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Abstract
According to the WHO, the number of mental disorder patients, especially depression patients, has overgrown and become a leading contributor to the global burden of disease. With the rising of tools such as artificial intelligence, using physiological data to explore new possible physiological indicators of mental disorder and creating new applications for mental disorder diagnosis has become a new research hot topic. We present a multi-modal open dataset for mental-disorder analysis. The dataset includes EEG and recordings of spoken language data from clinically depressed patients and matching normal controls, who were carefully diagnosed and selected by professional psychiatrists in hospitals. The EEG dataset includes data collected using a traditional 128-electrodes mounted elastic cap and a wearable 3-electrode EEG collector for pervasive computing applications. The 128-electrodes EEG signals of 53 participants were recorded as both in resting state and while doing the Dot probe tasks; the 3-electrode EEG signals of 55 participants were recorded in resting-state; the audio data of 52 participants were recorded during interviewing, reading, and picture description.
Measurement(s) | Human Brainwave • spoken language |
Technology Type(s) | EEG collector • audio recorder |
Sample Characteristic - Organism | Homo Sapiens |
Sample Characteristic - Location | China |
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Details
1 Lanzhou University, Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou, China (GRID:grid.32566.34) (ISNI:0000 0000 8571 0482)
2 Lanzhou University Second Hospital, Lanzhou, China (GRID:grid.411294.b) (ISNI:0000 0004 1798 9345)
3 Lanzhou University, Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou, China (GRID:grid.32566.34) (ISNI:0000 0000 8571 0482); Chinese Academy of Sciences, Shenzhen Institutes of Advanced Technology, Shenzhen, China (GRID:grid.9227.e) (ISNI:0000000119573309)
4 Lanzhou University, Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou, China (GRID:grid.32566.34) (ISNI:0000 0000 8571 0482); Chinese Academy of Sciences, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institutes for Biological Sciences, Shanghai, China (GRID:grid.9227.e) (ISNI:0000000119573309); Joint Research Center for Cognitive Neurosensor Technology of Lanzhou University & Institute of Semiconductors, Chinese Academy of Sciences, Lanzhou, China (GRID:grid.9227.e) (ISNI:0000000119573309); Open Source Software and Real-Time System (Lanzhou University), Ministry of Education, Lanzhou, China (GRID:grid.419897.a) (ISNI:0000 0004 0369 313X)