back task Using Wearable Sensor
- Citation Author(s):
-
Win-Ken Beh
(Graduate Institute of Electrical Engineering, National Taiwan University)
Yi-Hsuan Wu (Graduate Institute of Electrical Engineering, National Taiwan University)An-Yeu (Andy) Wu (Graduate Institute of Electrical Engineering, National Taiwan University) - Submitted by:
- Win Ken Beh
- Last updated:
- DOI:
- 10.21227/q4td-yd35
- Data Format:
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Abstract
The MAUS dataset focused on collecting easy-acquired physiological signals under different mental demand conditions. We used the N-back task to stimuli different mental workload statuses. This dataset can help in developing a mental workload assessment system based on wearable device, especially for that PPG-based system. MAUS dataset provides ECG, Fingertip-PPG, Wrist-PPG, and GSR signal. User can make their own comparison between Fingertip-PPG and Wrist-PPG. Some study can be carried out in this dataset
In brief, each of 22 persons (2 females) recorded in the dataset is represented with a 35-minutes recording of physiological signals (ECG, Fingertip-PPG, Wrist-PPG, and GSR).
Instructions:
The database is organized in 2 folders and documentation:
• Data – raw signal recordings for the individual participants, including extracted Inter-Beat-Interval sequence and participants’ respond in N-back task
• Subjective_rating – subjective rating of sleep quality and NASA-TLX
• MAUS_Documentation.pdf – documentation of dataset description and details.
