About MODMA
We present a multi-modal open dataset for mental-disorder analysis. For now, the dataset includes data mainly from clinically depressed patients and matching normal controls. All our patients were carefully diagnosed and selected by professional psychiatrists in hospitals. At this stage, only electroencephalogram (EEG) and speech recording data are made publicly available. The EEG signals were recorded as both in resting state and under stimulation. The EEG dataset includes not only data collected using traditional 128-electrodes mounted elastic cap, but also a novel wearable 3-electrode EEG collector for pervasive applications. The speech data were recorded as during interviewing, reading and picture description. Detail descriptions of each sub-dataset are listed accordingly in the download section. In the future, more data will be added regularly, which will cover not only more mental disorders, such as schizophrenia, anxiety and mania; but also more data types, such as eye-movement tracking, facial expression recording and MRIs. We encourage other researchers in the field to use it for testing their own methods of mental-disorder analysis.
Dataset Ethics
Written informed consent was obtained from all participants prior to the experiment. Consent forms and study design were approved by the local Ethics Committee for Biomedical Research at the Lanzhou University Second Hospital in accordance to the Code of Ethics of the World Medical Association (Declaration of Helsinki).
Acknowledgments
First and foremost, we'd like to thank all participants, partner doctors and hospitals for
having the patience and goodwill to let us finish all the experiments and collect all the valuable data.
Then we'd like to thank our funding bodies:
* National Key Research and Development Program of China (Grant No. 2019YFA0706200)
* National Basic Research Program of China (973 Program) (Grant No.2014CB744600)
* National Natural Science Foundation of China (Grant No.61210010, No.61632014, No.61627808)
* Program of International S&T Cooperation of MOST (Grant No.2013DFA11140)
* Program of Beijing Municipal Science & Technology Commission (Grant No. Z171100000117005)
