• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.5A
• /
• pp.388-394
• /
• 2012

In this paper, the influence analysis of food on human body organs is proposed by applying speech signal processing techniques. Until these days, most of researches regarding the influence of food on body organs are such that "A" ingredient of food may produce a good effect on "B" organ. However, the numerical and quantified researches regarding these effects hardly have been performed. This paper therefore proposes a method to quantify the effects by using numerical data, so as to retrieve new facts and informations. Especially, this paper investigates the effect of tomatoes on human heart function. The experiment collects samples of voice signals, before and after 5 minutes, 30 minutes and 1 hour, from 15 males in their 20s who have not abnormal heart function; the voice signal components are applied to measure changes of heart conditions to digitize and quantify the effects of tomatoes on cardiac function.

• Journal of Broadcast Engineering
• /
• v.24 no.2
• /
• pp.264-272
• /
• 2019

In this paper, we propose a 3D human body reconstruction and refinement method from the frames extracted from a video to obtain natural and smooth motion in temporal domain. Individual frames extracted from the video are fed into convolutional neural network to estimate the location of the joint and the silhouette of the human body. This is done by projecting the parameter-based 3D deformable model to 2D image and by estimating the value of the optimal parameters. If the reconstruction process for each frame is performed independently, temporal consistency of human pose and shape cannot be guaranteed, yielding an inaccurate result. To alleviate this problem, the proposed method analyzes and interpolates the principal component parameters of the 3D morphable model reconstructed from each individual frame. Experimental result shows that the erroneous frames are corrected and refined by utilizing the relation between the previous and the next frames to obtain the improved 3D human reconstruction result.

• TTA Journal
• /
• s.156
• /
• pp.76-81
• /
• 2014

• Journal of Korean Electronics
• /
• v.22 no.6
• /
• pp.11-14
• /
• 2002

• TTA Journal
• /
• s.137
• /
• pp.97-101
• /
• 2011

• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
• /
• v.10 no.4
• /
• pp.11-20
• /
• 1999

• Journal of Korean Electronics
• /
• v.25 no.8
• /
• pp.44-45
• /
• 2005

• TTA Journal
• /
• s.130
• /
• pp.63-66
• /
• 2010

• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
• /
• v.29 no.6
• /
• pp.26-30
• /
• 2018

• Journal of IKEEE
• /
• v.24 no.1
• /
• pp.120-126
• /
• 2020

We present a user recognition method using human body impulse response signals. The body compositions vary from person to person depending on the portion of water, muscle, and fat. In the body communication study, the body has been interpreted circuit models using capacitance and resistances, and its characteristics are determined by the body compositions. Therefore, the individual body channel is unique and can be used for user recognition. In this paper, we applied pseudo impulse signals to the left hand and recorded received signals from the right hand. The empirical mode decomposition (EMD) method removed noise from the received signals and 10 peak values are extracted. We set the differences between peak amplitudes as a key feature to identify individuals. We collected data from 6 subjects and achieved accuracy of 97.71% for the user recognition application.