Music During Cataract Surgery: Impact on Anxiety.

PURPOSE: To determine the effect of playing patient-selected music intra-operatively on patient self-reported anxiety and the amount of sedative administered during cataract surgery. SETTING: Yale New Haven Hospital health system, New Haven, CT. DESIGN: Prospective, randomized, controlled clinical trial. METHODS: Patients were randomized to either music group or control group, which had no music played. Patients were blinded to the purpose of the study. On postoperative day 1, patients were consented to participate in the study and asked to complete a six-question Likert-style survey (modified from the State-Trait Anxiety Inventory) assessing anxiety at baseline and during surgery. Patients' intraoperative and postoperative vitals were recorded. The medication, dosage, and number of sedative injections given were also recorded. Paired t-tests were used to assess for significant differences between the two groups. RESULTS: A total of 107 patients (mean age 71.2 years) were enrolled in the study. There was no significant difference in baseline anxiety between the two groups. Patients randomized to the music group had significantly lower total self-reported anxiety (mean 5.98) than the control group (mean 7.13, p=0.006). Moreover, patients exposed to music felt significantly less frightened, nervous, and confused during surgery (p=0.002, 0.007, and 0.017, respectively). There was no significant difference between the groups in number and dosage of sedatives given. CONCLUSION: Playing patient-selected music during cataract surgery is an effective way to decrease anxiety. Music has a direct impact on patient experience and is an inexpensive, low-risk method of reducing patient anxiety during surgery.

Surgical Time and Postoperative Symptoms Study in Pterygium Excision and Amniotic Membrane Graft Using Celularity Triple Layer Dehydrated Amniotic Membrane.

Purpose: To evaluate a novel sutureless glueless technique using a triple-layer dehydrated amniotic membrane (TLDAM) for pterygia excisions in surgical time, postoperative pain, epiphora, irritation, and FBS. Methods: Twenty eyes with pterygia underwent excision with mitomycin C. The conjunctival defect was closed with TLDAM placed on the dried scleral bed with the edges of the amniotic membrane tucked under the edges of the conjunctival defect. Surgical times were measured from injection of lidocaine to final placement of bandage contact lens. After a bandage contact lens was placed, the eye was patched until POD1. Patients graded self-administered questionnaires to rate pain, FBS, irritation, and epiphora on a scale of 1-5 (1-none; 5-severe) at POD1 and POW1. Results: Surgical times ranged from 6:55 to 12:00, with mean of 8:29. Compared with a previous study of sutureless glueless methodology, the difference in mean surgical time was 11.9 (p < 0.0001). Mean questionnaire scores were as follows: POD1 pain 1.8, FBS 2.3, irritation 1.0, and epiphora 2.6; POW1 pain 1.5, FBS 1.6, irritation 1.6, and epiphora 1.6. Compared to previous studies, this technique showed significantly improved pain at POD1 (p=0.0086, p<0.0001, p<0.0001, p<0.0001) and POW1 (p=0.0002, p=0.0016, p<0.0001). Significant improvement in irritation and FBS was noted at POD1 and POW1. See Table 1 for full analysis. Conclusion: The sutureless glueless technique using TLDAM is a safe and effective technique compared to current standard methods. There appears to be a significant benefit regarding surgical time and postoperative pain, irritation, epiphora, and FBS compared to previous studies.

Nivel de coordinación motriz de niños y niñas participantes del programa escuelas deportivas integrales del ministerio del deporte de Chile / Level of motor coordination in children participating in the integral sports schools program of chile's sports ministry

Hurtado Almonacid, J.G., Páez Herrera, J., Abusleme Allimant, R. Olate Gómez, F., Follegati Shore, S., Briones Oyanedel, V. y Mallea Díaz, V. (2023). Nivel de coordinación motriz de niños y niñas participantes del programa escuelas deportivas integrales del ministerio del deporte de Chile. PENSAR EN MOVIMIENTO: Revista de Ciencias del Ejercicio y la Salud, 21(1), 1-16. Durante los últimos años se ha identificado que una baja coordinación motriz general incide en una baja participación en instancias de juego libre, actividades deportivas organizadas y libres. A su vez, un mejor dominio motriz se relaciona con un bajo nivel de sedentarismo. Por lo tanto, el objetivo de este artículo fue comparar el nivel de coordinación motriz general de niños y niñas participantes del componente de Iniciación Deportiva del programa ''Escuelas Deportivas Integrales'' (EDI) del Ministerio del Deporte Chile (''Crecer en Movimiento'' desde 2019), según región de procedencia. En relación con la muestra, se evaluaron 341 niños y niñas de ocho regiones del país (Antofagasta, Coquimbo, Valparaíso, O'Higgins, Metropolitana, Bío-Bío, Araucanía y Los Lagos) cuyas edades fluctuaron entre los 6 y 11 años de edad. Para recopilar información, se utilizó el instrumento 3JS, compuesto por siete tareas (3 de locomoción y 4 de control de objetos). Los resultados reflejaron que los niños poseen mejor rendimiento que las niñas en coordinación motriz general. Al agrupar las pruebas del test según el tipo de coordinación, también superan a las damas en locomoción y en control de objetos. Los niños y niñas de la región de Los Lagos obtienen mejor rendimiento en seis de las siete pruebas. Se concluye que los varones superan a las damas en las pruebas de coordinación locomotriz y control de objetos, así como también en las puntuaciones de coordinación motriz general.

Hurtado Almonacid, J.G., Páez Herrera, J., Abusleme Allimant, R. Olate Gómez, F., Follegati Shore, S., Briones Oyanedel, V. & Mallea Díaz, V. (2023). Level of motor coordination in children participating in the integral sports schools program of chile's sports ministry. PENSAR EN MOVIMIENTO: Revista de Ciencias del Ejercicio y la Salud, 21(1), 1-16. In recent years, it has been detected that generally low motor coordination results in low participation in free play situations, organized and free sports activities. In turn, a better motor mastery is consistent with a low level of sedentary lifestyle. Therefore, the objective of this article is to compare the level of general motor coordination in children that participate in the Sports Initiation component of the ''Integral Sports Schools'' (EDI) program of Chile's Sports Ministry (since 2019, ''Growing in Movement''), according to the regions they come from. Concerning the sample, the assessment covered 341 boys and girls from eight different regions in the country (Antofagasta, Coquimbo, Valparaíso, O'Higgins, Metropolitan Region, Bío-Bío, Araucanía and Los Lagos), in ages ranging from 6 to 11. The information was gathered through the 3JS instrument, made up of seven tasks (3 in locomotion and 4 in object control). The results showed that boys have a better performance than girls in terms of general motor coordination. When the test data were grouped according to the type of coordination, boys are also above girls in terms of locomotion and object control. Boys and girls from the Los Lagos region performed better in six of seven tests. In conclusion, boys outperform girls in the tests of motor coordination and object control, as well as in the scores of general motor coordination.

Hurtado Almonacid, J.G., Páez Herrera, J., Abusleme Allimant, R. Olate Gómez, F., Follegati Shore, S., Briones Oyanedel, V. e Mallea Díaz, V. (2023). Nível de coordenação motora das crianças que participam do programa escolas esportivas integrais do ministério do esporte do Chile. PENSAR EN MOVIMIENTO: Revista de Ciencias del Ejercicio y la Salud, 21(1), 1-16. Nos últimos anos, identificou-se que a baixa coordenação motora geral tem um impacto na baixa participação em atividades de jogos livres, atividades esportistas organizadas e livres. Por sua vez, uma melhor dominância motora está relacionada com um baixo nível de sedentarismo. Portanto, o objetivo deste artigo foi comparar o nível de coordenação motora geral das crianças participantes do componente de Iniciação Esportiva do programa "Escolas Esportivas Integrais" (EEI) do Ministério do Esporte do Chile ("Crescendo em Movimento" desde 2019), segundo a região de origem. Em relação à amostra, foram avaliadas 341 crianças de oito regiões do país (Antofagasta, Coquimbo, Valparaíso, O'Higgins, Metropolitana, Bío-Bío, Araucanía e Los Lagos) com idades entre 6 e 11 anos. Para a coleta de informações, foi utilizado o instrumento 3JS, composto por sete tarefas (3 de locomoção e 4 de controle de objetos). Os resultados mostraram que os meninos têm melhor desempenho do que as meninas na coordenação motora geral. Ao agrupar os testes de acordo com o tipo de coordenação, eles também superam as meninas em locomoção e controle de objetos. As crianças da região de Los Lagos tiveram melhor desempenho em seis dos sete testes. Conclui-se que os meninos superam as meninas nos testes de coordenação locomotora e controle de objetos, bem como nos escores gerais de coordenação motora.

¿Son los implantes "personalizados" una solución en la cirugía de revisión acetabular? A propósito de un caso / Are customized implants a solution in acetabular revision surgery? A case study

Se presenta a un paciente de 73 años que había sido sometido a dos revisiones de prótesis de cadera debido a una infección crónica por un microorganismo multirresistente. Acude a nuestro centro tras un primer tiempo quirúrgico. En la radiografía simple y la tomografía computarizada, se observan un defecto femoral tipo IV y un defecto acetabular tipo IIIA de Paprosky. Tras un control clínico y análisis de laboratorio, se decide la reconstrucción acetabular mediante un implante "personalizado" y un vástago tumoral. A los 2 años, el paciente evoluciona favorablemente: deambula con bastón y sin dolor. El implante está estable y en posición normal, no hubo recidiva infecciosa. Nivel de Evidencia: IV

We present the case of a 73-year-old patient, previously treated with two hip prosthesis revisions due to a chronic infection caused by a multidrug-resistant microorganism, who consulted after the first surgical procedure. Radiographic and computed tomography studies revealed a Paprosky type IV femoral defect and a type IIIA acetabular defect. Following clinical and laboratory monitoring, it was decided to perform acetabular reconstruction using a custom-made implant and a tumor stem. Two years later, the patient shows a favorable evolution: he is able to walk with a cane and without pain. The implant is stable and properly positioned, with no recurrent infection. Level of Evidence: IV

Blockchain Assisted Disease Identification of COVID-19 Patients with the Help of IDA-DNN Classifier.

Globally, millions of people were affected by the Corona-virus disease-2019 (COVID-19) causing loads of deaths. Most COVID-19 affected people recover in a few spans of weeks. However, certain people even those with a milder variant of the disease persist in experiencing symptoms subsequent to their initial recuperation. Here, a novel Block-Chain (BC)-assisted optimized deep learning algorithm, explicitly improved dragonfly algorithm based Deep Neural Network (IDA-DNN), is proposed for detecting the different diseases of the COVID-19 patients. Initially, the input data of the COVID-19 recovered patients are gathered centered on their post symptoms and their data is amassed as a BC for rendering security to the patient's data. After that, the disease identification of the patient's data is performed with the aid of system training. The training includes '4' disparate datasets for data collection, and then, performs preprocessing, Feature Extraction (FE), Feature Reduction (FR), along with classification utilizing ID-DNN on the gathered inputted data. The IDA-DNN classifies '2' classes (presence of disease and absence of disease) for every type of data. The proposed method's outcomes are examined as well as contrasted with the other prevailing techniques to corroborate that the proposed IDA-DNN detects the COVID-19 more efficiently.

Design of an Estimator Using the Artificial Neural Network Technique to Characterise the Braking of a Motor Vehicle.

Automatic systems are increasingly being applied in the automotive industry to improve driving safety and passenger comfort, reduce traffic and increase energy efficiency. The objective of this work is focused on improving the automatic brake assistance systems of motor vehicles trying to imitate human behaviour but correcting possible human errors such as distractions, lack of visibility or time reaction. The proposed system can optimise the intensity of the braking according to the available distance to carry out the manoeuvre and the vehicle speed to be as less aggressive as possible, thus giving priority to the comfort of the driver. A series of tests are carried out in this work with a vehicle instrumented with sensors that provide real-time information about the braking system. The data obtained experimentally during the dynamic tests are used to design an estimator using the Artificial Neural Network (ANN) technique. This information makes it possible to characterise all braking situations based on the pressure of the brake circuit, the type of manoeuvre and the test speed. Thanks to this ANN, it is possible to estimate the requirements of the braking system in real driving situations and carry out the manoeuvres automatically. Experiments and simulations verified the proposed method for the estimation of braking pressure in real deceleration scenarios.

Attribute-Based Adaptive Homomorphic Encryption for Big Data Security.

There is a drastic increase in Internet usage across the globe, thanks to mobile phone penetration. This extreme Internet usage generates huge volumes of data, in other terms, big data. Security and privacy are the main issues to be considered in big data management. Hence, in this article, Attribute-based Adaptive Homomorphic Encryption (AAHE) is developed to enhance the security of big data. In the proposed methodology, Oppositional Based Black Widow Optimization (OBWO) is introduced to select the optimal key parameters by following the AAHE method. By considering oppositional function, Black Widow Optimization (BWO) convergence analysis was enhanced. The proposed methodology has different processes, namely, process setup, encryption, and decryption processes. The researcher evaluated the proposed methodology with non-abelian rings and the homomorphism process in ciphertext format. Further, it is also utilized in improving one-way security related to the conjugacy examination issue. Afterward, homomorphic encryption is developed to secure the big data. The study considered two types of big data such as adult datasets and anonymous Microsoft web datasets to validate the proposed methodology. With the help of performance metrics such as encryption time, decryption time, key size, processing time, downloading, and uploading time, the proposed method was evaluated and compared against conventional cryptography techniques such as Rivest-Shamir-Adleman (RSA) and Elliptic Curve Cryptography (ECC). Further, the key generation process was also compared against conventional methods such as BWO, Particle Swarm Optimization (PSO), and Firefly Algorithm (FA). The results established that the proposed method is supreme than the compared methods and can be applied in real time in near future.

LMI-Based H∞ Controller of Vehicle Roll Stability Control Systems with Input and Output Delays.

Many of the current research works are focused on the development of different control systems for commercial vehicles in order to reduce the incidence of risky driving situations, while also improving stability and comfort. Some works are focused on developing low-cost embedded systems with enough accuracy, reliability, and processing time. Previous research works have analyzed the integration of low-cost sensors in vehicles. These works demonstrated the feasibility of using these systems, although they indicate that this type of low-cost kit could present relevant delays and noise that must be compensated to improve the performance of the device. For this purpose, it is necessary design controllers for systems with input and output delays. The novelty of this work is the development of an LMI-Based H∞ output-feedback controller that takes into account the effect of delays in the network, both on the sensor side and the actuator side, on RSC (Roll Stability Control) systems. The controller is based on an active suspension with input and output delays, where the anti-roll moment is used as a control input and the roll rate as measured data, both with delays. This controller was compared with a controller system with a no-delay consideration that was experiencing similar delays. The comparison was made through simulation tests with a validated vehicle on the TruckSim® software.

An optimal cascaded recurrent neural network for intelligent COVID-19 detection using Chest X-ray images.

In recent times, COVID-19, has a great impact on the healthcare sector and results in a wide range of respiratory illnesses. It is a type of Ribonucleic acid (RNA) virus, which affects humans as well as animals. Though several artificial intelligence-based COVID-19 diagnosis models have been presented in the literature, most of the works have not focused on the hyperparameter tuning process. Therefore, this paper proposes an intelligent COVID-19 diagnosis model using a barnacle mating optimization (BMO) algorithm with a cascaded recurrent neural network (CRNN) model, named BMO-CRNN. The proposed BMO-CRNN model aims to detect and classify the existence of COVID-19 from Chest X-ray images. Initially, pre-processing is applied to enhance the quality of the image. Next, the CRNN model is used for feature extraction, followed by hyperparameter tuning of CRNN via the BMO algorithm to improve the classification performance. The BMO algorithm determines the optimal values of the CRNN hyperparameters namely learning rate, batch size, activation function, and epoch count. The application of CRNN and hyperparameter tuning using the BMO algorithm shows the novelty of this work. A comprehensive simulation analysis is carried out to ensure the better performance of the BMO-CRNN model, and the experimental outcome is investigated using several performance metrics. The simulation results portrayed that the BMO-CRNN model has showcased optimal performance with an average sensitivity of 97.01%, specificity of 98.15%, accuracy of 97.31%, and F-measure of 97.73% compared to state-of-the-art methods.

Internet of things-based intelligent physical support framework using future internet of things.

BACKGROUND: Physical exercise programs are required to improve students' physical ability, physical fitness, self-responsibility, and satisfaction to remain physically active for a lifetime. The supporting system's demanding characteristics include lack of school leadership support, and lack of communication skills among students is considered an essential factor in the physical education system. OBJECTIVE: In this paper, an Internet of Things (IoT)-based intelligent physical support framework (IoT-IPSF) has been proposed to encourage education leadership and student social interaction in the physical education system. METHOD: Training service analysis is introduced to improve adequate leadership support, helping in the physical education system's growth. Self-determination analysis is integrated with IoT-IPSF to enhance effective communication among school teachers, educational experts, and curriculum officers in the physical education system. RESULTS: The simulation results show that the proposed method achieves a high accuracy ratio of 98.7%, an efficiency ratio of 95.6, student performance 97.8%, fitness level 82.3%, activity involvement 94.5% compared to other existing models.

Holistic Vehicle Instrumentation for Assessing Driver Driving Styles.

Nowadays, autonomous vehicles are increasing, and the driving scenario that includes both autonomous and human-driven vehicles is a fact. Knowing the driving styles of drivers in the process of automating vehicles is interest in order to make driving as natural as possible. To this end, this article presents a first approach to the design of a controller for the braking system capable of imitating the different manoeuvres that any driver performs while driving. With this aim, different experimental tests have been carried out with a vehicle instrumented with sensors capable of providing real-time information related to the braking system. The experimental tests consist of reproducing a series of braking manoeuvres at different speeds on a flat floor track following a straight path. The tests distinguish between three types of braking manoeuvre: maintained, progressive and emergency braking, which cover all the driving circumstances in which the braking system may intervene. This article presents an innovative approach to characterise braking types thanks to the methodology of analysing the data obtained by sensors during experimental tests. The characterisation of braking types makes it possible to dynamically classify three driving styles: cautious, normal and aggressive. The proposed classifications allow it possible to identify the driving styles on the basis of the pressure in the hydraulic brake circuit, the force exerted by the driver on the brake pedal, the longitudinal deceleration and the braking power, knowing in all cases the speed of the vehicle. The experiments are limited by the fact that there are no other vehicles, obstacles, etc. in the vehicle's environment, but in this article the focus is exclusively on characterising a driver with methods that use the vehicle's dynamic responses measured by on-board sensors. The results of this study can be used to define the driving style of an autonomous vehicle.

Clinical relevance of marginal factors on ultrafiltration in peritoneal dialysis.

BACKGROUND: Ultrafiltration (UF) in peritoneal dialysis (PD) is mainly driven by the osmotic gradient and peritoneal permeability, but other factors-such as intraperitoneal pressure (IPP)-also have an influence. METHODS: To assess the clinical relevance of these marginal factors, we studied 41 unselected PD patients undergoing two consecutive 2 h, 2.27% glucose exchanges, first with 2.5 L and then with 1.5 L. RESULTS: IPP, higher in the 2.5 L exchange, had a wide interpatient range, was higher in obese and polycystic patients and their increase with infusion volume was higher for women regardless of body size. UF with 2.5 L correlated inversely with IPP and was higher for patients with polycystosis or hernias, while for 1.5 L we found no significant correlations. The effluent had higher glucose and osmolarity in the 2.5 L exchange than in the 1.5 L one, similar for both sexes. In spite of this stronger osmotic gradient, only 21 patients had more UF in the 2.5 L exchange, with differences up to 240 mL. The other 20 patients had more UF in the 1.5 L exchange, with stronger differences (up to 800 mL, and more than 240 mL for 9 patients). The second group, with similar effluent osmolarity and peritoneal equilibration test (PET) parameters than the first, has higher IPP and preponderance of men. The sex influence is so intense that men decreased average UF with 2.5 L with respect to 1.5 L, while women increased it. CONCLUSIONS: With 2.27% glucose, sex and IPP-modulated by obesity, polycystosis, hernias, and intraperitoneal volume-significantly affect UF in clinical settings and might be useful for its management.

Intraperitoneal pressure: Stability over time and validation of Durand's measurement method.

Intraperitoneal pressure (IPP) is gaining consideration as a relevant parameter of peritoneal dialysis (PD) in adults, although many of its aspects are still pending clarification. We address here its stability over time and the validity of the usual method of clinical measurement, as proposed by Durand in 1992 but never specifically validated. We performed this validation by comparing Durand's method and direct measurements with a central venous pressure system. We performed a total of 250 measurement pairs in 50 patients with different intraperitoneal volumes plus in-vitro measurements with a simulated peritoneum. Absolute differences between the two systems in vivo were 0.87 ± 0.91 cmH2O (range 0-5 cmH2O); only 6.4% of them were ≥3 cmH2O. In vitro results for both methods were identical. We also compared IPP measurements in the same patient separated by 1-4 h (514 measurement pairs in 136 patients), 1 week (92 pairs in 92 patients), and 2 years (34 pairs in 17 patients). Net differences of measurements separated by hours or 1 week were close to 0 cmH2O, with oscillations of 1.5 cmH2O in hours and 2.3 cmH2O in 1 week. IPP measured 2 years apart presented a net decrease of 2.5 ± 4.9 cmH2O, without correlation with body mass index changes or any other usual parameter of PD. In hours, 7% of IPP differences were >3 cmH2O, 22% in 1 week, and 50% in 2 years. In conclusion, Durand's method is precise enough to measure IPP in peritoneal dialysis. This parameter is not stable over long timescales, so it is necessary to use recent measurements.

Development and Characterization of a Compact Device for Measuring the Braking Torque of a Vehicle.

In this article, a new force transducer is designed, developed and built for the measurement of braking forces in the wheel rim of a motor vehicle. The parameters of the transducer design are justified using numerical simulation. In order to install it in the vehicle in a simple and interference-free way, the metal base of the caliper rod is used. It is manufactured and installed in a vehicle in order to obtain the signals of the wheel braking torque, in real time, and at different speeds of circulation, carrying out several tests on the track. Subsequently, data are obtained from calculations of the disc brake system itself. The latter provides instantaneous adherence values between the brake pad and the disc.

PyDSLRep: A domain-specific language for robotic simulation in V-Rep.

Calculating forward and inverse kinematics for robotic agents is one of the most time-intensive tasks when controlling the robot movement in any environment. This calculation is then encoded to control the motors and validated in a simulator. The feedback produced by the simulation can be used to correct the code or to implement the code can be implemented directly in the robotic agent. However, the simulation process executes instructions that are not native to the robotic agents, extending development time or making it preferable to validate the code directly on the robot, which in some cases might result in severe damage to it. The use of Domain-Specific Languages help reduce development time in simulation tasks. These languages simplify code generation by describing tasks through an easy-to-understand language and free the user to use a framework or programming API directly for testing purposes. This article presents the language PyDSLRep, which is characterized by the connection and manipulation of movement in mobile robotic agents in the V-Rep simulation environment. This language is tested in three different environments by twenty people, against the framework given by V-Rep, demonstrating that PyDSLRep reduces the average development time by 45.22%, and the lines of code by 76.40% against the Python framework of V-Rep.

An artificial neural network approach for predicting hypertension using NHANES data.

This paper focus on a neural network classification model to estimate the association among gender, race, BMI, age, smoking, kidney disease and diabetes in hypertensive patients. It also shows that artificial neural network techniques applied to large clinical data sets may provide a meaningful data-driven approach to categorize patients for population health management, and support in the control and detection of hypertensive patients, which is part of the critical factors for diseases of the heart. Data was obtained from the National Health and Nutrition Examination Survey from 2007 to 2016. This paper utilized an imbalanced data set of 24,434 with (69.71%) non-hypertensive patients, and (30.29%) hypertensive patients. The results indicate a sensitivity of 40%, a specificity of 87%, precision of 57.8% and a measured AUC of 0.77 (95% CI [75.01-79.01]). This paper showed results that are to some degree more effectively than a previous study performed by the authors using a statistical model with similar input features that presents a calculated AUC of 0.73. This classification model can be used as an inference agent to assist the professionals in diseases of the heart field, and can be implemented in applications to assist population health management programs in identifying patients with high risk of developing hypertension.

A Strain-Based Intelligent Tire to Detect Contact Patch Features for Complex Maneuvers.

Tires are essential components of vehicles and are able to transmit traction and braking forces to the contact patch, contribute to directional stability, and also help to absorb shocks. If these components can provide information related to the tire-road interaction, vehicle safety can be increased. This research is focused on developing the tire as an active sensor capable to provide its functional parameters. Therefore, in this work, we studied strain-based measurements on the contact patch to develop an algorithm to compute the wheel velocity at the contact point, the effective rolling radius and the contact length on dynamic situations. These parameters directly influence the dynamics of wheel behavior which nowadays is not clearly defined. Herein, hypotheses have been assumed based on previous studies to develop the algorithm. The results expose to view an experimental test regarding influence of the tire operational condition (slip angle, vertical load, and rolling velocity) onto the computed parameters. This information is used to feed a fuzzy logic system capable of estimating the effective radius and contact length. Furthermore, a verification process has been carried out using CarSim simulation software to get the inputs for the fuzzy logic system at complex maneuvers.

Validation of a Low-Cost Electromyography (EMG) System via a Commercial and Accurate EMG Device: Pilot Study.

Electromyography (EMG) devices are well-suited for measuring the behaviour of muscles during an exercise or a task, and are widely used in many different research areas. Their disadvantage is that commercial systems are expensive. We designed a low-cost EMG system with enough accuracy and reliability to be used in a wide range of possible ways. The present article focuses on the validation of the low-cost system we designed, which is compared with a commercially available, accurate device. The evaluation was done by means of a set of experiments, in which volunteers performed isometric and dynamic exercises while EMG signals from the rectus femoris muscle were registered by both the proposed low-cost system and a commercial system simultaneously. Analysis and assessment of three indicators to estimate the similarity between both signals were developed. These indicated a very good result, with spearman's correlation averaging above 0.60, the energy ratio close to the 80% and the linear correlation coefficient approximating 100%. The agreement between both systems (custom and commercial) is excellent, although there are also some limitations, such as the delay of the signal (<1 s) and noise due to the hardware and assembly in the proposed system.

Is the Use of a Low-Cost sEMG Sensor Valid to Measure Muscle Fatigue?

Injuries caused by the overstraining of muscles could be prevented by means of a system which detects muscle fatigue. Most of the equipment used to detect this is usually expensive. The question then arises whether it is possible to use a low-cost surface electromyography (sEMG) system that is able to reliably detect muscle fatigue. With this main goal, the contribution of this work is the design of a low-cost sEMG system that allows assessing when fatigue appears in a muscle. To that aim, low-cost sEMG sensors, an Arduino board and a PC were used and afterwards their validity was checked by means of an experiment with 28 volunteers. This experiment collected information from volunteers, such as their level of physical activity, and invited them to perform an isometric contraction while an sEMG signal of their quadriceps was recorded by the low-cost equipment. After a wavelet filtering of the signal, root mean square (RMS), mean absolute value (MAV) and mean frequency (MNF) were chosen as representative features to evaluate fatigue. Results show how the behaviour of these parameters across time is shown in the literature coincides with past studies (RMS and MAV increase while MNF decreases when fatigue appears). Thus, this work proves the feasibility of a low-cost system to reliably detect muscle fatigue. This system could be implemented in several fields, such as sport, ergonomics, rehabilitation or human-computer interactions.

A Strain-Based Method to Estimate Tire Parameters for Intelligent Tires under Complex Maneuvering Operations.

The possibility of using tires as active sensors opens the door to a huge number of different ways to accomplish this goal. In this case, based on a tire equipped with strain sensors, also known as an Intelligent Tire, relevant vehicle dynamics information can be provided. The purpose of this research is to improve the strain-based methodology for Intelligent Tires to estimate all tire forces, based only on deformations measured in the contact patch. Firstly, through an indoor test rig data, an algorithm has been developed to pick out the relevant features of strain data and correlate them with tire parameters. This information of the tire contact patch is then transmitted to a fuzzy logic system to estimate the tire parameters. To evaluate the reliability of the proposed estimator, the well-known simulation software CarSim has been used to back up the estimation results. The software CarSim has been used to provide the vehicle parameters in complex maneuvers. Finally, the estimations have been checked with the simulation results. This approach has enabled the behaviour of the intelligent tire to be tested for different maneuvers and velocities, providing key information about the tire parameters directly from the only contact that exists between the vehicle and the road.