Soft Tissue Attenuation of Acoustic Emission Pulses

1983 ◽  
Vol 105 (1) ◽  
pp. 20-23 ◽  
Author(s):  
T. M. Wright ◽  
J. M. Carr
Keyword(s):  
Acoustic Emission ◽  
Soft Tissue ◽  
Rise Time ◽  
Peak Amplitude ◽  
Signal Duration ◽  
Tissue Thickness ◽  
Exponential Decrease ◽  
Soft Tissue Attenuation

The soft tissue attenuation of acoustic emission signals was measured by transmitting pulses through volunteers and measuring the decay of the waveform characteristics of the pulse as a function of the thickness of the interposed tissue. Waveform characteristics of the received signal (signal duration, number of counts, peak amplitude, energy, and rise time) demonstrated an exponential decrease with increasing tissue thickness. The decrease appeared insensitive to the frequency of the pulse within the range of 50 to 600 KHz.

Pattern Classification of Acoustic Emission Signals during Wood Drying by Principal Component Analysis and Artificial Neural Network

2005 ◽  
Vol 297-300 ◽  
pp. 1962-1967 ◽  
Author(s):  
Ki Bok Kim ◽  
Ho Yang Kang ◽  
Dong Jin Yoon ◽  
Man Yong Choi
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Acoustic Emission ◽  
Rise Time ◽  
Component Analysis ◽  
Peak Amplitude ◽  
Wood Drying ◽  
Event Duration ◽  
Artificial Neural ◽  
Ae Signals

This study was performed to classify the acoustic emission (AE) signal due to surface check and water movement of the flat-sawn boards of oak (Quercus Variablilis) during drying using the principle component analysis (PCA) and artificial neural network (ANN). To reduce the multicollinearity among AE parameters such as peak amplitude, ring-down count, event duration, ring-down count divided by event duration, energy, rise time, and peak amplitude divided by rise time and to extract the significant AE parameters, correlation analysis was performed. Over 96 % of the variance of AE parameters could be accounted for by the first and second principal components. An ANN was successfully used to classify the AE signals into two patterns. The ANN classifier based on PCA appeared to be a promising tool to classify the AE signals from wood drying.

The Effects of Signal Rise Time and Duration on the Early Components of the Auditory Evoked Cortical Response

1971 ◽  
Vol 14 (3) ◽  
pp. 552-558 ◽  
Author(s):  
Paul H. Skinner ◽  
Frank Antinoro
Keyword(s):  
Rise Time ◽  
Early Response ◽  
Cortical Response ◽  
Peak Latency ◽  
Peak Amplitude ◽  
Signal Duration ◽  
Wave Form ◽  
Dramatic Effect ◽  
Consistent Change ◽  
Slow Rise

The effects of signal rise time and duration on the early components of the auditory evoked cortical response were studied in 20 subjects. Tone bursts were presented at 1000 Hz at various rise times and durations. No consistent effects of signal duration on the latency or amplitude of the early response were observed. The effects of signal rise time yielded no consistent change in peak latency but revealed a dramatic effect on peak amplitude. Amplitude decreased markedly with slower rise times. Stimuli presented with slow rise times resulted in instability of the wave form, while click stimuli produced remarkably stable responses from trial to trial.

Accuracy of robot-assisted versus optical frameless navigated stereoelectroencephalography electrode placement in children

2019 ◽  
Vol 23 (3) ◽  
pp. 297-302 ◽  
Author(s):  
Julia D. Sharma ◽  
Kiran K. Seunarine ◽  
Muhammad Zubair Tahir ◽  
Martin M. Tisdall
Keyword(s):  
Soft Tissue ◽  
Entry Point ◽  
Electrode Placement ◽  
Target Point ◽  
Localization Error ◽  
Bone Thickness ◽  
Tissue Thickness ◽  
Robot Assisted ◽  
Soft Tissue Thickness ◽  
Safety Margins

OBJECTIVEThe aim of this study was to compare the accuracy of optical frameless neuronavigation (ON) and robot-assisted (RA) stereoelectroencephalography (SEEG) electrode placement in children, and to identify factors that might increase the risk of misplacement.METHODSThe authors undertook a retrospective review of all children who underwent SEEG at their institution. Twenty children were identified who underwent stereotactic placement of a total of 218 electrodes. Six procedures were performed using ON and 14 were placed using a robotic assistant. Placement error was calculated at cortical entry and at the target by calculating the Euclidean distance between the electrode and the planned cortical entry and target points. The Mann-Whitney U-test was used to compare the results for ON and RA placement accuracy. For each electrode placed using robotic assistance, extracranial soft-tissue thickness, bone thickness, and intracranial length were measured. Entry angle of electrode to bone was calculated using stereotactic coordinates. A stepwise linear regression model was used to test for variables that significantly influenced placement error.RESULTSBetween 8 and 17 electrodes (median 10 electrodes) were placed per patient. Median target point localization error was 4.5 mm (interquartile range [IQR] 2.8–6.1 mm) for ON and 1.07 mm (IQR 0.71–1.59) for RA placement. Median entry point localization error was 5.5 mm (IQR 4.0–6.4) for ON and 0.71 mm (IQR 0.47–1.03) for RA placement. The difference in accuracy between Stealth-guided (ON) and RA placement was highly significant for both cortical entry point and target (p < 0.0001 for both). Increased soft-tissue thickness and intracranial length reduced accuracy at the target. Increased soft-tissue thickness, bone thickness, and younger age reduced accuracy at entry. There were no complications.CONCLUSIONSRA stereotactic electrode placement is highly accurate and is significantly more accurate than ON. Larger safety margins away from vascular structures should be used when placing deep electrodes in young children and for trajectories that pass through thicker soft tissues such as the temporal region.

A dense approach for computation of facial soft tissue thickness data

2021 ◽  
pp. 200460
Author(s):  
Diana Toneva ◽  
Silviya Nikolova ◽  
Stanislav Harizanov ◽  
Dora Zlatareva ◽  
Vassil Hadjidekov
Keyword(s):  
Soft Tissue ◽  
Tissue Thickness ◽  
Facial Soft Tissue ◽  
Soft Tissue Thickness

scholarly journals Improvement of biohistological response of facial implant materials by tantalum surface treatment

2019 ◽  
Vol 41 (1) ◽  
Author(s):  
Mohammed Mousa Bakri ◽  
Sung Ho Lee ◽  
Jong Ho Lee
Keyword(s):  
Foreign Body ◽  
Soft Tissue ◽  
Surface Treatment ◽  
Clinical Applications ◽  
Tissue Response ◽  
Bone Surface ◽  
Tissue Thickness ◽  
Implant Materials ◽  
Soft Tissue Thickness

Abstract Background A compact passive oxide layer can grow on tantalum (Ta). It has been reported that this oxide layer can facilitate bone ingrowth in vivo though the development of bone-like apatite, which promotes hard and soft tissue adhesion. Thus, Ta surface treatment on facial implant materials may improve the tissue response, which could result in less fibrotic encapsulation and make the implant more stable on the bone surface. The purposes of this study were to verify whether surface treatment of facial implant materials using Ta can improve the biohistobiological response and to determine the possibility of potential clinical applications. Methods Two different and commonly used implant materials, silicone and expanded polytetrafluoroethylene (ePTFE), were treated via Ta ion implantation using a Ta sputtering gun. Ta-treated samples were compared with untreated samples using in vitro and in vivo evaluations. Osteoblast (MG-63) and fibroblast (NIH3T3) cell viability with the Ta-treated implant material was assessed, and the tissue response was observed by placing the implants over the rat calvarium (n = 48) for two different lengths of time. Foreign body and inflammatory reactions were observed, and soft tissue thickness between the calvarium and the implant as well as the bone response was measured. Results The treatment of facial implant materials using Ta showed a tendency toward increased fibroblast and osteoblast viability, although this result was not statistically significant. During the in vivo study, both Ta-treated and untreated implants showed similar foreign body reactions. However, the Ta-treated implant materials (silicone and ePTFE) showed a tendency toward better histological features: lower soft tissue thickness between the implant and the underlying calvarium as well as an increase in new bone activity. Conclusion Ta surface treatment using ion implantation on silicone and ePTFE facial implant materials showed the possibility of reducing soft tissue intervention between the calvarium and the implant to make the implant more stable on the bone surface. Although no statistically significant improvement was observed, Ta treatment revealed a tendency toward an improved biohistological response of silicone and ePTFE facial implants. Conclusively, tantalum treatment is beneficial and has the potential for clinical applications.

scholarly journals Soft tissue attenuation in middle ear on HRCT: Pictorial review

2012 ◽  
Vol 22 (4) ◽  
pp. 298 ◽  
Author(s):  
Arangasamy Anbarasu ◽  
Kiruthika Chandrasekaran ◽  
Sivasubramanian Balakrishnan
Keyword(s):  
Soft Tissue ◽  
Middle Ear ◽  
Pictorial Review ◽  
Soft Tissue Attenuation
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