Abstract:
Disclosed herein are a system and a method for volitional electromyography (vEMG) signal detection from an EMG signal when functional electrical stimulation (FES) is applied. The system for vEMG signal detection includes a receiver for receiving data from an EMG electrode when FES is applied, a memory for storing a program for detecting a vEMG signal using the received data, and a processor for executing the program, wherein the processor cuts the data received from the EMG electrode disposed at a predetermined position, calculates a difference between data for previous FES and data for current FES, and detects the vEMG signal using the calculated difference.
Abstract:
A tactile music learning apparatus converts sound data of a user's voice corresponding to original music into first tactile data including tactile information, generates a synchronized tactile pattern by synchronizing the first tactile data with second tactile data including tactile information corresponding to sound data of the original music, and transfers the synchronized tactile pattern to a tactile reproducing apparatus to allow the tactile reproducing apparatus to reproduce the synchronized tactile pattern.
Abstract:
The present disclosure relates to a method and apparatus for performing a spatial domain-based optical convolution operation. A method of performing a convolution operation according to an embodiment of the present disclosure may comprise: performing a first optical Fourier transform on a spatial domain image; performing a second optical Fourier transform on a spatial domain kernel; performing an element-wise product operation between a result of the first optical Fourier transform and a result of the second optical Fourier transform; calculating a convolution result by performing a third optical Fourier transform on a result of the element-wise product operation; and obtaining data based on the convolution result.
Abstract:
Technology for a method of detecting a user hand by a user hand detecting device. The method according to an aspect of the present invention includes extracting a first mask image from a depth image in which the user hand is imaged; extracting a second mask image having a preset skin color value among regions corresponding to the first mask image in a color image in which the user hand is imaged; generating a skin color value histogram model in a color space different from a region of the color image corresponding to a color region of the second mask image; generating a skin color probability image of the different color space from the color image using the skin color value histogram model and an algorithm for detecting a skin color region; and combining the skin color probability image with the second mask image and detecting the user's hand region.
Abstract:
Disclosed is an optical artificial neural network system which includes an optical hidden layer that receives an input light including input data and generates an output light by performing a linear process and a nonlinear process on the input data, and a light transfer unit that provides the output light to an input of the optical hidden layer, and the optical hidden layer performs the linear process and the nonlinear process based on the received output light.
Abstract:
A muscle control device includes an electromyography (EMG) electrode unit including a plurality of electrodes, and that senses an EMG signal, an EMG circuit unit that generates channel data, based on electrode signals, a control unit that receives the channel data, extracts a volitional electromyography signal, based on the channel data, and determines FES (Functional Electrical Stimulation) stimulation parameters, based on the volitional electromyography signal, an FES electrode unit that outputs a functional electrical stimulation, based on the FES stimulation parameters, and an FES circuit unit that receives the FES stimulation parameters, generates the functional electrical stimulation, based on the FES stimulation parameters, and transmits the functional electrical stimulation to the FES electrode unit, and the control unit recognizes a direction and an intensity of a motion from the volitional electromyography signal, based on the volitional electromyography signal and adjusts an intensity of the functional electrical stimulation.
Abstract:
Provided is a soft actuator. The soft actuator includes a first support body, a second support body spaced apart from the first support body in a first direction, a yarn structure having one end coupled to the first support body and the other end coupled to the second support body, and a light source part spaced apart from the yarn structure in a second direction crossing the first direction. The yarn structure includes a polymer layer having a coil spring shape extending in the first direction and a light absorption layer configured to surround an outer surface of the polymer layer.