Objective Evaluation Parameters Research Articles

Osteoporosis, spinal degenerative disorders, and their association with low back pain, activities of daily living, and physical performance in a general population

Osteoporosis, vertebral fractures, and spinal degenerative diseases are common conditions that often coexist in older adults. This study aimed to determine the factors influencing low back pain and its impact on activities of daily living (ADL) and physical performance in older individuals with multiple comorbidities. This cross-sectional study was part of a large-scale population-based cohort study in Japan, involving 1009 participants who underwent spinal magnetic resonance imaging (MRI) to assess cervical cord compression, radiographic lumbar spinal stenosis, and lumbar disc degeneration. Vertebral fractures in the thoracolumbar spine were evaluated using sagittal MRI with a semi-quantitative method. Bone mineral density was measured using dual-energy X-ray absorptiometry. Low back pain, Oswestry Disability Index (ODI), and physical performance tests, such as one-leg standing time, five times chair-stand time, maximum walking speed, and maximum step length, were assessed. Using clinical conditions as objective variables and image evaluation parameters as explanatory variables, multiple regression analysis showed that vertebral fractures were significantly associated with low back pain and ODI. Vertebral fractures and osteoporosis significantly impacted physical performance, whereas osteoporosis alone did not affect low back pain or ODI. Our findings contribute to new insights into low back pain and its impact on ADL and physical performance.

Underwater image classification based on image enhancement and information quality evaluation

Underwater target imaging is widely used in oceans, rivers and lakes detection fields, but due to the existence of water on light absorption scattering attenuation effect, the diffraction limit of imaging system, aberration distortion and underwater turbulence, underwater images has serious degradation, mainly manifested in noise, fuzzy and low resolution, etc. In recent years, some scholars have started from the image enhancement and restoration to improve the image degradation and improve the image clarity, but the effect still needs to be improved, and the resolution can not be improved, and some algorithms will even reduce the resolution.Resolution is an important parameter for the image evaluation, improving the image quality in the underwater imaging, especially in the human eye vision, which is largely determined by the improved resolution. Therefore, this paper starts from each aspects of image processing, studies, proposes and experiments a large number of image recovery algorithms. This paper analyzes various factors introducing noise in underwater imaging process, proposes block mixed filter image denoising method based on noise statistical characteristics, analyzes the necessity of evaluating image quality by using objective indicators, and gives the corresponding objective evaluation parameters according to the characteristics of the image recovery algorithm. According to the noise preprocessing method and the image quality evaluation method, the underwater image synthesis dataset is screened to improve the performance of the underwater object recognition model.

Comparative Studies of Single-Channel Speech Enhancement Techniques

Several speech enhancement techniques like Spectral Subtraction, MMSE, Log-MMSE, β -order MMSE, adaptive β -order MMSE and compressive sensing methods are developed worldwide. Scientists, engineers and researchers have implemented, evaluated and tested all methods individually with the different speech corpus. However, we found few articles on comparative studies of various speech enhancement techniques. In the present paper, several speech enhancement techniques have been studied, and their performance in terms of speech quality measures is compared objectively and subjectively. The results have been evaluated not only through speech quality measures but also in terms of waveform and spectrogram for speech enhancement applications. For this, MATLAB is used for the simulation of all methods. After getting the enhanced speech signals, we evaluated their enhanced speech signals of the methods. Results in terms of objective evaluation parameters indicated that the adaptive β -order MMSE-based method produces good-quality speech signals compared to the other methods. Also, we evaluated their enhanced speech signals using a listening test, i.e. subjective evaluation. In the subjective quality test through mean opinion score (using the listening test), the performance of the adaptive β -order MMSE method and GOMP are equal. In the case of waveform and spectrogram, the visualisation of enhanced speech signal obtained from GOMP-based compressive algorithms is very close to clean speech signal.

A Review on Orodispersible tablet

The oral route is the most important and recommended route of drug administration. Oral route is the safest and convenient route of drug delivery because of wide range of drugs are administered through this route. Oro dispersible tablets are novel oral drug-delivery system as they have improved patient compliance and have some additional advantages compared to other oral formulation. Oral dispersible tablet are solid unit dosage forms, which disintegrate or dissolves quickly in the mouth within a minute in the presence of saliva without chewing or water. The dosage form containing super disintegrates which impart the quality of quick disintegration in the presence of saliva and also play an important role in the formulation of oral dispersible tablets. The present review is focused on ideal properties, objective, advantages and disadvantages and evaluation parameters.

An efficient fragile watermarking scheme for tamper localization in satellite images

The applications of satellite images in various fields like oceanography, agriculture, biodiversity conservation, forestry, landscape, geology, regional planning, intelligence, and warfare are growing at a burgeoning rate. As satellite images carry very sensitive information, they need a secure and verifiable transmission over the network. To address the sensitive authentication issue and making the satellite images verifiable, this paper proposes an efficient ROI-based blind fragile watermarking approach. The proposed approach bundles the capability to not only verify the integrity of the watermarked satellite image but can also localize the regions where any intentional or unintentional tampering occurred in the watermarked satellite images with more than 90% accuracy. The proposed approach also achieves a good imperceptibility between the cover and watermarked satellite image in terms of PSNR (Average 60 dB). In the proposed approach, eight dynamically evolved progenies are generated corresponding to every ROI pixel. These progenies are tightly associated with each other at the bit level. The proposed approach hosts a sequence of algorithms, which when applied to these progenies, generates an authentication bit for every corresponding ROI pixel. The generated authentication bit is then embedded into the different intensities of RONI pixels. The selection of the number of bits per pixel to embed the watermark is decided dynamically. Detailed experimental results using various subjective and objective evaluation parameters have been presented to substantiate the imperceptibility and tamper localization capabilities of our proposed approach.

MP78-14 INTERNATIONAL EXPERT CONSENSUS ON DEVELOPMENT OF A STATE OF THE ART MALE GENITAL SIMULATION MODEL FOR URETHROPLASTY AND ARTIFICIAL URINARY SPHINCTER INSERTION

You have accessJournal of UrologyCME1 Apr 2023MP78-14 INTERNATIONAL EXPERT CONSENSUS ON DEVELOPMENT OF A STATE OF THE ART MALE GENITAL SIMULATION MODEL FOR URETHROPLASTY AND ARTIFICIAL URINARY SPHINCTER INSERTION Andrew Cohen, Marc (Toto) Abalajon, Katherine Anderson, Nima Baradaran, Cooper Benson, William Boysen, Benjamin Breyer, Arthur Burnett, Felix Campos, Lindsay Hampson, Ty Higuchi, Niels Johnsen, Nicolaas Lumen, Dmitriy Nikolavsky, Joseph Pariser, Jay Simhan, Alex Vanni, Nick Warner, E. James Wright, and Ahmed Ghazi Andrew CohenAndrew Cohen More articles by this author , Marc (Toto) AbalajonMarc (Toto) Abalajon More articles by this author , Katherine AndersonKatherine Anderson More articles by this author , Nima BaradaranNima Baradaran More articles by this author , Cooper BensonCooper Benson More articles by this author , William BoysenWilliam Boysen More articles by this author , Benjamin BreyerBenjamin Breyer More articles by this author , Arthur BurnettArthur Burnett More articles by this author , Felix CamposFelix Campos More articles by this author , Lindsay HampsonLindsay Hampson More articles by this author , Ty HiguchiTy Higuchi More articles by this author , Niels JohnsenNiels Johnsen More articles by this author , Nicolaas LumenNicolaas Lumen More articles by this author , Dmitriy NikolavskyDmitriy Nikolavsky More articles by this author , Joseph PariserJoseph Pariser More articles by this author , Jay SimhanJay Simhan More articles by this author , Alex VanniAlex Vanni More articles by this author , Nick WarnerNick Warner More articles by this author , E. James WrightE. James Wright More articles by this author , and Ahmed GhaziAhmed Ghazi More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003355.14AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: The number of available simulation-based models for technical skills training in urology is rapidly increasing, and development of training around these procedures should follow a structured approach. Utilizing modern education theory previously used to develop a hydrogel model for penile prosthesis placement, we aim to establish the criteria for development of a hydrogel male genital simulation model for Urethroplasty and Artificial Urinary Sphincter Insertion using international expert consensus. METHODS: 19 international experts of genitourinary reconstructive surgery were invited to participate in a three phase consensus building approach (modified Delphi technique). A total of 39 unique questions with 155 sub questions over three rounds were included in 4 categories 1) Overall utility of the model 2) anatomical and procedural components, 3) tissue fidelity and 4) evaluation of performance. Components reaching a content validity index (CVI) ≥0.80 were utilized to fabricate a prototype model. RESULTS: 106 of the 155 (68.3%) questions reached the consensus benchmark. Regarding utility, consensus was reached that a non-biohazardous urethral model and simulation-based platform would be very beneficial and should be developed using a validated educational approach. The expert panel agreed the simulator should allow for surgical practice in a risk free environment and allow performance evaluation. Consensus was reached on key anatomical components (Table 1) including an initial training focus of a 2 cm proximal bulbar stricture. The panel agreed a model should allow flexible application of urethroplasty techniques such as grafts. The addition of an obturator canal was prompted from the group given desires for future urethral sling simulation. Furthermore, the experts approved a framework for a standardized evaluation metric for urethroplasty. They agreed motion analysis wearables for efficiency of movement and retrograde infusion test for anastomotic integrity have value as objective standardized feedback. CONCLUSIONS: Harnessing the consensus of 19 international experts, the framework for a robust and bio-safe model for reconstructive urethral surgery with proposed objective evaluation parameters of surgical performance was achieved. Fabrication of the prototype based on this consensus statement is in development. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e1137 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Andrew Cohen More articles by this author Marc (Toto) Abalajon More articles by this author Katherine Anderson More articles by this author Nima Baradaran More articles by this author Cooper Benson More articles by this author William Boysen More articles by this author Benjamin Breyer More articles by this author Arthur Burnett More articles by this author Felix Campos More articles by this author Lindsay Hampson More articles by this author Ty Higuchi More articles by this author Niels Johnsen More articles by this author Nicolaas Lumen More articles by this author Dmitriy Nikolavsky More articles by this author Joseph Pariser More articles by this author Jay Simhan More articles by this author Alex Vanni More articles by this author Nick Warner More articles by this author E. James Wright More articles by this author Ahmed Ghazi More articles by this author Expand All Advertisement PDF downloadLoading ...

Objective assessment of vehicle controllability in straight-line motion

Introduction (statement of the problem and relevance). The problem of vehicle handling and stability during rectilinear motion was raised in the first half of the 20th century, and today this issue is still relevant. The requirements for handling, including during rectilinear movement of modern cars, are getting tougher. Straight-line stability and long-distance directional stability affect driver's fatigue, his driving safety and pleasure, as well as car fuel efficiency. Besides it, to provide modern driver assistance system, the car should possess good straight-line stability. At the same time, the design mustn't be affected by unbalanced forces and torques that could cause the trajectory deviation of the vehicle. There comes a need for an objective controllability and stability assessment of the car in a straight line.The purpose of the research was to analyze the existing methods for studying rectilinear motion controllability, to develop objective parameters for evaluating such motion, and to apply the worked out solutions when analyzing vehicle tests results.Methodology and research methods. Mathematical analysis, comparison, experiments, measurements were applied as research methods.Scientific novelty and results. The results have been presented in the form of a developed straight motion evaluation parameters list and were processed by calculating objective evaluation parameters. The scientific novelty is presented by the parameters of the driver's work objective assessment, and the first step has been made to correlate the objective and subjective assessment of the test driver.Practical significance. The developed method of the objective assessment can be applicable to all vehicles with traditional steering control.

Research on noise source separation and sound quality prediction for electric powertrain

The overall noise of the electric powertrain (EP) features the characteristics of high-frequency discreteness, abundant orders of harmonics, and serious howling. The consequent poor sound quality problems in the EP are frequently inevitable. In this paper, a complete set of sound quality evaluation system for EP noise signals is established, which closely combines the time-domain separation and sound quality evaluation. The EP noise source separation method in the time domain based on computational auditory scene analysis (CASA) and Robust-independent component analysis (ICA) is proposed to separate and identify EP independent noise sources. Five independent noise source signals in the time domain are then obtained, which could be played back for further psychoacoustic evaluation. The EP sound quality prediction method based on kernel principal component analysis (KPCA) and Lasso regression is proposed to develop the relationship between the subjective and objective quality for EP noise signals. Besides, the dimensionality of the objective evaluation parameters can be significantly reduced from nine to five. The experimental results indicate the superiority of the proposed prediction method to the traditional multiple linear regression approach on predicting the sound quality. A further deduction is made that the harmonic noise (HN) and switching noise (SN) can contribute more to sound quality of the EP overall noise and optimization on them can be a good choice.

Infrared and low-light-level image registration based on neighborhood difference chain code

The registration of the infrared (IR) image and the low-light-level (LLL) image remains a challenging problem due to poor dispersion of feature points, low correlation of structure and texture information. In this paper, we propose a method based on neighbourhood difference chain code to address the challenge. First we extracted the feature points of the images with the binary eight or sixteen-neighborhood information. And then construct the descriptor of the feature point by neighborhood difference chain code. At last we use the Euclidean distance to match the feature points. We adopt TNO and INO data sets to verify our method, and by comparing with four objective evaluation parameters obtained by other three methods. The result demonstrated that the proposed algorithm performs competitively, compared to the state-of-arts such as Harris, SIFT and SURF, in terms of accuracy of registration and speed.

Research on Optimization of car door closing sound quality based on the integration of structural simulation and test

People’s primary impression of the sound quality of a car usually comes from door closing sound, which brings the direct subjective feelings to customers. This article obtains a sample library of the sound of closing doors, conducts subjective evaluation and extracts objective evaluation parameters. The correlation between subjective and objective evaluation parameters is analyzed in this study. Then the Back Propagation (BP) neural network and support vector machine (SVM) prediction model is established with loudness and sharpness as inputs and subjective evaluation results as outputs. After comprehensive comparison, support vector machine prediction model with better training effect is used to predict the sound quality of door closing. Subsequently, the finite element model (FEM) and boundary element model (BEM) of automobile door are established for door closing sound simulation. The acceleration of the door obtained from the finite element simulation analysis is taken as the boundary condition, which is imported into the BEM of the door. The frequency domain diagram of the sound pressure of the car door is obtained using the boundary element method. The loudness and sharpness are extracted from the sound pressure diagram. They are imported into SVM prediction model to obtain the evaluation value of door closing sound quality. Eventually, the experimental research on the vibration and noise of car door closing is carried out. The acoustic signals obtained from the experiment and simulation are compared to verify the accuracy of the simulation results. After completing the above verification, from the perspective of sound quality, the sound quality of the door closing is improved by optimizing the structure of the door inner panel. Since then, a set of flow from door closing sound quality simulation to optimization to evaluation and prediction has been established. It provides an important reference for related research.

Colorization of fusion image of infrared and visible images based on parallel generative adversarial network approach

Fusing the infrared (IR) and visible images has many advantages and can be applied to applications such as target detection and recognition. Colors can give more accurate and distinct features, but the low resolution and low contrast of fused images make this a challenge task. In this paper, we proposed a method based on parallel generative adversarial networks (GANs) to address the challenge. We used IR image, visible image and fusion image as ground truth of ‘L’, ‘a’ and ‘b’ of the Lab model. Through the parallel GANs, we can gain the Lab data which can be converted to RGB image. We adopt TNO and RoadScene data sets to verify our method, and compare with five objective evaluation parameters obtained by other three methods based on deep learning (DL). It is demonstrated that the proposed approach is able to achieve better performance against state-of-arts methods.

Infrared and visible image fusion using salient decomposition based on a generative adversarial network.

In order to address the fusion problem of infrared (IR) and visible images, this paper proposes a method using a local non-subsampled shearlet transform (LNSST) based on a generative adversarial network (GAN). We first decompose the source images into basic images and salient images by LNSST, then use two GANs fuse basic images and salient images. Lastly, we compose the fused basic images and salient images by inverse LNSST. We adopt public data sets to verify our method and by comparing with eight objective evaluation parameters obtained by 10 other methods. It is demonstrated that our method is able to achieve better performance than the state of the art on preserving both texture details and thermal information.

A new evaluation and prediction model of sound quality of high-speed permanent magnet motor based on genetic algorithm-radial basis function artificial neural network.

Sound quality (SQ) has become an important index to measure the competitiveness of motor products. To better evaluate and optimize SQ, a novelty SQ evaluation and prediction model of high-speed permanent magnet motor (HSPMM) with better accuracy is presented in this research. Six psychoacoustic parameters of A-weighted sound pressure level (ASPL), loudness, sharpness, roughness, fluctuation strength (FS), and perferred-frequency speech interference (PSIL) were adopted to objectively evaluate the SQ of HSPMM under multiple operating conditions and subjective evaluation was also conducted by the combination of semantic subdivision method and grade scoring method. The evaluation results show that the SQ is poor, which will have a certain impact on human psychology and physiology. The correlation between the objective evaluation parameters and the subjective scores is analyzed by coupling the subjective and objective evaluation results. The average error of multiple linear regression (MLR) model is 7.10%. It has good accuracy, but poor stability. In order to improve prediction accuracy, a new predicted model of radial basis function (RBF) artificial neural network was put forward based on genetic algorithm (GA) optimization. Compared with MLR, its average error rate is reduced by 3.16% and the standard deviation is reduced by 1.841. In addition, the weight of each objective parameter was analyzed. The new predicted model has a better accuracy. It can evaluate and optimize the SQ exactly. The research methods and conclusions of this paper can be extended to the evaluation, prediction, and optimization of SQ of other motors.

Infrared and visible image fusion using two-layer generative adversarial network

Infrared (IR) images can distinguish targets from their backgrounds based on difference in thermal radiation, whereas visible images can provide texture details with high spatial resolution. The fusion of the IR and visible images has many advantages and can be applied to applications such as target detection and recognition. This paper proposes a two-layer generative adversarial network (GAN) to fuse these two types of images. In the first layer, the network generate fused images using two GANs: one uses the IR image as input and the visible image as ground truth, and the other with the visible as input and the IR as ground truth. In the second layer, the network transfer one of the two fused images generated in the first layer as input and the other as ground truth to GAN to generate the final fused image. We adopt TNO and INO data sets to verify our method, and by comparing with eight objective evaluation parameters obtained by other ten methods. It is demonstrated that our method is able to achieve better performance than state-of-arts on preserving both texture details and thermal information.

Independent and sensitive gait parameters for objective evaluation in knee and hip osteoarthritis using wearable sensors

BackgroundAlthough it is well-established that osteoarthritis (OA) impairs daily-life gait, objective gait assessments are not part of routine clinical evaluation. Wearable inertial sensors provide an easily accessible and fast way to routinely evaluate gait quality in clinical settings. However, during these assessments, more complex and meaningful aspects of daily-life gait, including turning, dual-task performance, and upper body motion, are often overlooked. The aim of this study was therefore to investigate turning, dual-task performance, and upper body motion in individuals with knee or hip OA in addition to more commonly assessed spatiotemporal gait parameters using wearable sensors.MethodsGait was compared between individuals with unilateral knee (n = 25) or hip OA (n = 26) scheduled for joint replacement, and healthy controls (n = 27). For 2 min, participants walked back and forth along a 6-m trajectory making 180° turns, with and without a secondary cognitive task. Gait parameters were collected using 4 inertial measurement units on the feet and trunk. To test if dual-task gait, turning, and upper body motion had added value above spatiotemporal parameters, a factor analysis was conducted. Effect sizes were computed as standardized mean difference between OA groups and healthy controls to identify parameters from these gait domains that were sensitive to knee or hip OA.ResultsFour independent domains of gait were obtained: speed-spatial, speed-temporal, dual-task cost, and upper body motion. Turning parameters constituted a gait domain together with cadence. From the domains that were obtained, stride length (speed-spatial) and cadence (speed-temporal) had the strongest effect sizes for both knee and hip OA. Upper body motion (lumbar sagittal range of motion), showed a strong effect size when comparing hip OA with healthy controls. Parameters reflecting dual-task cost were not sensitive to knee or hip OA.ConclusionsBesides more commonly reported spatiotemporal parameters, only upper body motion provided non-redundant and sensitive parameters representing gait adaptations in individuals with hip OA. Turning parameters were sensitive to knee and hip OA, but were not independent from speed-related gait parameters. Dual-task parameters had limited additional value for evaluating gait in knee and hip OA, although dual-task cost constituted a separate gait domain. Future steps should include testing responsiveness of these gait domains to interventions aiming to improve mobility.

The relationships between three-axis accelerometer measures of physical activity and motor symptoms in patients with Parkinson\u2019s disease: a single-center pilot study

BackgroundVarious wearable devices for objectively evaluating motor symptoms of patients with Parkinson’s disease (PD) have been developed. Importantly, previous studies have suggested protective effects of physical activity in PD. However, the relationships between conventional clinical ratings for PD and three-axis accelerometer measures of physical activity (e.g., daily physical activity levels [PAL] or metabolic equivalents of task [METs]) are still unclear, particularly for METs. In the current study, we sought to elucidate these relationships on a daily basis, and to clarify optimal predictors for clinical states on a 30-min basis.MethodsPatients who were hospitalized for adjustment of drugs or deep brain stimulation were enrolled. Using waist-worn three-axis accelerometers, PAL and METs parameter data were obtained and compared with UPDRS-3[On] and symptom diary data. We extracted data from the patients’ best and worst days, defined by the best and worst UPDRS-3[On] scores, respectively. Thus, 22 data sets from 11 patients were extracted. We examined the correlations and produced scatter plots to represent the relationships, then investigated which METs parameters and activity patterns were the best predictors for “On” and “dyskinesia”.ResultsThe parameter “mean METs value within the 95–92.5 percentile range on a day (95–92.5 percentile value)” exhibited the strongest correlation with conventional daily clinical ratings (Rho: − 0.799 for UPDRS-3[On], 0.803 for On hours [p < 0.001]). Scatter plots suggested that PAL tended to have higher values in patients with involuntary movement. However, METs parameters focusing on higher METs seemed to alleviate this tendency. We clarified that “time over 2.0 METs” and “time over 1.5 METs” could be predictors for “On” and “dyskinesia” on a 30-min basis, respectively (AUROC: 0.779 and 0.959, 95% CI: 0.733–0.824 and 0.918–1.000). The specificity and sensitivity of the optimal activity pattern for “On” were 0.858 and 0.621.ConclusionsThis study suggested feasible activity patterns and METs parameters for objective evaluation of motor symptoms on a 30-min or daily basis. Three-axis accelerometer measures focusing on higher METs may be appropriate for evaluating physical activity. Further larger-scale studies are necessary to clarify the validity, reliability, and clinical utility of these objective measures.

Sound Quality Prediction of Fuel Cell Vehicles Based on Regression Analysis

The typical fuel cell vehicle(FCV)was taken as the research object. The noise test of the FCV was carried out in the environment of the semi-anechoic room of the vehicle. The noise samples in the vehicle were collected under the condition of constant speed, which was intercepted and processed with equal time. Noise was subjectively evaluated using a pairwise comparison method. The objective evaluation parameters suitable for evaluating the sound quality of FCV were selected. The objective evaluation parameters were calculated and solved. According to the subjective and objective evaluation results of sound quality, run multiple linear regression analysis to quantitatively solve the correlation between the subjective and objective evaluation results. MAPE results showed that the accuracy of the multiple linear regression prediction model was low, in order to further improve the accuracy of the prediction model of the sound quality of FCVs, The GA-BP neural network prediction model was used to establish the evaluation prediction model between the subjective and objective evaluation results. The weight of the influence of objective parameters on the subjective evaluation results was calculated. The MAPE calculation results showed that the neural network model was more suitable for the establishment of FCV sound quality prediction According to the model, A-weighting and roughness were the most influential to the subjective evaluation results. The two algorithms had the same results.

Double vest lipodermal flaps for depressed facial scars.

Depressed tethered scar is a common problem that can cause emotional, social and behavioural problems, especially when it involves the exposed body parts. Several techniques have been described for treating these depressed scars, but none of these can fulfil the optimal results. Evaluating the aesthetic outcome of using a double vest lipodermal flaps for treating depressed facial scars. The study included 25 patients with depressed facial scars who underwent scar revision. Their mean age was 31 years. Under local anaesthesia, the scarred area was de-epithelialised and double dart lipodermal flaps were used for revision. Visual analogue and Vancouver scar scales were used as subjective and objective parameters of evaluation, respectively. All the patients followed up for five to eight months. No complications were observed during the scar healing period. Patients satisfaction according to the visual analogue scale showed an average value of 8. The mean total scale according to the Vancouver scar scale was 2.6. The new technique of using double vest lipodermal flaps is simple and offers a promising alternative for revising depressed scars.

Ergonomic evaluation and performance of a new handle for laparoscopic tools in surgery

This paper presents a new handle for instruments used in laparoscopic surgery. This new handle has been designed to provide the best ergonomic and usability features required in this kind of surgical interventions. The main novelty of this handle is that the opening and closing motion of the end-effector is operated with the thumb using a lever located on the top of the handle. This enables the surgeon to reach the patient's organs without adopting extremely awkward postures. In order to demonstrate its advantages, the handle has been tested and compared with another commercial handle in terms of efficiency, effectiveness, and satisfaction. To this end, volunteers have been selected for participation in the experimental evaluation, which comprised two types of surveys: objective and subjective. Electromyography and goniometric studies provide objective parameters for evaluation. Questionnaires are used for the subjective assessment. Outstanding results include the lower level of pain reported by the individuals working with the new handle, as well as the reduction in the hyperflexion of the wrist. Compared with the conventional handle, electromyography reveals that no muscle load is increased when working with the new handle. The results of the subjective survey show that volunteers expressed a significant preference for the new handle, demonstrating an improvement in the ergonomic characteristics.

Road Noise Evaluation by Sound Quality Simulation Module

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;An objective evaluation of sound quality is a technical bridge connecting sound pressure level (SPL) and human auditory sensation. In this paper, an algorithm is proposed for calculating objective evaluation parameters of sound quality (including loudness, sharpness and articulation index), considering acoustic characteristics of human external ear, middle ear and inner ear to reflect auditory sensation. A sound quality simulation (SQS) module is coded according to the algorithm. The module is used for evaluating sound quality of road noise from an SUV in three steps. Firstly, interior noise is predicted by integrating finite-element method (FEM), hybrid FE-SEA method, and statistical energy analysis (SEA) for low frequency (20~315 Hz), medium frequency (315~500 Hz), and high frequency (&amp;gt;500 Hz) in 1/3 octave band, respectively. The predicted interior noise SPLs are compared with the measured results, with deviations less than 3dB in average. Secondly, the sound quality parameters are calculated using the predicted SPLs in the SQS module. The predicted and measured loudness, sharpness, and articulation index are compared, with average deviations less than 5%. Finally, the predicted interior noise is filtered by the SQS module in 1/3 octave band, to determine the dominant contribution bands for the sound quality parameters. Several optimized designs are implemented to optimize the sound quality parameters, and validated by experiments.&lt;/div&gt;&lt;/div&gt;