The Signal Transmission Mechanism on the Surface of Human Body for Body Channel Communication

2012 ◽  
Vol 60 (3) ◽  
pp. 582-593 ◽  
Author(s):  
Joonsung Bae ◽  
Hyunwoo Cho ◽  
Kiseok Song ◽  
Hyungwoo Lee ◽  
Hoi-Jun Yoo
2021 ◽  
Vol 263 (1) ◽  
pp. 5538-5540
Author(s):  
Jeon Jonghoon ◽  
Jonghoon Jeon ◽  
Kyunglae Gu ◽  
Junhong Park

This study presented a quantitative evaluation index related to sound response for diagnosis of middle ear condition. The signal transmission paths for human perception of sound are divided into bone conduction and air conduction, respectively, depending on the path through which vibration and sound are transmitted. The components of auditory system that can affect the sound signal variability include temporal bone, ear canal, eardrum, and middle ear cavity. The specific acoustic impedances were obtained through simple geometric model of the auditory components, and the sound transmission mechanism was implemented through the outer-middle ear circuit model. The frequency range corresponding to the resonance characteristics of each components were calculated. The response difference for the medium of middle ear was confirmed by deriving frequency response function between the input sound and the output sound in the frequency domain through the transfer function method. The reliability of the algorithm was confirmed through the ROC curve, and individual evaluation indexes were derived according to the priority factor between classification accuracy and error rate.


2007 ◽  
Vol 55 (5) ◽  
pp. 1080-1086 ◽  
Author(s):  
Namjun Cho ◽  
Jerald Yoo ◽  
Seong-Jun Song ◽  
Jeabin Lee ◽  
Seonghyun Jeon ◽  
...  

2020 ◽  
Vol 69 (9) ◽  
pp. 6399-6411 ◽  
Author(s):  
Taewook Kang ◽  
Sungeun Kim ◽  
Kwang-Il Oh ◽  
Jung-Hwan Hwang ◽  
Jaejin Lee ◽  
...  

Author(s):  
Zheng Qiong

As the traditional spectral community detection method uses adjacency matrix for clustering which might cause the problem of accuracy reduction, we proposed a signal-diffusion-based spectral clustering for community detection. This method solves the problem that unfixed total signal as using the signal transmission mechanism, provides optimization of algorithm time complexity, improves the performance of spectral clustering with construction of Laplacian based on signal diffusion. Experiments prove that the method reaches as better performance on real-world network and Lancichinetti–Fortunato–Radicchi (LFR) benchmark.


2010 ◽  
Vol 59 (4) ◽  
pp. 963-969 ◽  
Author(s):  
M.S. Wegmueller ◽  
M. Oberle ◽  
N. Felber ◽  
N. Kuster ◽  
W. Fichtner

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