Publications by authors named "Changmao Ni"
Substance use disorders (SUDs) imposes profound physical, psychological, and socioeconomic burdens on individuals, families, communities, and society as a whole, but the available treatment options remain limited. Deep brain-machine interfaces (DBMIs) provide an innovative approach by facilitating efficient interactions between external devices and deep brain structures, thereby enabling the meticulous monitoring and precise modulation of neural activity in these regions. This pioneering paradigm holds significant promise for revolutionizing the treatment landscape of addictive disorders.
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- The brain-computer interface (BCI) system connects external devices to the human brain and reflects mental states through EEG signals, which can often be contaminated by various artifacts.
- The complexity of unprocessed EEG data makes analysis and cleanup difficult, posing challenges for accurate readings.
- Recent advancements in artificial intelligence (AI) and machine learning have significantly improved the processing of EEG signals, allowing for better understanding of patients' health and potentially enhancing their quality of life.