Experimental Study on Neural Feedback in Embedded System Teaching Processing Based on ERP Signal Analysis

Du, Dongdong

doi:10.3991/ijet.v14i12.10715

Cited by 3 publications

(2 citation statements)

References 24 publications

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“…With the development of information science and computer science, signal processing technology has developed rapidly and presented endless prospects. It is widely used in the fields of speech recognition, communication, robot vision sensing, earthquake, event-related potential (ERP) technology, industrial monitoring, and so on [1][2][3][4][5][6]. Signal and system course (SSC) provide basic theories and methods for the application of signal and system (SS) processing technology in these fields.…”

Section: Introductionmentioning

confidence: 99%

Blended Teaching for Signal and System Course Based on Internet-Engineering Education

Dou

Wang²,

Li³

et al. 2023

Research Reports on Computer Science

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Aiming at the teaching difficulties of signal and system course, adapting to the new situation of the information age and the engineering education of outcome-based education (OBE), adhering to the traditional classroom teaching and making full use of the network teaching platform and internet technology, a blended teaching mode of internet-engineering education (BTM-IEE) is proposed. In this mode, we adhered to the educational concept of OBE, formulated teaching objectives, optimized teaching content, and built matching teaching resources. In three teaching stages: before class, in class and after class, online-offline blended teaching was effectively organized and implemented by using internet technology, network teaching platform, independently developed a comprehensive experimental system, remote virtual experiment platform, QQ group, etc. In order to ensure a good cycle of teaching quality, a multi-dimensional evaluation system is constructed. A variety of application examples and questionnaire data showed that BTM-IEE can achieve a deep integration of in class-out of class and online-offline, improve students’ engineering application ability, autonomous learning ability, cooperation, communication ability, and cultivate innovative thinking. The horizontal and vertical comparison between the traditional and the improved teaching mode shows that the BTM-IEE can improve the teaching effect, the excellent rate is significantly increased, and the failure rate is significantly reduced. This mode provides a reference for the improvement of the teaching quality of professional courses and has important practical significance.

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Section: Introductionmentioning

confidence: 99%

Blended Teaching for Signal and System Course Based on Internet-Engineering Education

Dou

Wang²,

Li³

et al. 2023

Research Reports on Computer Science

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“…Ready-to-use Python solutions for EEG signal analysis such as python-MNE (Gramfort et al, 2013;Gramfort et al,2014) or PyEEG (Bao et al, 2011) are either too complicated to encompass or not suitable for further real-time decoding of particular brain states. Instruction, April 2021 • Vol.14, No.2 usability are being studied: workload and satisfaction (Riccio et al, 2011;Zander et al, 2010); learnability (Du, 2019;Lorenz et al, 2014); user-friendliness, pleasantness, and fatigue (Jukiewicz & Cysewska-Sobusiak, 2016;Cipresso et al, 2012); etc. Examining how people perceive and operate on designed services is already well recognized and studied in the field of computer software development (Jacko, 2012;Preece et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Analysis of EEG Signals for Non-technical and Non-medical Students

Buchwald¹,

Czyż²,

Jukiewicz³

2021

INT J INSTRUCTION

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The interaction between humans and computers is one of the most pressing challenges in contemporary society. Subtleties of this communication require that human-computer interfaces are conceptualized and tested by highly specialized experts. Here we describe a novel academic course for human-oriented designers and project managers, with the emphasis being put on the communication between the human brain and computer. Outcomes of the course were validated on 12 course participants both: qualitativelyeducational experience, and quantitatively outcomes of a project and final exam. T-test comparison revealed that students who participated in the course gained specialized knowledge, as compared to students who did not take part in the course. Moreover, students generally agreed that the course was helpful and interesting, however, about one-third of them considered the course hard. All in all, we find our brain-computer interfaces course useful in instructing specialist oriented on the human-factor of the communication between human and the machine.

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