Now showing 1 - 10 of 21
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    Optimizing Electrical Systems Stability: A Novel Lyapunov Framework for Harmonic Reduction and Power Quality Enhancement
    (IEEE, 2024-08-05)
    Wilson Pavón
    ;
    Michael Chamorro
    ;
    Ismael Michala
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    ;
    Mohan Kolhe
    This study investigates power quality improvement through a Lyapunov-based harmonic reduction strategy utilizing an Active Hybrid Power Filter (SHAPF). Central to this approach is the application of state feedback to maintain system stability. A practical case study examining the influence of a Nonlinear Load (NLL) on an IEEE 13-bus distribution system validates the proposed methodology. Implemented and scrutinized via Matlab/Simulink, this research encompasses the detailed modeling of the SHAPF, its control strategies, and the analysis of harmonic distortion data. Such an in-depth simulation facilitates a rigorous evaluation of the method in conditions mirroring real-world scenarios, shedding light on its efficacy and applicability. Harnessing the principles of Lyapunov theory alongside advanced control techniques, the objective is to markedly diminish harmonic distortions in power systems, thereby significantly improving power quality and Electrical Compatibility (EC). This contribution highlights a commitment to enhancing the reliability and quality of modern power system engineering through innovative solutions.
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    RoboGait: sistema robótico no invasivo para el análisis de la marcha humana
    (Universitat Politecnica de Valencia, 2023-10-31)
    David Álvarez
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    ;
    Alberto Brunete
    ;
    Miguel Hernando
    ;
    Ernesto Gambao
    Actualmente, los sistemas utilizados en laboratorios para analizar la marcha se basan en técnicas marcadores o sensores colocados sobre el cuerpo del paciente, lo que resulta en un proceso que requiere un tiempo largo de preparación y calibración, así como la incomodidad que causa a los pacientes tener dispositivos colocados por el cuerpo. Además, el espacio en el que se pueden realizar pruebas resulta muy limitado. En respuesta a estas problemáticas, se ha desarrollado el sistema robótico RoboGait. Consiste en un robot móvil capaz de navegar autónomamente delante del paciente. El robot incluye una cámara RGBD en su parte superior para captar el cuerpo humano. Este sistema no requiere marcadores adheridos al cuerpo del paciente ya que utiliza la información proporcionada por la cámara RGBD para analizar la marcha. El objetivo de este estudio es demostrar la validez de RoboGait y su aplicabilidad en entornos clínicos. Para conseguirlo, se ha optado por mejorar la estimación de señales cinemáticas y espacio-temporales de la marcha procesando las medidas de la cámara con redes neuronales artificiales (RNA) entrenadas usando datos obtenidos de un sistema Vicon certificado. Posteriormente, se ha medido el rendimiento del sistema en la clasificación de patrones normales y patológicos, utilizando como referencia un sistema basado en sensores inerciales Xsens. De este modo, se ha probado el sistema robótico móvil en un rango amplio de la marcha, al tiempo que se ha comparado con un sistema comercial en las mismas condiciones experimentales. Los resultados obtenidos demuestran que RoboGait puede realizar el análisis de la marcha con suficiente precisión,mostrando un gran potencial para su análisis clínico y la identificación de patologías.
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    Performance of a Mobile 3D Camera to Evaluate Simulated Pathological Gait in Practical Scenarios
    (MDPI AG, 2023-08-04) ;
    Daniel Lemus
    ;
    Heike Vallery
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    Alberto Brunete
    ;
    Miguel Hernando
    Three-dimensional (3D) cameras used for gait assessment obviate the need for bodily markers or sensors, making them particularly interesting for clinical applications. Due to their limited field of view, their application has predominantly focused on evaluating gait patterns within short walking distances. However, assessment of gait consistency requires testing over a longer walking distance. The aim of this study is to validate the accuracy for gait assessment of a previously developed method that determines walking spatiotemporal parameters and kinematics measured with a 3D camera mounted on a mobile robot base (ROBOGait). Walking parameters measured with this system were compared with measurements with Xsens IMUs. The experiments were performed on a non-linear corridor of approximately 50 m, resembling the environment of a conventional rehabilitation facility. Eleven individuals exhibiting normal motor function were recruited to walk and to simulate gait patterns representative of common neurological conditions: Cerebral Palsy, Multiple Sclerosis, and Cerebellar Ataxia. Generalized estimating equations were used to determine statistical differences between the measurement systems and between walking conditions. When comparing walking parameters between paired measures of the systems, significant differences were found for eight out of 18 descriptors: range of motion (ROM) of trunk and pelvis tilt, maximum knee flexion in loading response, knee position at toe-off, stride length, step time, cadence; and stance duration. When analyzing how ROBOGait can distinguish simulated pathological gait from physiological gait, a mean accuracy of 70.4%, a sensitivity of 49.3%, and a specificity of 74.4% were found when compared with the Xsens system. The most important gait abnormalities related to the clinical conditions were successfully detected by ROBOGait. The descriptors that best distinguished simulated pathological walking from normal walking in both systems were step width and stride length. This study underscores the promising potential of 3D cameras and encourages exploring their use in clinical gait analysis.</jats:p>
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    The Accuracy of the Microsoft Kinect V2 Sensor for Human Gait Analysis. A Different Approach for Comparison with the Ground Truth
    (MDPI AG, 2020-08-07) ;
    Alberto Brunete
    ;
    Miguel Hernando
    ;
    Javier Rueda
    ;
    Enrique Navarro Cabello
    Several studies have examined the accuracy of the Kinect V2 sensor during gait analysis. Usually the data retrieved by the Kinect V2 sensor are compared with the ground truth of certified systems using a Euclidean comparison. Due to the Kinect V2 sensor latency, the application of a uniform temporal alignment is not adequate to compare the signals. On that basis, the purpose of this study was to explore the abilities of the dynamic time warping (DTW) algorithm to compensate for sensor latency (3 samples or 90 ms) and develop a proper accuracy estimation. During the experimental stage, six iterations were performed using the a dual Kinect V2 system. The walking tests were developed at a self-selected speed. The sensor accuracy for Euclidean matching was consistent with that reported in previous studies. After latency compensation, the sensor accuracy demonstrated considerably lower error rates for all joints. This demonstrated that the accuracy was underestimated due to the use of inappropriate comparison techniques. On the contrary, DTW is a potential method that compensates for the sensor latency, and works sufficiently in comparison with certified systems.
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    Editorial: Assistive and service robots for health and home applications (RH3 - Robot Helpers in Health and Home)
    (Frontiers Media SA, 2024-10-29)
    Paloma de la Puente
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    Markus Vincze
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    ;
    Daniel Galan
    In Choi et al. (2024), the main trends in assistive technologies for healthcare and home environments were analyzed. In that study, assistive technologies were classified into three major groups: physical aid or mobility devices, sensor and monitoring systems, and assistive robots. In an aging society, with people living longer and a lack of medical personnel, there is undoubtedly a growing interest in the development and commercialization of robotic systems that are able to provide support at healthcare facilities and home environments (Bajones et al., 2018; Keroglou et al., 2023; Silvera-Tawil, 2024). At healthcare facilities, robots improve the diagnosis and treatment of many different diseases (mental and physical), and they help professional staff be more efficient, with more time for patients. At home, they assist to prevent accidents, and they have the potential to perform different household tasks, keep the users active with cognitive and physical activities, and raise alarms if needed. Assistive robots designed for therapeutic purposes have proven useful in reducing agitation of elderly people and stress of caregivers (Kolstad et al., 2020).
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    Multivariate System Identification of Differential Drive Robot: Comparison Between State-Space and LSTM-Based Models
    Modeling mobile robots is crucial to odometry estimation, control design, and navigation. Classical state-space models (SSMs) have traditionally been used for system identification, while recent advances in deep learning, such as Long Short-Term Memory (LSTM) networks, capture complex nonlinear dependencies. However, few direct comparisons exist between these paradigms. This paper compares two multivariate modeling approaches for a differential drive robot: a classical SSM and an LSTM-based recurrent neural network. Both models predict the robot’s linear (v) and angular (ω) velocities using experimental data from a five-minute navigation sequence. Performance is evaluated in terms of prediction accuracy, odometry estimation, and computational efficiency, with ground-truth odometry obtained via a SLAM-based method in ROS2. Each model was tuned for fair comparison: order selection for the SSM and hyperparameter search for the LSTM. Results show that the best SSM is a second-order model, while the LSTM used seven layers, 30 neurons, and 20-sample sliding windows. The LSTM achieved a FIT of 93.10% for v and 90.95% for ω, with an odometry RMSE of 1.09 m and 0.23 rad, whereas the SSM outperformed it with FIT values of 94.70% and 91.71% and lower RMSE (0.85 m, 0.17 rad). The SSM was also more resource-efficient (0.00257 ms and 1.03 bytes per step) compared to the LSTM (0.0342 ms and 20.49 bytes). The results suggest that SSMs remain a strong option for accurate odometry with low computational demand while encouraging the exploration of hybrid models to improve robustness in complex environments. At the same time, LSTM models demonstrated flexibility through hyperparameter tuning, highlighting their potential for further accuracy improvements with refined configurations.
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    Continuous Speech Recognition and Identification of the Speaker System
    (Springer International Publishing, 2018) ;
    Danilo Martínez
    ;
    José Paladines
    ;
    Andrea Sarmiento
    Currently speech recognition and speaker identification based on a biometric parameter such as voice have been treated as two different worlds and in the market there are no integrated applications of these systems. The design of a system could mean a great contribution to the development of personalized commands, in the area of home automation and robotics, thanks to the availability of the message and the identification of the speaker. Therefore, the development of an integrated biometric voice system is proposed, based on a single voice sample for the identification of the speaker and the message. We use GOOGLE SPEECH API, as a voice text translation tool, and Mel Frequency Cepstral Coefficients or MFCCs extracted from voice signal to identify speakers voice. Functional tests were carried with 50 randomly users, in the end of the study results show 96.4% efficiency in identification, demonstrating efficiency using MFCCs in speaker’s automatic recognition and verifying the use of GOOGLE SPEECH API as a fast, accurate and robust translation tool.
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    Organic zinc sources in broiler production at high altitude under on-top supplementation or total or partial replacement: 1. Effects on performance and zinc excretion
    (Elsevier BV, 2024-12)
    R. Riboty
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    J.L. Gaibor
    ;
    C.L. Ponce-de-Leon
    ;
    Feeding broilers with organic chemical sources of Zn has recently been recommended to improve performance, immune system, carcass yield, and reduce environmental contamination. However, its use under proposed supplementation strategies (i.e., total replacement, partial replacement, on-top) needs further investigation. This study assessed the effect of total replacement, partial replacement, and on-top supplementation strategies to feed organic Zn sources and the effect of two organic chemical forms on performance and Zn excretion in broilers at high altitudes. Twenty-two male Cobb 500-day-old chicks were placed in each of 54 floor pens and raised for up to 42 days under a three-phase feeding program and following the Ecuadorian highland production system. Pens were assigned to one of nine experimental treatments consisting of a basal diet supplemented with 0, 33, and 100 ppm of Zn from ZnSO4 and added or not 40 ppm Zn from Zn proteinate or Zn amino acid complex. A Completely Randomized Block Design was considered, being the block the replication. The Zn concentration of the basal diet was determined. Feed intake, BW, BW gain, feed conversion ratio, and European Production Efficiency Factor were assessed at 21 and 42 days of age, and the Zn excretion was estimated accordingly. Each supplementation strategy was compared with the standard practice (100 ppm Zn as ZnSO4) using contrasts and mixed models, and the interaction with the chemical form was assessed considering the P-values of the ANOVA and the multiple comparisons between the corresponding treatments. The effects of the organic Zn forms and their interactions with the dietary Zn level were assessed considering the responses were linear functions of the organic Zn source, the feed intake, the Zn intake, the Zn supplementation level, and the block, as corresponding. None of the strategies to supplement a Zn organic source, or the organic sources themselves, showed overall detectable effects on performance. However, interactions were observed between the supplementation strategy and the organic Zn source and between the organic source and the dietary Zn levels or the Zn intake. Under the on-top supplementation strategy, the Zn organic sources showed different feed conversion ratios at 21 days. In addition, totally or partially replacing the ZnSO4 with a Zn organic form reduced the Zn excretion. In conclusion, although no overall effect of the supplementation strategies was detected, the assessed organic Zn forms showed different effects on the feed conversion ratio at 21 days.
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    Organic zinc sources in broiler production at high altitude under on-top supplementation or total or partial replacement: 2. Effects on tibia and blood characteristics
    (Elsevier BV, 2024-12)
    R. Riboty
    ;
    J.L. Gaibor
    ;
    C.L. Ponce-de-Leon
    ;
    The use of organic Zn sources has been claimed to reduce the environmental impact of poultry production and improve broiler performance and the quality of products. This study investigated the effects of three organic Zn supplementation strategies (i.e., TRE, total replacement; PRE, partial replacement; OTS, on-top supplementation) on tibia and blood biochemistry characteristics of broilers at high altitudes. Male Cobb 500 chicks were distributed in 54 floor pens (22 birds each) and assigned to nine experimental treatments. Birds were fed mash diets under three feeding phases until 42 days and following the standard Ecuadorian high-altitude production standard practices. The treatments were a basal diet supplemented with three inclusion rates of ZnSO4 and the same diets including or not Zn from one of two organic Zn sources (i.e., ZPR, Zn proteinate; ZAC, Zn amino acid complex). Basal diets were analyzed for Zn concentration. Tibia ash and Zn concentrations and serum biochemistry variables were determined at 21 and 42 days. The strategies to supplement organic Zn were compared with the reference treatment containing 100 ppm Zn as ZnSO4 (the standard practice; STD) using mixed models, being the block (i.e., the replication) as a random factor. The interaction of the strategy with the organic Zn source was assessed with the ANOVA and multiple comparisons. The organic Zn sources were compared considering the feed intake a random factor, and their interaction with the dietary Zn level was assessed using multiple regression. No overall effect of the Zn supplementation strategy was observed other than the reduced Zn concentration at 21 days in TRE birds. At 21 days, PRE and TRE increased the serum protein and phosphorus concentrations, respectively. At that age, TRE also increased insulin concentration, but only in the ZAC-fed birds. However, TRE produced the opposite effect on serum protein at 42 days. At the same age, ZAC-fed birds showed lower serum phosphorus concentration than ZPR-fed ones regardless of the dietary Zn supplementation level or the Zn intake. Also, ZAC under TRE produced no effect on tibia Zn concentration compared to STD, but ZPR increased it. The ZPR increased the tibia Zn concentration when fed under PRE or TRE, but not under OTS. In conclusion, the results showed no adverse effect of PRE or TRE strategies on tibia characteristics. The data indicate likely different effects of PRE and TRE on protein metabolism and a possible negative interaction of the organic Zn with a high Zn content as ZnSO4.
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    Comparison of Two System Identification Approaches for a Four-Wheel Differential Robot Based on Velocity Command Execution
    (MDPI AG, 2025-06-05) ;
    Moisés Filiberto Mora Murillo
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    Marco Alejandro Hinojosa
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    Santiago Bustamante Sanchez
    ;
    Javier Oswaldo Obregón Gutiérrez
    Precise modeling of differential drive robots is crucial for effective control and trajectory planning in autonomous systems. A comparative analysis of two modeling approaches for a four-wheel differential drive robot is presented in this paper. The first approach, named Motor-Based Model (MBM), identifies four transfer functions, one for each motor, while the second approach, named Simplified Model (SM), uses only two transfer functions, one for linear velocity and another for angular velocity. Both models were validated by comparing their predicted trajectories against real odometry data obtained from a SLAM system implemented on a differential-drive robot. This provided a practical assessment of each model’s accuracy and underscored the importance of model selection in control design and navigation tasks. The results showed that the Motor-Based Model (MBM) consistently outperformed the Simplified Model (SM) in terms of odometry accuracy, both in position and orientation. Across all trajectories, the average RMSE for position using MBM was 0.309 m, while the SM recorded a higher average RMSE of 0.414 m. Similarly, the maximum position error averaged 0.522 m for MBM and 0.710 m for SM, confirming that MBM is more accurate and consistent in position tracking. Regarding the results of orientation estimation, when averaged across all experiments, the MBM maintained a lower angular RMSE of 0.170 rad in contrast to SM, which achieves an RMSE of 0.239 rad. The maximum angular error was also higher for the MBM at 0.316 rad, compared to 0.447 rad for the SM. Moreover, the computational performance evaluation indicated that the SM consistently outperformed MBM, achieving a 30% reduction in simulation time and substantially lower memory usage. These results demonstrate the relationship between model complexity and accuracy and suggest that the motor-specific model is more appropriate for applications requiring precise mapping or localization, such as SLAM, while the simplified model may be suitable for simpler use cases with lower computational requirements, such as embedded systems with limited resources. This paper provides a practical evaluation of the accuracy and computational performance of two modeling approaches, highlighting the implications of model selection for the design of navigation tasks.