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Partially automated robotic systems, such as camera holders, represent a pivotal step towards enhancing efficiency and precision in surgical procedures. Therefore, this paper introduces an approach for real-time tool localization in laparoscopy surgery using convolutional neural networks. The proposed model, based on two Hourglass modules in series, can localize up to two surgical tools simultaneously. This study utilized three datasets: the ITAP dataset, alongside two publicly available datasets, namely Atlas Dione and EndoVis Challenge. Three variations of the Hourglass-based models were proposed, with the best model achieving high accuracy (92.86%) and frame rates (27.64 FPS), suitable for integration into robotic systems. An evaluation on an independent test set yielded slightly lower accuracy, indicating limited generalizability. The model was further analyzed using the Grad-CAM technique to gain insights into its functionality. Overall, this work presents a promising solution for automating aspects of laparoscopic surgery, potentially enhancing surgical efficiency by reducing the need for manual endoscope manipulation.
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Laparoscopía , Redes Neurales de la Computación , Laparoscopía/métodos , Humanos , Procedimientos Quirúrgicos Robotizados/métodos , AlgoritmosRESUMEN
BACKGROUND AND AIMS: Cyclooxygenase-2 (COX-2) is involved in different liver diseases, but little is known about the significance of COX-2 in cholestatic injury. This study was designed to elucidate the role of COX-2 expression in hepatocytes during the pathogenesis of obstructive cholestasis. METHODS: We used genetically modified mice constitutively expressing human COX-2 in hepatocytes. Transgenic mice (hCOX-2-Tg) and their wild-type (Wt) littermates were either subjected to a mid-abdominal laparotomy or common bile duct ligation (BDL) for 2 or 5 days. Then, we explored the mechanisms underlying the role of COX-2 and its derived prostaglandins in liver function, and the synthesis and excretion of bile acids (BA) in response to cholestatic liver injury. RESULTS: After BDL, hCOX-2-Tg mice showed lower grades of hepatic necrosis and inflammation than Wt mice, in part by a reduced hepatic neutrophil recruitment associated with lower mRNA levels of pro-inflammatory cytokines. Furthermore, hCOX-2-Tg mice displayed a differential metabolic pattern of BA synthesis that led to an improved clearance after BDL-induced accumulation. In addition, an enhanced response to the BDL-induced oxidative stress and hepatic apoptosis was observed. In vitro experiments using hepatic cells that stably express hCOX-2 confirmed the cytoprotective role of prostaglandin E2 against BA toxicity. CONCLUSIONS: Taken together, our data indicate that constitutive expression of COX-2 in hepatocytes ameliorates cholestatic liver injury in mice by reducing inflammation and cell damage and by modulating BA metabolism, pointing to a role for COX-2 as a defensive response against cholestasis-derived BA accumulation and injury.
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Livestock monitoring is a task traditionally carried out through direct observation by experienced caretakers. By analyzing its behavior, it is possible to predict to a certain degree events that require human action, such as calving. However, this continuous monitoring is in many cases not feasible. In this work, we propose, develop and evaluate the accuracy of intelligent algorithms that operate on data obtained by low-cost sensors to determine the state of the animal in the terms used by the caregivers (grazing, ruminating, walking, etc.). The best results have been obtained using aggregations and averages of the time series with support vector classifiers and tree-based ensembles, reaching accuracies of 57% for the general behavior problem (4 classes) and 85% for the standing behavior problem (2 classes). This is a preliminary step to the realization of event-specific predictions.
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Algoritmos , Aprendizaje Automático , Animales , Bovinos , Conducta Animal/fisiología , Máquina de Vectores de Soporte , Humanos , Monitoreo Fisiológico/métodos , Monitoreo Fisiológico/instrumentaciónRESUMEN
Background: Prolonged hospitalization in severe COVID-19 cases can lead to substantial muscle loss and functional deterioration. While rehabilitation is essential, conventional approaches face capacity challenges. Therefore, evaluating the effectiveness of robotic-assisted rehabilitation for patients with post-COVID-19 fatigue syndrome to enhance both motor function and overall recovery holds paramount significance. Our objective is to assess the effectiveness of rehabilitation in post-COVID-19 patients with upper extremity impairment through the utilization of a hand exoskeleton-based robotic system. Methods: A total of 13 participants experiencing acute or limited functional or strength impairment in an upper extremity due to COVID-19 were enrolled in the study. A structured intervention consisted of 45 min therapy sessions, conducted four times per week over a six-week period, utilizing a hand exoskeleton. The research employed standardized health assessments, motion analysis, and semi-structured interviews for pre-intervention and follow-up evaluations. Paired sample t-tests were employed to statistically analyze the outcomes. Results: The outcomes showed a reduction in overall dependence levels across participants, positive changes in various quality of life-related measurements, and an average increase of 60.4 ± 25.7% and 28.7 ± 11.2% for passive and active flexion, respectively. Conclusions: Our data suggest that hand exoskeleton-based robotic systems hold promise to optimize the rehabilitation outcomes following severe COVID-19. Trial registration: ID NCT06137716 at ClinicalTrials.gov.
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Introduction: The RobHand (Robot for Hand Rehabilitation) is a robotic neuromotor rehabilitation exoskeleton that assists in performing flexion and extension movements of the fingers. The present case study assesses changes in manual function and hand muscle strength of four selected stroke patients after completion of an established training program. In addition, safety and user satisfaction are also evaluated. Methods: The training program consisted of 16 sessions; two 60-minute training sessions per week for eight consecutive weeks. During each session, patients moved through six consecutive rehabilitation stages using the RobHand. Manual function assessments were applied before and after the training program and safety tests were carried out after each session. A user evaluation questionnaire was filled out after each patient completed the program. Results: The safety test showed the absence of significant adverse events, such as skin lesions or fatigue. An average score of 4 out of 5 was obtained on the Quebec User Evaluation of Satisfaction with Assistive Technology 2.0 Scale. Users were very satisfied with the weight, comfort, and quality of professional services. A Kruskal-Wallis test revealed that there were not statistically significant changes in the manual function tests between the beginning and the end of the training program. Discussion: It can be concluded that the RobHand is a safe rehabilitation technology and users were satisfied with the system. No statistically significant differences in manual function were found. This could be due to the high influence of the stroke stage on motor recovery since the study was performed with chronic patients. Hence, future studies should evaluate the rehabilitation effectiveness of the repetitive use of the RobHand exoskeleton on subacute patients. Clinical Trial Registration: https://clinicaltrials.gov/ct2/show/NCT05598892?id=NCT05598892&draw=2&rank=1, identifier NCT05598892.
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The effectiveness of EMG biofeedback with neurorehabilitation robotic platforms has not been previously addressed. The present work evaluates the influence of an EMG-based visual biofeedback on the user performance when performing EMG-driven bilateral exercises with a robotic hand exoskeleton. Eighteen healthy subjects were asked to perform 1-min randomly generated sequences of hand gestures (rest, open and close) in four different conditions resulting from the combination of using or not (1) EMG-based visual biofeedback and (2) kinesthetic feedback from the exoskeleton movement. The user performance in each test was measured by computing similarity between the target gestures and the recognized user gestures using the L2 distance. Statistically significant differences in the subject performance were found in the type of provided feedback (p-value 0.0124). Pairwise comparisons showed that the L2 distance was statistically significantly lower when only EMG-based visual feedback was present (2.89 ± 0.71) than with the presence of the kinesthetic feedback alone (3.43 ± 0.75, p-value = 0.0412) or the combination of both (3.39 ± 0.70, p-value = 0.0497). Hence, EMG-based visual feedback enables subjects to increase their control over the movement of the robotic platform by assessing their muscle activation in real time. This type of feedback could benefit patients in learning more quickly how to activate robot functions, increasing their motivation towards rehabilitation.
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Dispositivo Exoesqueleto , Rehabilitación Neurológica , Humanos , Biorretroalimentación Psicológica , Retroalimentación Sensorial , Terapia por EjercicioRESUMEN
Cerebrovascular accidents have physical, cognitive and emotional effects. During rehabilitation, the main focus is placed on motor recovery, yet the patient's emotional state should also be considered. For this reason, validating robotic rehabilitation systems should not only focus on their effectiveness related to the physical recovery but also on the patient's emotional response. A case series study has been conducted with five stroke patients to assess their emotional response towards therapies using RobHand, a robotic hand rehabilitation platform. Emotional state was evaluated in three dimensions (arousal, valence and dominance) using a computer-based Self-Assessment Manikin (SAM) test. It was verified that the emotions induced by the RobHand platform were successfully distributed in the three-dimensional emotional space. The increase in dominance and the decrease in arousal during sessions reflects that patients had become familiar with the rehabilitation platform, resulting in an increased feeling of control and finding the platform less attractive. The results also reflect that patients found a therapy based on a virtual environment with a realistic scenario more pleasant and attractive.
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Medical instruments detection in laparoscopic video has been carried out to increase the autonomy of surgical robots, evaluate skills or index recordings. However, it has not been extended to surgical gauzes. Gauzes can provide valuable information to numerous tasks in the operating room, but the lack of an annotated dataset has hampered its research. In this article, we present a segmentation dataset with 4003 hand-labelled frames from laparoscopic video. To prove the dataset potential, we analyzed several baselines: detection using YOLOv3, coarse segmentation, and segmentation with a U-Net. Our results show that YOLOv3 can be executed in real time but provides a modest recall. Coarse segmentation presents satisfactory results but lacks inference speed. Finally, the U-Net baseline achieves a good speed-quality compromise running above 30 FPS while obtaining an IoU of 0.85. The accuracy reached by U-Net and its execution speed demonstrate that precise and real-time gauze segmentation can be achieved, training convolutional neural networks on the proposed dataset.
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Fenómenos Biológicos , Laparoscopía , Mano , Procesamiento de Imagen Asistido por Computador/métodos , Procedimientos Quirúrgicos Mínimamente Invasivos , Redes Neurales de la ComputaciónRESUMEN
This study explores the effects of the shift to emergency remote teaching (ERT) on teachers' levels of well-being, emotions, and motivation. A total of 936 Spanish teachers participated in this nationwide survey from all educational levels, thus allowing comparison among levels, which is a novelty and strength of our study. Four aspects were explored: (1) instructional adaptation to ERT; (2) well-being changes and the main challenges in this regard; (3) changes in emotions; and (4) changes in motivation and the main factors. Importantly, we explored a number of teacher characteristics (e.g., gender, age) for the three last aspects. Our results show that teachers felt the impact of ERT on their well-being, emotions, and motivation. Additionally, female teachers, teachers with students of low socioeconomic status (SES), in public schools, and primary and secondary teachers were the most affected groups. This indicates that the impact of ERT differed and some populations of teachers are more at risk of suffering burnout because of ERT.
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In this study, new low-cost neck-mounted sensorized wearable device is presented to help farmers detect the onset of calving in extensive livestock farming by continuously monitoring cow data. The device incorporates three sensors: an inertial measurement unit (IMU), a global navigation satellite system (GNSS) receiver, and a thermometer. The hypothesis of this study was that onset calving is detectable through the analyses of the number of transitions between lying and standing of the animal (lying bouts). A new algorithm was developed to detect calving, analysing the frequency and duration of lying and standing postures. An important novelty is that the proposed algorithm has been designed with the aim of being executed in the embedded microcontroller housed in the cow's collar and, therefore, it requires minimal computational resources while allowing for real time data processing. In this preliminary study, six cows were monitored during different stages of gestation (before, during, and after calving), both with the sensorized wearable device and by human observers. It was carried out on an extensive livestock farm in Salamanca (Spain), during the period from August 2020 to July 2021. The preliminary results obtained indicate that lying-standing animal states and transitions may be useful to predict calving. Further research, with data obtained in future calving of cows, is required to refine the algorithm.
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Parto , Dispositivos Electrónicos Vestibles , Animales , Conducta Animal , Bovinos , Granjas , Femenino , Humanos , Ganado , Proyectos Piloto , EmbarazoRESUMEN
Depending on their use, electrodes must have a certain size and design so as not to compromise their electrical characteristics. It is fundamental to be aware of all dependences on external factors that vary the electrochemical characteristics of the electrodes. When using implantable electrodes, the maximum charge injection capacity (CIC) is the total amount of charge that can be injected into the tissue in a reversible way. It is fundamental to know the relations between the characteristics of the microelectrode itself and its maximum CIC in order to develop microelectrodes that will be used in biomedical applications. CIC is a very complex measure that depends on many factors: material, size (geometric and effectiveness area), and shape of the implantable microelectrode and long-term behavior, composition, and temperature of the electrolyte. In this paper, our previously proposed measurement setup and automated calculation method are used to characterize a graphene microelectrode and to measure the behavior of a set of microelectrodes that have been developed in the Fraunhofer Institute for Biomedical Engineering (IBMT) labs. We provide an electrochemical evaluation of CIC for these microelectrodes by examining the role of the following variables: pulse width of the stimulation signal, electrode geometry and size, roughness factor, solution, and long-term behavior. We hope the results presented in this paper will be useful for future studies and for the manufacture of advanced implantable microelectrodes.
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The design of safe stimulation protocols for functional electrostimulation requires knowledge of the "maximum reversible charge injection capacity" of the implantable microelectrodes. One of the main difficulties encountered in characterizing such microelectrodes is the calculation of the access voltage Va. This paper proposes a method to calculate Va that does not require prior knowledge of the overpotential terms and of the electrolyte (or excitable tissue) resistance, which is an advantage for in vivo electrochemical characterization of microelectrodes. To validate this method, we compare the calculated results with those obtained from conventional methods for characterizing three flexible platinum microelectrodes by cyclic voltammetry and voltage transient measurements. This paper presents the experimental setup, the required instrumentation, and the signal processing.
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Electrodos Implantados , Microelectrodos , HumanosRESUMEN
IMPORTANCE: Surgical treatment can bring seizure remission in people with focal epilepsy but requires careful selection of candidates. OBJECTIVES: To determine which preoperative factors are associated with postoperative seizure outcome. DESIGN: We audited seizure outcome of 693 adults who had resective epilepsy surgery between 1990 and 2010 and used survival analysis to detect preoperatively identifiable risk factors of poor seizure outcome. RESULTS: Seven factors were significantly associated with increased probability of recurrence of seizures with impaired awareness postsurgery: MRI findings (eg, HR adjusted for other variables in the model 2.5; 95% CI 1.6 to 3.8 for normal MRI compared with hippocampal sclerosis), a history of secondarily generalised convulsive seizures (2.3; 95% CI 1.7 to 3.0 for these seizures in the previous year vs never), psychiatric history (1.3; 95% CI 1.1 to 1.7), learning disability (1.8; 95% CI 1.2 to 2.6) and extratemporal (vs temporal) surgery (1.4; 95% CI 1.02, 2.04). People with an older onset of epilepsy had a higher probability of seizure recurrence (1.01; 95% CI 1.00, 1.02) as did those who had used more antiepileptic drugs (1.05; 95% CI 1.01 to 1.09). Combinations of variables associated with seizure recurrence gave overall low probabilities of 5-year seizure freedom (eg, a normal MRI and convulsive seizures in the previous year has a probability of seizure freedom at 5 years of approximately 0.19). CONCLUSIONS AND RELEVANCE: Readily identified clinical features and investigations are associated with reduced probability of good outcome and need consideration when planning presurgical evaluation.
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Epilepsias Parciales/cirugía , Resultado del Tratamiento , Adulto , Trastornos de la Conciencia/diagnóstico , Femenino , Estudios de Seguimiento , Humanos , Masculino , Persona de Mediana Edad , Complicaciones Posoperatorias/diagnóstico , Cuidados Preoperatorios , Recurrencia , Factores de Riesgo , Análisis de SupervivenciaRESUMEN
Animal testing plays a vital role in biomedical research. Stress reduction is important for improving research results and increasing the welfare and the quality of life of laboratory animals. To estimate stress we believe it is of great importance to develop non-invasive techniques for monitoring physiological signals during the transport of laboratory animals, thereby allowing the gathering of information on the transport conditions, and, eventually, the improvement of these conditions. Here, we study the suitability of commercially available electric potential integrated circuit (EPIC) sensors, using both contact and contactless techniques, for monitoring the heart rate and breathing rate of non-restrained, non-sedated laboratory mice. The design has been tested under different scenarios with the aim of checking the plausibility of performing contactless capture of mouse heart activity (ideally with an electrocardiogram). First experimental results are shown.
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Anestesia , Capacidad Eléctrica , Frecuencia Cardíaca/fisiología , Monitoreo Fisiológico/métodos , Respiración , Animales , Animales de Laboratorio , Presión Sanguínea/fisiología , Ratones Endogámicos C57BL , Procesamiento de Señales Asistido por Computador , Factores de TiempoRESUMEN
This paper proposes a multiagent system (MAS) that uses smart wearable devices and mobile technology for the care of patients in a geriatric home care facility. The system is based on an advanced ZigBee wireless sensor network (WSN) and includes location and identification microchips installed in patient clothing and caregiver uniforms. The use of radio-frequency identification and near-field communication technologies allows remote monitoring of patients, and makes it possible for them to receive treatment according to preventive medical protocol. The proposed MAS manage the infrastructure of services within the environment both efficiently and securely by reasoning, task-planning, and synchronizing the data obtained from the sensors. Additionally, this paper presents the design and implementation of the reasoning agent in the MAS. A system prototype was installed in a real environment and the results obtained are presented in this paper.