National Cheng-Kung University

Industrial Technology Research Institute

Advanced & Wise Technology Corp.

Sheng-Fu Liang

Chih-En Kuo

Chin-Teng Lin

Jia-Lin Chen

Tai-Jie Yun

Tsung-Hua Lu

Tsung-Hao Hsieh

I Yu Chen

Fu-Zen Shaw

Her-Chang Pu

Jen Jui Hsueh

Tien-Ho Chung

Yu-Hung Li

Yung-Hung Wang

Wen-yu Su

A brainwave feedback system, adapted to generate feedback based on a user's brainwave, the brainwave feedback system comprises: a brainwave sensing device, configured to obtain a first brainwave signal of the user; a server, storing a keyword string pool including a plurality of sorted keywords, and performing a feedback procedure when a first physiological parameter falls outside of a predetermined parameter range, wherein the first physiological parameter is associated with the first brainwave signal, the feedback procedure includes choosing a keyword from the keyword string pool by the server as a feedback keyword, and outputting the feedback keyword; and an output component, in communicable connection with the server, wherein the output component presents an analysis result corresponding to the first physiological parameter. The present disclosure further discloses an operation method of brainwave feedback system.

Brainwave feedback system and operation method thereof

This invention mainly discloses an EOG-based sleep staging method which is used to improve of an accuracy of automatic sleep judging result. The method may be executed by a processor and comprises steps of reading a to-be-test data having a variation depending on time of EOG generated by a user during a sleep process; acquiring a plurality of eye movement characteristics based on a variation of the EOG of a period, with the characteristics including an eye movement ratio, a blink count, a low frequency power ratio, a high frequency power ratio, an alpha rhythm ratio, a spindle rhythm ratio, a delta rhythm ratio and an average amplitude of eletrooculogram (EOG) signals; and determining a sleep state of the period is a 'WAKE stage', a 'REM stage', a &#x201c;S1 stage&#x201d;, a &#x201c;S2 stage&#x201d;, or a &#x201c;SWS stage&#x201d; based on the EOG characteristics. Furthermore, a computer readable medium with stored programs, and electronic apparatuses are provided.

EOG-based sleep staging method, computer program product with stored programs, computer readable medium with stored programs, and electronic apparatuses

The invention provides a method for image resolution enhancement, which utilizes a fuzzy analysis system simulating the human vision system and uses the neural network as a basis for digital image interpolation. After an original image is inputted in, the image analysis module will divide and classify the original image, and then each of the image being classified will be processed by either the bilinear interpolation or the neural network interpolation. Because the fuzzy analysis system is configured according to the human vision system, and because the neural network is a model obtained from learning real natural images, the vision effect of the image enlarged through the processing method of the invention is very close to the real natural image.

Method for image resolution enhancement

A &ldquo;virtual string&rdquo; is generated for synthesizing sound produced by plucked-string instruments using recurrent neural networks. The disclosed recurrent neural network, called a Scattering Recurrent Network (SRN), is based on the physics of waves traveling in the string. Vibration measured from a plucked string is used as the training data for the SRN. The trained SRN is a virtual model capable of generating tones similar to the tones generated by the physical string. As with a real string, the &ldquo;virtual string&rdquo; corresponding to the SRN responds differently to different types of string &ldquo;plucking&rdquo; motions.

Method and apparatus of synthesizing plucked string instruments using recurrent neural networks

Growing community of inventors

Tainan, Taiwan

Sheng-Fu Liang