Root Mean Square Standard Deviation Research Articles

Air inflow into vacuum-type immobilization devices impacts setup errors.

We aimed to determine the impact of air inflow into vacuum-type immobilization devices (VIDs) on setup errors. We assigned 70 patients undergoing radiotherapy for head and neck cancer to groups V (n = 34) or N (n = 36) according to whether the VIDs were deflated weekly or not deflated during treatment, respectively. We calculated systematic errors (Σ) as the standard deviations (SDs) of mean errors, and random errors (σ) as the root mean square of SDs in each patient. We compared overall means (μ), SDs (SDoverall), random errors and systematic errors. We also measured temporary pressure changes in VIDs to determine the influence of pressure changes in VIDs on setup errors. The μ was within 0.20mm and 0.2° in both groups, whereas SDoverall significantly differed between them. The SDoverall differed the most in the Roll axes of groups N (0. 87°) and V (0.58°). The Σ and σ values were lower in all axes of group V than in group N. Despite the initial deflation target of -70kPa, the pressure in VIDs reached -5kPa at the end of treatment. However, weekly deflation apparently maintained pressure at -20kPa. Effective pressure control in VIDs can reduce patient-by-patient variation and improve setup reproducibility for individual patients, consequently resulting in small variations among overall setup errors.

Characterisation of the acute hypoxic response using breathing variability parameters: A pilot study in humans

PurposeWe aimed to investigate respiratory rate variability (RRV) and tidal volume (Vt) variability during exposure to normobaric hypoxia (i.e., reduction in the fraction of inspired oxygen - FiO2), and the association of the changes in RRV and Vt variability with the changes in pulse oxygen saturation (SpO2). MethodsThirty healthy human participants (15 females) were exposed to: (1) 15-min normoxia, (2) 10-min hypoxia simulating 2200 m, (3) 10-min hypoxia simulating 4000 m, (4) 10-min hypoxia simulating 5000 m, (5) 15-min recovery in normoxia. Linear regression modelling was applied with SpO2 (dependent variable) and the changes in RRV and Vt variability (independent variables), controlling for FiO2, age, sex, changes in heart rate (HR), changes in HR variability (HRV), and changes in minute ventilation (VE). ResultsWhen modelling breathing parameter variability as root-mean-square standard deviation (RMSSD), a significant independent association of the changes in RRV with the changes in SpO2 was found (B = −4.3e-04, 95% CI = −8.3e-04/−2.1e-05, p = 0.04). The changes in Vt variability showed no significant association with the changes in SpO2 (B = −1.6, 95% CI = −5.5/2.4, p = 0.42). When modelling parameters variability as SD, a significant independent association of the changes in RRV with the changes in SpO2 was found (B = −8.2e-04, 95% CI = −1.5e-03/−9.4e-05, p = 0.03). The changes in Vt variability showed no significant association with the changes in SpO2 (B=1.4, 95% CI = −5.8/8.6, p = 0.69). ConclusionHigher RRV is independently associated with lower SpO2 during acute hypoxic exposure, while Vt variability parameters are not. Therefore, RRV may be a potentially interesting parameter to characterize individual responses to acute hypoxia.

Age-related changes in lumbar bone mineral density measured using quantitative computed tomography in healthy female cynomolgus monkeys.

Cynomolgus monkeys are widely used in studies related to osteoporosis, and there is no evidence of age-related changes in volumetric bone mineral density (vBMD) measured using quantitative computed tomography (QCT) in nonhuman primates. This study aimed to describe changes in the characteristics of lumbar vBMD with age, to analyze the relationship between lumbar vBMD and body composition, and to investigate the precision of QCT measurements in healthy female cynomolgus monkeys. Age-related changes in lumbar vBMD were described using cubic regression models, and the accumulated bone loss rates (ABLR) of the lumbar spine were calculated. Spearman rank correlation and ridge regression analysis were used to investigate the relationship of the average lumbar vBMD and body components. Thirty animals were selected to analyze the short-term in vivo precision of the QCT measurements. The precision was expressed as the root-mean-square coefficient of variation (RMS-CV%) or root-mean-square standard deviation (RMS-SD). A total of 72 healthy female cynomolgus monkeys, aged 1-25 years, were included in this study. The average lumbar vBMD of female cynomolgus monkeys increased with age until the age of 10 years, around which it reached peak bone mass, with a relatively marked decline after the age of 13 years. The ABLRs of female cynomolgus monkeys in the premenopausal (13-19 years) and postmenopausal age groups (20-25 years) were -4.9% and -21.2%, respectively. Ridge regression analysis showed that age and subcutaneous adipose tissue (SAT) contributed positively to the average lumbar vBMD in animals aged ≤10 years, whereas in animals aged >10 years, age contributed negatively to lumbar vBMD. The RMS-CV% (RMS-SD) of the lumbar vBMD measured using QCT ranged from 0.47% to 1.60% (1.91-6.31 mg/cm3). Age-related changes in lumbar vBMD measured using QCT in healthy female monkeys showed similar trends to those in humans. Age and SAT may affect the lumbar vBMD in female cynomolgus monkeys. QCT revealed good precision in measuring the lumbar vBMD in female cynomolgus monkeys.

EFFECT OF GENDER ON BLOOD PRESSURE AND HEART RATE VARIABILITY DURING INCREASING INTENSITIES OF ISOMETRIC HAND GRIP EXERCISE IN UNTRAINED ADULTS

ender influences blood pressure (BP) and heart rate variability (HRV). The purpose of this study was to investigate the influence of gender on BP and HRV during increasing intensities of isometric hand grip (IHG) exercise. Nineteen (n=19) (10 males, 9 females) participants aged 25.7±0.9 and 27.0±0.6 years (Mean± SEM), with height and weight of 173.4±3.1 cm, 72.8±3.7kg and 160.9±1.6 cm, 59.3±3.4 kg volunteered after ethical approval. BP, HRV and maximum voluntary contraction (MVC) was measured at rest. Thereafter, participants underwent 30% MVC for 2 minutes during which BP and HRV was taken with 10 minutes rest. Contractions were amplified to 35, 40, 45% MVC. One-Way ANOVA compared Mean±SEM values at 95% significance. The systolic blood pressure (SBP) increased significantly in females (p<0.001) than males (p<0.01); diastolic blood pressure (DBP) increased significantly in both gender (p<0.001); average number of heart beats increased significantly in males (p<0.001) than females (p<0.01); significant increase in LF/HF ratio in females (p<0.01) but not in males. However, there was no significant difference in the standard deviation of N-N interval (SDNN), low frequency (LF), high frequency (HF), very low frequency (VLF), root mean square of standard deviation (RMSSD), total frequency power (TFP), proportion of numbers of pairs of successive intervals (Pnn50) in both genders. This study may suggest a higher sympathetic influence (following rise in SBP and LF/HF ratio) in females than males during IHG exercise. Thus, variations exist in BP and HRV during short interval, altered intensities IHG exercise in both genders.

Heart Rate Variability and Cold Pressor Test before Onset of Pre-eclampsia in Pregnant Women-A Longitudinal Study

Introduction: A major obstetric complication, that leads to severe maternal and foetal morbidity is Pre-eclampsia (PE). Studies evaluating the autonomic nervous activity in pregnant women with PE shows conflicting results. Previous studies are inadequate for the identification of the most useful tools to detect and monitor autonomic dysfunction prior to PE. The cold pressor test is a simple and validated test, in which the afferent sensory pathways are stimulated by the cold stimulus, resulting in an increase in Blood Pressure (BP). Aim: To evaluate the response to cold pressor test and Heart Rate Variability (HRV) to detect increased vascular reactivity and sympathetic activity prior to the clinical manifestation of PE in pregnant women. Materials and Methods: A longitudinal study was conducted in in the Department of Physiology at Hamdard Institute of Medical Sciences, HAHC Hospital, Jamia Hamdard, New Delhi, India. The duration of the study was 11 months, from December 2018 to November 2019. Subjects were 50 pregnant women, between age 18-40 years and of 12-14 weeks of gestation. Cold pressor test and HRV were parameters measured for the assessment of the autonomic functions during 12 and 21 weeks of gestational period. The Statistical Package for Social Sciences (SPSS) version 26.0 was used for analysis of the quantitative data. Paired t-test was done for comparison of all values. Results: The mean age of the study participants was 29±2.7 years. There was no hyper-reaction to cold pressor test at 12 weeks of gestation, nor the subjects showed any signs of PE. At 14 weeks of gestation, 2 (4%) showed hyper-reaction to cold pressor test. At 21 weeks of gestation, 3 (6%) subjects showed hyper-reactions to cold pressor test and out of them, 2 developed PE. Root Mean Square Standard Deviation (RMSSD) and difference between adjacent Standard Deviation of N-N intervals (SDNN) of HRV analysis were significantly higher in the first trimester as compared to 21 weeks of pregnancy. Conclusion: Response to cold pressor test showed increased vascular reactivity, as a sign before the development of PE. HRV analysis could not detect any significant features of increased sympathetic activity prior to the clinical manifestation of PE in pregnant women.

Future Challenges of Particulate Matters (PMs) Monitoring by Computing Associations Among Extracted Multimodal Features Applying Bayesian Network Approach

ABSTRACT The particulate matter (PM) is emitted from diverse sources and affects the human health very badly. In the past, researchers applied different automated computational tools in the predication of PM. Accurate prediction of PM requires more relevant features and feature importance. In this research, we first extracted the multimodal features from time domain standard deviation average (SDAPM), standard deviation of standard deviation (SDSD), standard deviation of particulate matter (SDPM), root-mean square of standard deviation (RMSSD), and nonlinear dynamical measure wavelet entropy (WE) – Shannon, norm, threshold, multiscale entropy based on KD tree (MSEKD), and multiscale approximate entropy (MAEnt). We then applied the intelligent-based Bayesian inference approach to compute the strength of relationship among multimodal features. We also computed total incoming and outgoing forces between the features (nodes). The results reveal that there was a very highly significant correlation (p-value <0.05) between the selected nodes. The highest total force was yielded by WE-norm followed by SDAPM and SDPM. The association will further help to investigate that which extracted features are more positively or negatively correlated and associated with each other. The results revealed that the proposed methodology can further provide deeper insights into computing the association among the features.

The precision study of dual energy X-ray absorptiometry for bone mineral density and body composition measurements in female cynomolgus monkeys.

Dual-energy X-ray absorptiometry (DXA) is a well-accepted tool for monitoring skeletal and body composition changes in biomedical studies. The nonhuman primate model is suitable for studies exploring the pathogenesis of and novel treatments for osteoporosis. Our objectives are to determine the precision of DXA detection in cynomolgus monkeys and to identify the difference in precision in lumbar bone mineral density (BMD) with various segment selections. Thirty adult female cynomolgus monkeys underwent duplicate total body DXA scans. Total body bone mineral density (BMDTB) and body composition, including bone mineral content (BMCTB), lean mass (LMTB), and fat mass (FMTB), were analyzed by enCORE software, while lumbar BMD was obtained by manual region-of-interest analysis. The precision was represented as the root-mean-square standard deviation (RMS-SD) and coefficient of variation (RMS-CV%), and least significant changes (LSCs) were reported. The RMS-SD (RMS-CV%) of the repeated DXA analyses for BMDTB, BMCTB, LMTB and FMTB were 0.002 g/cm2 (0.50%), 0.90 g (0.42%), 0.015 kg (0.49%), and 0.031 kg (2.71%), respectively. The regional BMD precision (RMS-CV%) of the lumbar spine with various combinations ranged from 0.70% to 1.09%, The LSCs with 80% statistical confidence (LSC80) ranged from 1.27% to 1.97%, and LSC95 ranged from 1.94% to 3.01%. DXA provided excellent reproducibility in the measurements of BMD and body composition in nonhuman primates. We find DXA reliable for total and regional measurement in skeletal research and the evaluation of osteoporosis treatment with monkeys as animal models.

Caffeine intake and its influences on heart rate variability recovery in healthy active adults after exercise: A systematic review and meta-analysis

AimsResults regarding the effects of caffeine (CAF) intake on the autonomic control of heart rate recovery exercise remain inconclusive. Thus far, no study has used effect measures to pool the results of different experiments. We aim to assess the acute effect of CAF intake before exercise on the recovery of heart rate variability (HRV) after exercise through a systematic review and meta-analysis. Data synthesisRandomized controlled clinical trials were included; sample composed of physically active or trained adults; CAF should be offered/ingested before exercise, with dosage between 100 and 400 mg or between 2 and 6 mg/kg and administration/ingestion route analogous in the protocols; studies required to present results of HRV indices before and after exercise. Bias risk analysis and meta-analysis were performed. Twelve studies were included in the qualitative synthesis and five studies were encompassed in the quantitative synthesis (meta-analysis). For the Root-mean-square standard deviation (RMSSD) index we revealed p = 0.67, Total 95% confidence interval (95% CI) ranged from −0.45 to 0.29, and 66.7% for heterogeneity between groups were reported. Concerning the High Frequency (HF) index, we observed p = 0.22, Total 95% CI that ranged from −0.34 to 0.30, and 44% for heterogeneity between groups. ConclusionsCAF intake did not affect heart rate variability recovery after exercise.

Heart rate turbulence measurements in patients with dipper and non-dipper hypertension: the effects of autonomic functions

Hypertensive patients have shown autonomic dysfunction that is closely associated with the measurements of heart rate variability (HRV) and heart rate turbulence (HRT). We aimed to show the alterations of HRV and HRT measurements in patients with both dipper and non-dipper hypertension. This was a retrospective study consisting of one hundred and twenty-three participants (mean age ± SD, 55.7 ± 14.8 years; range, 18–90 years). The participants were divided into two groups: Group1: The patients with dipper hypertension, Group2: The patients with non-dipper hypertension. Two cardiologists performed HRV and HRT using 24-h electrocardiography (ECG) Holter and ambulatory blood pressure monitoring (ABPM) of patients. The results indicated that patients in group 2 had higher low frequency power/high frequency power ratio (LF/HF), lower high frequency power (HF) , root mean square of standard deviation (RMSSD) values than group 1 (p = 0.007, p = 0.008, and p = 0.002, respectively). Group 2 also showed higher heart rate turbulence onset (HRTTO) and lower heart rate turbulence slope (HRTTS) values than Group 1 (p = 0.004, p = 0.001, respectively). We performed multivariate analysis and observed that HRTTS and HRTTO have statistically significant associations with the presence of dipper or non-dipper hypertension [F = 7.755, p = 0.001], LF/HF [F = 7.868, p = 0.001], and HF [F = 4.081, p = 0.020]. This study shows a statistically significant difference in HRT measurements between dipper and non-dipper hypertensive patients. Deteriorated autonomic circadian rhythm and autonomic functions may contribute to these results.

Corneal stromal roughness after VisuMax and Intralase femtosecond laser photodisruption: An atomic force microscopy study.

PurposeTo compare the induced corneal stromal bed roughness measured with atomic force microscopy (AFM) after LASIK flap creation with the IntraLase 60 kHz and the VisuMax femtosecond laser platforms.MethodsThree freshly enucleated porcine eyes were operated with each femtosecond laser in this experimental study. Standard LASIK treatment parameters were used for the experiment. After LASIK flap creation, the corneal stromal roughness was assessed using a JPK NanoWizard II® AFM in contact mode immersed in liquid. Olympus OMCL-RC800PSA commercial silicon nitride cantilever tips were used. Surface measurements were made in 10 regions of the central cornea of each sample measuring 20 x 20 microns, at 512 x 512 point resolution. Roughness was measured using the root-mean-square (RMS) value within the given regions.ResultsMeasurements from 30 regions of the 3 eyes (10 measurements per eye) in the Intralase (FS1) group, and 30 regions of the 3 eyes (10 measurements per eye) in the VisuMax (FS2) group were analyzed. There was a statistically significant difference in mean ± standard deviation RMS values between the FS1 and the FS2 groups (360 ± 120 versus 230 ± 100 nm respectively; P< 0.00001).ConclusionThis AFM study indicates that the surface of the stromal bed after LASIK flap creation is smoother in the FS2 group than the FS1 group.

Test-retest reliability and smallest detectable change (SDC) of MRI-based cartilage thickness analysis in a large multicenter randomized controlled clinical trial of knee osteoarthritis

Test-retest reliability and smallest detectable change (SDC) of MRI-based cartilage thickness analysis in a large multicenter randomized controlled clinical trial of knee osteoarthritis

Analisis Diskriminan Terhadap Pengelompokan Mutu Pendidikan Sekolah Menengah Atas di Kabupaten Lamongan

Quality of education is the educational services ability that can fill the needs or expectations, satisfaction internally and externally which includes educational inputs, processes and outputs. The purpose of this reserach is to classify the quality of high school education in Lamongan District using factor, cluster and discriminant analysis. The dominant factors of 12 education quality variables can be known from the results of factor analysis using the PCA (Principal Component Analysis) method. The grouping of 48 high schools did by cluster analysis using 5 hierarchical methods. The validity index used to determine the optimal group number of the five hierarchical methods is RMSSTD (Root Mean Square Standard Deviation). The classification accuracy testing uses discriminant analysis based on the results of factor analysis and cluster analysis. Grouping the quality of education is influenced by dominant factors such as the number of classrooms, the value of accreditation, the number of certification and non-certification teachers, the number of education staff, the ratio of students to teachers, the number of laboratory rooms that can be known from the results of factor analysis. In cluster analysis, using the Mahalanobis distance because there is multicollinearity and the smallest RMSSTD index value obtained in the Complete Linkage method with 5 clusters. So, with discriminant analysis, it can be concluded that the grouping based on factor analysis and cluster analysis is 58.3% of the 48 processed data that has been entered in the group that matches the original data.

Impact of IGRT Frequency Upon Errors in Head and Neck Radiation: A Retrospective Analysis of Different Schedules.

The relationship between image guided radiation therapy (IGRT) frequency and errors remains unclear. We present this data obtained from various IGRT frequencies in head and neck cancer patients. All consecutive head and neck cancer patients receiving radiation with curative intent and daily IGRT using kV cone beam CT (CBCT) scans, between June and December 2018, were included in the study. Translational displacements in medial-lateral (ML), superior-inferior (SI) and anterior-posterior (AP) direction were documented daily. Four IGRT scenarios were simulated retrospectively with reducing frequency, namely, 50% (Displacement data of every alternate fraction), 30% (Displacement data of 1st 3 fractions followed by once weekly), 20% (Displacement data of once weekly fraction) and 10% (Displacement data of 1st 3 fractions). Displacement data for once weekly was documented from shifts acquired on treatment day 1, 6,11, 16 and so on. Mean Displacements (MD), Systematic Errors (Σ), Random Errors (σ) and Planning Target Volume (PTV) margins were calculated for daily and simulated scenarios (Table 1). Thirty-one patients were analyzed with a median age of 54.5 years (Inter-Quartile Range - 42.75 - 67), predominantly males (77.4%), commonly involving oral cavity (54.8%) and oropharynx (25.8%) and treated post-operatively (64.5%). A total of 831 CBCT scans were analyzed, demonstrating MD in ML, SI and AP were normally distributed across all the image guidance scenarios, except in SI direction for daily format (Kolmogorov-Smirnov test of normality; Skewness - 3.32, p = .05). MD in the three directions were <0.1cm, reflected in Σ (< 0.2cm) for daily and simulated IGRT scenarios; σ for different formats revealed that in SI direction, for daily format was 0.7cm, whereas it was around 0.2cm for simulated scenarios and these differences were demonstrated in PTV margin calculation, 1cm in SI direction based upon daily IGRT data and around 0.5cm based upon simulated IGRT scenarios; margin estimation was similar in ML and AP direction for daily and simulated IGRT scenarios (Table 1). MD >0.5cm were around 2-3% in ML and SI direction, and 5% in AP direction; whereas MD >0.3cm were ranging between 10-20%. Systematic and random errors were similar across all simulated IGRT scenarios, inconclusive for superiority of one schedule over another, however higher random errors were observed with daily format in SI direction. This further validates the need for more data in determining the optimum IGRT frequency.Tabled 1Abstract 2565; TableIGRT FrequencyMLSIAPErrors (Σ = standard deviation (SD) from values of mean displacement for all patients; σ = root mean square of SD of all patients)ΣσΣσΣσDaily0.110.200.210.700.120.2250%0.110.210.120.210.140.2230%0.130.220.140.200.120.2520%0.150.240.150.200.130.2710%0.150.250.140.200.140.28PTV Margin (Van Herk’s Formula) (2.5Σ + 0.7σ) (cm)MLSIAPDaily0.421.000.4650%0.430.440.5030%0.490.480.4820%0.540.510.5010%0.560.490.56 Open table in a new tab

Impact of Himalayan Singing Bowls Meditation Session on Mood and Heart Rate Variability – An Observational Study

Introduction Scientific evidence has demonstrated the psychological and physiological benefits of meditation. Sound vibrations also improve emotional wellbeing while enhancing the physiological parameters. There is an opportunity to explore the psychological and physiological benefits of Himalayan Singing Bowls (HSB) sound bath meditation, i.e. meditation assisted with sound vibrations. Aim of the Study The study explored changes in mood and Heart Rate Variability (HRV) parameters after a HSB Sound Bath Meditation on healthy individuals. The primary objectives of the study were to understand if a 40 minute long seated HSB Sound Bath Meditation results in significant improvement (a) in positive affect and negative affect, as measured by Positive And Negative Affect Scale (PANAS) and (b) in physiological parameters, as measured by Heart Rate Variability. The secondary objective of the study was to understand the impact on various moods as measured by Profile Of Mood States (POMS) Survey. Methods The psychological parameters included changes in Positive and Negative Affect (measured on 77 individuals using PANAS) and changes in specific, positive and negative moods (measured on 17 individuals using POMS) before and after the meditation session. The physiological parameters included HRV parameters such as Heart Rate (HR), Stress Index (SI) and Root Mean Square of Standard Deviation (RMSSD) measuring during the entire session on 15 individuals using the EmWave Pro device. HRV data analysis was conducted with Kubios HRV Premium and all the data was analyzed using paired T-Test. Results All the subjects after meditation showed statistically significant improvement in Positive Affect (mood) and a reduction in Negative Affect (mood). The HRV parameters showed a trend demonstrating overall relaxation with a statistically significant reduction in HR, Stress Index and an increase in RMSSD in the last 5 minutes as compared to the first 5 minutes. Consistent with changes in positive, negative mood and HRV, all the participants showed statistically significant reduction in tension, anger, fatigue, depression and confusion. In terms of positive mood, there was a statistically significant improvement in esteem related affect and an increase (but not statistically significant) in vigor. Conclusion The findings demonstrate that seated HSB Sound Bath Meditation session has a positive impact on the mood related measures. The physiological changes measured during the meditation using HRV parameters indicated a consistent reduction in Heart Rate throughout the meditation and a reduction in overall sympathetic tone and an increase in parasympathetic tone. Thus, HSB can be used to improve both psychological and physiological parameters even after one 40 min session. Future work in this area could explore comparison with a control group and a longer study duration consisting of multiple sessions.

Impact of reference point selection on DXA-based measurement of forearm bone mineral density.

Forearm fractures are clinically important outcomes from the perspective of morbidity, health care costs, and interruption of work. BMD of the forearm, as derived by dual-energy x-ray absorptiometry (DXA), is a better predictor of fracture at the forearm compared with BMD measured at other sites. However, very few studies have evaluated the technical aspects of selecting the ROI for forearm BMD measurement. This study aimed to compare the BMD values measured at the 1/3 radius site using three different reference points: the ulnar styloid process, the radial endplate, and the bifurcation of the ulna and radius. Healthy Chinese patients participating in the control group of an ongoing study at Zhejiang Provincial People's Hospital were recruited for this study. For each patient, a DXA scan (GE Lunar Prodigy) of the forearm was performed and BMD values were separately calculated using each of the three reference points to identify the ROI. Pearson correlation coefficients were calculated to examine the correlation between the BMD measures derived from each reference point. The F test and independent t test were applied for more robust analysis of the differences in the variances and means. Sixty-eight healthy Chinese volunteers agreed to participate in this study. The root mean square standard deviation (RMS-SD) percentages of BMD values measured at the 1/3 radius site were 2.19%, 2.23%, and 2.20% when using the ulnar styloid process, radial endplate, and the bifurcation of the ulna and radius as the reference points, respectively. Pearson's correlation coefficients for all pairwise comparisons among these three groups were greater than 0.99. F tests and independent t tests showed p values ranging from 0.92 to 0.99. However, we observed that among 10% of patients, choosing an ROI at the ulnar styloid process led to an inability to accurately determine the BMD at the ultra-distal radius. Given equal ability to determine BMD at the 1/3 radius accurately, the radial endplate or the bifurcation of the ulna and radius should be preferentially selected as the reference point for routine forearm BMD measurements in order to avoid situations in which the ultra-distal radius BMD cannot be determined.

Comparison of the Trueness of Lithium Disilicate Crowns Fabricated From All-in-One and Combination CAD/CAM Systems.

To examine and compare the trueness between a computer-aided design (CAD) file and the final milled prosthesis. For each included patient (n = 30), two lithium disilicate crowns were produced (n = 60) using two different CAD/computer-assisted manufacture (CAD/CAM) systems (all-in-one type and combination type). To compare the trueness, the scanned internal surfaces of the fabricated prostheses were compared to the design files in CAD using 3D analysis software (Geomagic Control X, 3D Systems). The mean ± standard deviation root mean square value for posterior teeth was 32.2 ± 9.4 in the combination type group and 43.8 ± 11.7 in the all-in-one type group, indicating higher trueness for the combination type (P < .05). This study has shown that the final milled prosthesis in combination type CAD/CAM systems had better trueness than the all-in-one system.

A reliable method for morphological measurement of 3D calcaneus models from computed tomography images.

The way to assess the calcaneal fractures reduction is still open. Anatomical morphology is an important clinical value to maintain normal function and may use as references to evaluate the reduction for calcaneal fractures. The aim of study is to provide reliable and repeatable three-dimensional (3D) morphology measurement. 3D models of ninety-nine Taiwanese normal calcaneus were reconstructed and segmented from CT image. Anatomical landmark serves as measurement constraints that manually identified and localized on bone mesh surface according to Gaussian curvature analysis. Computer assisted measurement and manual measurement were performed to quantify morphological parameters. Statistically, measurement results of calcaneal morphology were analyzed. The correlation between each of morphological parameters was tested using Bivariate-Pearson correlation. Gender differences relate to parameters were also tested. Intraclass correlation coefficient (ICC) and root mean square standard deviation (RMS-SD) were performed for reliable and precision study. Significant parameter differences between males and females were found (p 0.754). RMS-SD of precision for linear and angular measurement was adequate, around 0.8 mm and 1.7°. Morphological parameters for both male and female groups, 78.5 mm in length, 42.1 in height, 43.3 mm in width, 112.5° in Gissane angle, 33.4° in Bohler angle, which is not much different compared to Asian morphology population. The proposed method positively contributes to measurement calcaneal morphology with significant reliability and repeatability. This study may offer to be a basic data and reference for assessment calcaneal fracture reduction.

A novel online method for identifying motion artifact and photoplethysmography signal reconstruction using artificial neural networks and adaptive neuro-fuzzy inference system

Photoplethysmography (PPG) is a noninvasive technique to measure blood volume changes in blood vessels. Despite the wide usage of PPG signal in medical and non-medical applications, this signal can be affected by the motion artifacts leading to data loss. In this paper, we proposed an algorithm to detect motion artifacts and reconstruct the corrupted parts of the signal using real-time modeling based on multilayer perceptron (MLP), radial basis function (RBF) artificial neural networks (ANNs) and adaptive-neuro fuzzy inference system (ANFIS). The developed algorithm was applied to reconstruct the corrupted parts of PPG signals of 23 healthy 25- to 28-year-old volunteers. In the experimental phase, the left- and right-hand PPG signals of the volunteers were simultaneously obtained. While the left hand of the subjects were fixed, they were asked to shake their hands without any predetermined pattern, to simulate the real-life motion accelerations. To statistically and physiologically evaluate the performance of the proposed models, Pearson correlation coefficient (PCC), intraclass correlation coefficient (ICC), Bland–Altman plot (with the 95% limits of agreement), and time-domain feature analysis tests were adopted. The results indicated that the ANFIS with subtractive clustering algorithm shows the best performance in modeling the lost parts of the right-hand signals with an average PCC and ICC of 0.80 and 0.77, respectively, with the reference signal (left-hand signals) over all the tests. Also, the proposed ANFIS-based algorithm had an ability to retrieve the important time-domain PPG signal features, namely mean of inter-beat intervals (NN), standard deviations of NN (SDNN), root mean square of standard deviations (RMSSD) and standard deviation of standard deviations (SDSD) without any significant difference at p < 0.05 level to those of the reference signal (left-hand signal).

SSR-based genetic analysis of sweet corn inbred lines using artificial neural networks

Abstract Studies on genetic diversity and population structure provide basic information at the molecular level, which is a key input for breeding programs of crop species. This study evaluated the genetic diversity of 12 elite lines of sweet corn, using 20 microsatellite markers. To determine the genetic differentiation among lines, we used an artificial neural network with the self-organizing map (SOM) algorithm. This algorithm identified three genetically differentiated groups and produced relatively more accurate results than UPGMA, according to the indices of Davies-Bouldin and RMSSTD (Root Mean Square Standard Deviation). The expected heterozygosity was high (He>0.5) for 90% and the polymorphism information content high (PIC>0.6) for 40% of the SSR loci, indicating their potential to detect genetic differences among lines. The high genetic differentiation, detected by the neural network procedure, would allow the selection of promising divergent sweet corn genotypes.

Human-visual-perception-like intensity recognition for color rust images based on artificial neural network

Abstract Digital image processing has been applied to the assessment of steel bridge coating quality since the late 1990s. Most previously developed methods cluster rust images into two or three groups before calculating the rust percentage. Since two- or three-group clustering might not properly reflect the rust intensity or rusting severity on a rust image, the artificial-neural-network-based rust intensity recognition approach (ANNRI) is proposed in this paper. ANNRI integrates the root-mean-square standard deviation (RMSSTD) and artificial neural network (ANN) to cluster a rust image based on its rust intensity or rusting severity. RMSSTD measures the similarity of rust colors on a rust image, and an ANN trained with the results of a human visual rust inspection experiment would generate the optimal number of clusters for rust intensity recognition. Together with a pre-defined rust color spectrum, ANNRI is able to perform human-visual-perception-like rust intensity recognition and screen out background noises. According to the experiments conducted in this study, the proposed ANNRI can discriminate rust intensity much better than the existing methods with a fixed number of clusters.