Human-machine interaction plays a significant role in promoting convenience, production efficiency, and usage experience. Because of the universality and characteristics of electroencephalogram (EEG) signals, active EEG interaction is a promising and cutting-edge method for human-machine interaction. The seamless, skin-compliant, and motion-robust human-machine interface (HMI) for active EEG interaction has been in focus. Herein, we report a self-adaptive HMI (PAAS-MXene hydrogel) that can activate rapid gelation (5 s) using MXene cross-linking and conformably self-adapt to the scalp to help improve signal transduction. In addition to exhibiting satisfactory skin compliance, appropriate adhesion, and good biocompatibility, PAAS-MXene has demonstrated electrical performance reliability, such as low impedance (<50 Ω) at physiologically relevant frequencies, stable polarization potential (the rate of change is less than 6.5 × 10 V/min), negligible ion conductivity, and impedance change after 1000 stretch cycles, thereby realizing acquisition of EEG signals. In addition, a cap-free EEG signal acquisition method based on PAAS-MXene has been proposed. These findings confirm the high-precision detection ability of PAAS-MXene for electrocardiogram signals and EEG signals. Therefore, PAAS-MXene offers an option to actively control intention, motion, and vision through active EEG signals.
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http://dx.doi.org/10.1021/acsnano.2c08961 | DOI Listing |
J Affect Disord
December 2024
Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, People's Republic of China; Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin, People's Republic of China; Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration, Tianjin, People's Republic of China. Electronic address:
Generalized anxiety disorder (GAD) is a common anxiety disorder characterized by excessive, uncontrollable worry and physical symptoms such as difficulty concentrating and sleep disturbances. Although functional magnetic resonance imaging (fMRI) studies have reported aberrant network-level activity related to cognition and emotion in GAD, its low temporal resolution restricts its ability to capture the rapid neural activity in mental processes. EEG microstate analysis offers millisecond-resolution for tracking the dynamic changes in brain electrical activity, thereby illuminating the neurophysiological mechanisms underlying the cognitive and emotional dysfunctions in GAD.
View Article and Find Full Text PDFJ Neuroeng Rehabil
December 2024
School of Information Science and Technology, Fudan University, Shanghai, 200433, China.
For surface electromyography (sEMG) based human-machine interaction systems, accurately recognizing the users' gesture intent is crucial. However, due to the existence of subject-specific components in sEMG signals, subject-specific models may deteriorate when applied to new users. In this study, we hypothesize that in addition to subject-specific components, sEMG signals also contain pattern-specific components, which is independent of individuals and solely related to gesture patterns.
View Article and Find Full Text PDFPLoS One
December 2024
Division of Medical Information Sciences, Geneva University Hospitals, Geneva, Switzerland.
The essence of language and its evolutionary determinants have long been research subjects with multifaceted explorations. This work reports on a large-scale observational study focused on the language use of clinicians interacting with a phrase prediction system in a clinical setting. By adopting principles of adaptation to evolutionary selection pressure, we attempt to identify the major determinants of language emergence specific to this context.
View Article and Find Full Text PDFNanomicro Lett
December 2024
State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun, 130012, People's Republic of China.
Wearable pressure sensors capable of adhering comfortably to the skin hold great promise in sound detection. However, current intelligent speech assistants based on pressure sensors can only recognize standard languages, which hampers effective communication for non-standard language people. Here, we prepare an ultralight TiCT MXene/chitosan/polyvinylidene difluoride composite aerogel with a detection range of 6.
View Article and Find Full Text PDFNPJ Sci Learn
December 2024
Academy of Medical Engineering and Translational Medicine (AMT), Tianjin University, Tianjin, China.
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