Remote education student characteristic signal extraction and recognition method

A characteristic signal, distance education technology, applied in the field of information processing, can solve problems such as being difficult to apply

Inactive Publication Date: 2010-09-22
SHANGHAI JIAO TONG UNIV
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  • Abstract
  • Description
  • Claims
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Problems solved by technology

In this environment that lacks voice and expression changes, existing methods are difficult to apply

Method used

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  • Remote education student characteristic signal extraction and recognition method
  • Remote education student characteristic signal extraction and recognition method
  • Remote education student characteristic signal extraction and recognition method

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Embodiment Construction

[0076] Below in conjunction with accompanying drawing, the embodiment of the present invention is described in detail, this embodiment is implemented under the premise of the technical solution of the present invention, has provided detailed implementation and specific operation process, but the scope of protection of the present invention is not limited to Examples described below.

[0077] like figure 1 As shown, this embodiment includes the following steps:

[0078] Step 1, physiological signal noise filtering. After receiving the signal from the physiological signal sensor, first low-pass filter the input signal to weaken the interference of external electromagnetic fields such as alternating current on the signal. Then use a smoothing filter to smooth and filter the low-pass filtered signal to filter the Gaussian random noise that may be introduced by the student's slight body movement.

[0079] The physiological signal sensor includes: a skin conductance (Skin Conduct...

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Abstract

The invention relates to a remote education student characteristic signal extraction and recognition method in the technical field of information processing. The method comprises the following steps of: eliminating the signal biasing caused by individual difference and environmental factors by preprocessing physiological signals of students; processing the physiological signal characteristics by using a continuous limited Boltzmann machine to reduce the characteristic difference due to the individual difference; inputting the information into a support vector machine for training to obtain a sorter; and finally performing mode real-time recognition. Therefore, the feedback information of the students on teaching methods can be effectively acquired, the average teaching feedback information accuracy of the students on site reaches 82.6 percent, and the teaching level of the on-site remote education is improved. The remote education student characteristic signal extraction and recognition method can be widely applied to the remote education, can directly acquire the feedback information on the teaching acceptance degree of the students who take part in the remote education, timely adjusts and improves the teaching rhythm and level, is favorable for the remote education, and has obvious advantages on the sorting accuracy.

Description

technical field [0001] The present invention relates to a detection method in the technical field of information processing, in particular to a method for extracting and identifying characteristic signals of distance education students. Background technique [0002] With the gradual development of E-Learning, distance education technology has been widely accepted by the society. In the current distance education mode, because there is no face-to-face communication process between teachers and students, teachers cannot keep abreast of students' interest in course content during class, and cannot respond to students' emotional state changes during class. Appropriate adjustments to teaching methods will affect the teaching quality of distance education. Therefore, a method that can identify students' emotional states in real time through computers can make up for the defects in the existing distance education mode and improve the teaching efficiency of distance education. [...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G09B5/00
Inventor 周家骥罗恒罗全锋申丽萍申瑞民
Owner SHANGHAI JIAO TONG UNIV
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