A low-cost and open-hardware portable 3-electrode sleep monitoring device.

To continue sleep research activities during the lockdown resulting from the COVID-19 pandemic, experiments that were previously conducted in laboratories were shifted to the homes of volunteers. Furthermore, for extensive data collection, it is necessary to use a large number of portable devices. Hence, to achieve these objectives, we developed a low-cost and open-source portable monitor (PM) device capable of acquiring electroencephalographic (EEG) signals using the popular ESP32 microcontroller. The device operates based on instrumentation amplifiers. It also has a connectivity microcontroller with Wi-Fi and Bluetooth that can be used to stream EEG signals. This portable single-channel 3-electrode EEG device allowed us to record short naps and score different sleep stages, such as wakefulness, non rapid eye movement sleep (NREM), stage 1 (S1), stage 2 (S2), stage 3 (S3) and stage 4 (S4). We validated the device by comparing the obtained signals to those generated by a research-grade counterpart. The results showed a high level of accurate similarity between both devices, demonstrating the feasibility of using this approach for extensive and low-cost data collection of EEG sleep recordings.

SHA-256 Hardware Proposal for IoT Devices in the Blockchain Context.

This work proposes an implementation of the SHA-256, the most common blockchain hash algorithm, on a field-programmable gate array (FPGA) to improve processing capacity and power saving in Internet of Things (IoT) devices to solve security and privacy issues. This implementation presents a different approach than other papers in the literature, using clustered cores executing the SHA-256 algorithm in parallel. Details about the proposed architecture and an analysis of the resources used by the FPGA are presented. The implementation achieved a throughput of approximately 1.4 Gbps for 16 cores on a single FPGA. Furthermore, it saved dynamic power, using almost 1000 times less compared to previous works in the literature, making this proposal suitable for practical problems for IoT devices in blockchain environments. The target FPGA used was the Xilinx Virtex 6 xc6vlx240t-1ff1156.

A Collaborative Platform for Advancing Automatic Interpretation in ECG Signals.

Numerous papers report the efficiency of the automatic interpretation capabilities of commercial algorithms. Unfortunately, these algorithms are proprietary, and academia has no means of directly contributing to these results. In fact, nothing at the same stage of development exists in academia. Despite the extensive research in ECG signal processing, from signal conditioning to expert systems, a cohesive single application for clinical use is not ready yet. This is due to a serious lack of coordination in the academic efforts, which involve not only algorithms for signal processing, but also the signal acquisition equipment itself. For instance, the different sampling rates and the different noise levels frequently found in the available signal databases can cause severe incompatibility problems when the integration of different algorithms is desired. Therefore, this work aims to solve this incompatibility problem by providing the academic community with a diagnostic-grade electrocardiograph. The intention is to create a new standardized ECG signals database in order to address the automatic interpretation problem and create an electrocardiography system that can fully assist clinical practitioners, as the proprietary systems do. Achieving this objective is expected through an open and coordinated collaboration platform for which a webpage has already been created.

A High-Performance and Cost-Effective Field Programmable Gate Array-Based Motor Drive Emulator.

This work presents a hardware-based digital emulator capable of digitally driving a permanent magnet synchronous machine electronic setup. The aim of this work is to present a high-performance, cost-effective, and portable complementary solution when new paradigms of electronic drive design are generated, such as machine early failure detection, fault-tolerant drive, and high-performance control strategy implementations. In order to achieve the high performance required by the digital emulator, the electronic drive models (permanent-magnet synchronous machine, voltage-source inverter, motor-control strategy) are digitally described in Verilog hardware description language and implemented on a field programmable gate array (FPGA) digital platform using two approaches: parallel and sequential methods. The results obtained show the effectiveness of the digital emulator design, and the resources used by the solution presented can be implemented on a low-cost digital platform that reveals a cost-effective operation of the solution presented.

Arduino based intra-cerebral microinjector device for neuroscience research.

Stereotaxic surgery is a less invasive form of surgery that uses a three-dimensional coordinate system to place instruments at a specific location in the brain. Through this type of surgery, one can place needles among other tools within the structures of the brain. Therefore, injections can be given in order to deliver substances that cannot cross the blood-brain barrier. The two most important parameters of the microinjection to control are volume and speed. The volume should not be so large that it displaces the brain tissue and tears it. The injection speed must also be slow so that the liquid that comes out of the syringe can diffuse into the tissue without displacing it and damaging it. Thus, the objectives of the present work are: 1) To develop not a 3D printed prototype but an end-user device. 2) The device must be for animal research only. 3) It must have the same precision in volume and speed as commercial devices. 4) It must be adjustable for microsyringes from 0.5 µl to 1 ml. 5) It must be possible to place it directly on the stereotaxic surgery apparatus and to use it separately. 6) The price must be substantially lower than that of the commercial devices.

Imaging features of the postoperative spine: a guide to basic understanding of spine surgical procedures.

Spinal surgical procedures are becoming more common over the years, and imaging studies can be requested in the postoperative setting, such as a baseline study when implants are used, or when there is a new postoperative issue reported by the patient or even as routine surveillance. Therefore, it helps the surgeon in the appropriate management of cases. In this context, there is increasing importance of the radiologist in the adequate interpretation of postoperative images, as well as in the choice of the most appropriate modality for each case, especially among radiographs, computed tomography, magnetic resonance imaging and nuclear medicine. It is essential to be familiar with the main types of surgical techniques and imaging characteristics of each one, including the type and correct positioning of hardware involved, to differentiate normal and abnormal postoperative appearances. The purpose of this pictorial essay is to illustrate and discuss the more frequently used spine surgical interventions and their imaging characteristics, with an emphasis on classical decompression and fusion/stabilization procedures. KEY POINTS: Plain radiographs remain the main modality for baseline, dynamic evaluation, and follow-ups. CT is the method of choice for assessing bone fusion, hardware integrity and loosening. MRI should be used to evaluate bone marrow and soft tissue complications. Radiologists should be familiar with most performed spinal procedures in order to differentiate normal and abnormal. CRITICAL RELEVANCE STATEMENT: This article discusses the main surgical procedures involved in the spine, which can be didactically divided into decompression, stabilization-fusion, and miscellaneous, as well as the role of diagnostic imaging methods and their main findings in this context.

Low-Cost Data Acquisition System for Automotive Electronic Control Units.

The vehicle testing-validation phase is a crucial and demanding task in the automotive development process for vehicle manufacturers. It ensures the correct operation, safety, and efficiency of the vehicle. To meet this demand, some commercial solutions are available on the market, but they are usually expensive, have few connectivity options, and are PC-dependent. This paper presents an IoT-based intelligent low-cost system for vehicle data acquisition during on-road tests as an alternative solution. The system integrates low-cost acquisition hardware with an IoT server, collecting and transmitting data in near real-time, while artificial intelligence (AI) algorithms process the information and report errors and/or failures to the manufacturing engineers. The proposed solution was compared with other commercial systems in terms of features, performance, and cost. The results indicate that the proposed system delivers similar performance in terms of the data acquisition rate, but at a lower cost (up to 13 times cheaper) and with more advanced features, such as near real-time intelligent data processing and reduced time to find and correct errors or failures in the vehicle.

RaspyControl Lab: A fully open-source and real-time remote laboratory for education in automatic control systems using Raspberry Pi and Python.

Currently, remote laboratories have gained relevance in engineering education as tools to support active learning, experimentation, and motivation of students. Nonetheless, the costs and issues regarding their implementation and deployment limit the access of the students and educators to their advantages and features such as technical and educational. In this line, this study describes a fully open-source remote laboratory in hardware and software for education in automatic control systems employing Raspberry Pi and Python language with an approximate cost of USD 461. Even, by changing some components, the cost can be reduced to USD 420 or less. To illustrate the functionalities of the laboratory, we proposed a low-cost tank control system with its respective instrumentation, signal conditioning, identification, and control, which are exposed in this document. However, other experiments can be easily scalable and adaptable to the remote laboratory. Concerning the interface of the laboratory, we designed a complete user-friendly web interface with real-time video for the users to perform the different activities in automatic control such as identification or controller implementation through the programming language Python. The instructions to build and replicate the hardware and software are indicated in the open repositories provided for the project as well as in this paper. Our intention with this project is to offer a complete low-cost and open-source remote laboratory that can be adapted and used for the students, educators, and stakeholders to learn, experiment, and teach in the field of automatic control systems.

Strategies to obtain a better quality of environmental data gathered by low cost systems.

Monitoring systems are ubiquitous in many environmental science fields due to the technological advances in the last decades, which contributed to the migration from conventional to automated observing networks. However, the cost of acquisition and operation of sensor networks is still a limiting factor for their wide use. Under this scenario, low-cost and affordable open-source sensors and systems emerge as an alternative to research-grade instruments. To fulfill the quality requirements defined by international organizations, sensor calibration has to be performed and shall be considered as a basic requirement. Best monitoring practices including established quality control procedures should be implemented for gathering environmental data. With a focus on data gathering, this paper reviews basic concepts on open source technologies, calibration methods, quality control procedures, applications and trends, and possibilities for improving the hardware of low-cost and affordable systems.

Practical aspects of functional mri in clinical examinations / Aspectos práticos de rm funcional em exames clínicos / Aspectos prácticos de la rm funcional en los exámenes clínicos

The eloquent cerebral cortices are involved in movement, sensation, speech, vision, and higher cortical functions. Functional magnetic resonance imaging (fMRI) allows the evaluation of brain function, aiding in neurosurgical planning by mapping eloquent cortical areas. Considering the high cost of the hardware involved, the purpose of this work is to present a more affordable, in-house alternative for these studies that can provide adequate results in a clinical setting. We also present some practical information on how to perform these exams. We describe an affordable in-house hardware solution used by an imaging center, and examples of fMRI paradigms used to evaluate motor and language tasks. The fMRI studies show robust activations in eloquent areas consistent with the tasks performed on the exam. Images of post-processed studies illustrate clinical cases. The fMRI have well-established applications, mapping eloquent cortical areas in patients with brain lesions. In the case of surgical planning, it allows the surgeon to maximize the resection area while minimizing sequelae. More affordable hardware can reduce the cost of these exams, making them more accessible to the general public.

O córtex cerebral eloquente está envolvido nas atividades motora, sensação, fala, visão e funções corticais superiores. A ressonância magnética funcional (RMf) permite a avaliação da função cerebral, ajudando no planejamento neurocirúrgico através do mapeamento de áreas corticais eloquentes. Considerando o elevado custo do hardware envolvido, o objetivo deste trabalho é apresentar uma alternativa mais acessível para estes estudos, que possa fornecer resultados adequados em um ambiente clínico. Também apresentamos algumas informações práticas sobre a realização destes exames. Descrevemos uma solução de hardware acessível utilizada por um centro de imagens, e exemplos de paradigmas de RMf usados para avaliar tarefas motoras e relacionadas à fala. Os estudos de RMf mostram ativações em áreas eloquentes, consistentes com as tarefas realizadas no exame com imagens de estudos pós-processados ilustrando casos clínicos. A RMf tem aplicações bem estabelecidas, mapeando áreas corticais eloquentes em pacientes com lesões cerebrais. No caso do planejamento cirúrgico, permite que o cirurgião maximize a área de ressecção enquanto minimiza potenciais sequelas. Equipamentos mais acessíveis podem reduzir o custo destes exames, podendo aumentar a disponibilização ao público em geral.

La corteza cerebral elocuente está implicada en las actividades motoras, la sensibilidad, el habla, la visión y las funciones corticales superiores. La resonancia magnética funcional (RMf) permite la evaluación de la función cerebral, ayudando en la planificación neuroquirúrgica mediante el mapeo de las áreas corticales elocuentes. Teniendo en cuenta el elevado coste del hardware implicado, el objetivo de este artículo es presentar una alternativa más asequible para estos estudios que pueda proporcionar resultados adecuados en un entorno clínico. También presentamos información práctica sobre cómo realizar estos exámenes. Describimos una solución de hardware asequible utilizada por un centro de diagnóstico por imagen, y ejemplos de paradigmas de RMf utilizados para evaluar tareas motoras y relacionadas con el habla. Los estudios de RMf muestran activaciones en áreas elocuentes, coherentes con las tareas realizadas en el examen, con imágenes de estudios postprocesados que ilustran casos clínicos. La RMf tiene aplicaciones bien establecidas en el mapeo de áreas corticales elocuentes en pacientes con lesiones cerebrales. En el caso de la planificación quirúrgica, permite al cirujano maximizar el área de resección minimizando las posibles secuelas. Un equipo más asequible puede reducir el coste de estas exploraciones, aumentando potencialmente su disponibilidad para el público en general.

Dehiscencia de herida quirúrgica y exposición material de osteosíntesis. ¿Infección segura? / Surgical wound dehiscence and exposed hardware. Infection foretold?

Resumen: Introducción: la dehiscencia de herida quirúrgica con exposición de material de fijación interna es un grave problema en cirugía ortopédica y un factor importante de infección. Objetivo: descripción del caso inusual de un paciente adulto con dehiscencia de la herida quirúrgica y exposición completa de 20 cm de largo de una placa de cúbito tras seis años de la cirugía, sin signos de infección, consolidación ósea y reepitelización debajo de la placa y adherida al hueso. Caso clínico: hombre de 39 años que sufrió una fractura-luxación de Monteggia, abierta grado II y multifragmentaria. El paciente tenía historia de drogodependencia en tratamiento con metadona. Fue tratado con fijación interna del cúbito mediante una placa de reconstrucción larga. Postoperatoriamente, el paciente dejó de acudir para evaluación. A los seis años de la cirugía presentaba una completa exposición de la placa (20 cm de longitud), sin signos de infección y consolidación con malalineación de la fractura. Tras el retiro de la placa se observó epitelización espontánea adherida al lecho óseo cubital. La cobertura cutánea fue completa a los dos meses. Conclusión: aunque inusual, es posible la consolidación ósea y la ausencia de infección en una fractura abierta con exposición de larga evolución de una placa de antebrazo en el adulto.

Abstract: Introduction: surgical wound dehiscence with exposure of internal fixation material is a serious problem in orthopedic surgery and an important factor for infection. Objective: presentation of an unusual case of an adult patient with surgical wound dehiscence and complete exposure of 20 cm of the ulnar plate after six years of surgery, without infection signs, with bone healing and skin behind the plate. Case presentation: 39-year-old man with an open Gustilo II Monteggia fracture-dislocation multifracture. The patient had a history of drug dependence. He had an open reduction and internal fixation with an ulnar reconstruction plate. The patient did not have any follow-up. After six years of the surgery, there was a complete exposure of the plate (20 cm) without infection and healing of the fracture with misalignment. After removing the plate, we observed spontaneous epithelialization attached to the bone bed. Skin coverage was complete at two months. Conclusion: although unusual, bone consolidation without infection is possible in an open fracture with long-standing exposure to a forearm plate in the adult.

A Low-Power IoT Device for Measuring Water Table Levels and Soil Moisture to Ease Increased Crop Yields.

The simultaneous measurement of soil water content and water table levels is of great agronomic and hydrological interest. Not only does soil moisture represent the water available for plant growth but also water table levels can affect crop productivity. Furthermore, monitoring soil saturation and water table levels is essential for an early warning of extreme rainfall situations. However, the measurement of these parameters employing commercial instruments has certain disadvantages, with a high cost of purchase and maintenance. In addition, the handling of commercial devices makes it difficult to adapt them to the specific requirements of farmers or decision-makers. Open-source IoT hardware platforms are emerging as an attractive alternative to developing flexible and low-cost devices. This paper describes the design of a datalogger device based on open-source hardware platforms to register water table levels and soil moisture data for agronomic applications. The paper begins by describing energy-saving and wireless transmission techniques. Then, it summarizes the linear calibration of the phreatimeter sensor obtained with laboratory and field data. Finally, it shows how non-linear machine-learning techniques improve predictions over classical tools for the moisture sensor (SKU: SEN0193).

PytuTester: RaspberryPi open-source ventilator tester.

PytuTester is an open-source ventilator tester developed to help bio-engineers in the design and verification of new ventilator prototypes. A ventilator tester allows measuring the flow, pressure, volume, and oxygen concentration provided to the patient. During the global pandemic COVID-19, several open-source ventilators prototypes were developed; however, due to high cost and demand testers, they were not available. In this context, a low-cost tester was developed using a Raspberry Pi and medical-grade sensors for the test ventilators prototypes. This paper presents the design files, software interface, and validations tests. Our results indicate that the tester has good accuracy to evaluate the efficacy and performance of new prototypes. When tested on two ventilator designs developed in Paraguay, PytuTester reported flow profiles that were concordant with the industry-standard VT650 Gas Flow Analyzer. PytuTester was then field deployed to test several DIY ventilator designs in low-resource areas.

FPGA-based real-time simulation of mismatched photovoltaic arrays.

This paper proposes an approach to the real time simulation of photovoltaic (PV) arrays that are subjected to mismatching conditions, e.g. partial shadowing. The method, which has been named Model by Zone (MbZ), adopts the best PV model depending on the operating conditions of the cells in the module: it switches among single-diode model (SDM), linear model and constant voltage model. An optimized digital hardware architecture exploiting parallelism of operations over a FPGA system is exploited to effectively implement the proposed model. It reduces the computation time and the use of hardware resources. The good trade-off between accuracy and computation time of the proposed technique has been demonstrated in two cases of study: by evaluating the long-term PV power production of a PV field subjected to dynamic shadowing conditions and by analyzing the model performance in a maximum power point tracking (MPPT) application. In the former case, the proposed approach improves the computation time by 182.5 % with respect to methods that are available in recent literature, with a Relative Error (RE) at the Global Maximum Power Point (GMPP) lower than 0.39 % . In the MPPT application, the proposed technique allows to achieve a MAPE of 0.0319 % and 0.1892 % in the string voltage and power calculation, respectively.

A SHA-256 Hybrid-Redundancy Hardware Architecture for Detecting and Correcting Errors.

In emergent technologies, data integrity is critical for message-passing communications, where security measures and validations must be considered to prevent the entrance of invalid data, detect errors in transmissions, and prevent data loss. The SHA-256 algorithm is used to tackle these requirements. Current hardware architecture works present issues regarding real-time balance among processing, efficiency and cost, because some of them introduce significant critical paths. Besides, the SHA-256 algorithm itself considers no verification mechanisms for internal calculations and failure prevention. Hardware implementations can be affected by diverse problems, ranging from physical phenomena to interference or faults inherent to data spectra. Previous works have mainly addressed this problem through three kinds of redundancy: information, hardware, or time. To the best of our knowledge, pipelining has not been previously used to perform different hash calculations with a redundancy topic. Therefore, in this work, we present a novel hybrid architecture, implemented on a 3-stage pipeline structure, which is traditionally used to improve performance by simultaneously processing several blocks; instead, we propose using a pipeline technique for implementing hardware and time redundancies, analyzing hardware resources and performance to balance the critical path. We have improved performance at a certain clock speed, defining a data flow transformation in several sequential phases. Our architecture reported a throughput of 441.72 Mbps and 2255 LUTs, and presented an efficiency of 195.8 Kbps/LUT.

Design and implementation of 3-D printed radiation shields for environmental sensors.

The measurement of outdoor environmental and climatic variables is needed for many applications such as precision agriculture, environmental pollution monitoring, and the study of ecosystems. Some sensors deployed for these purposes such as temperature, relative humidity, atmospheric pressure, and carbon dioxide sensors require protection from climate factors to avoid bias. Radiation shields hold and protect sensors to avoid this bias, but commercial systems are limited, often expensive, and difficult to implement in low-cost contexts or large deployments for collaborative sensing. To overcome these challenges, this work presents an open source, easily adapted and customized design of a radiation shield. The device can be fabricated with inexpensive off-the-shelf parts and 3-D printed components and can be adapted to protect and isolate different types of sensors. Two material approaches are tested here: polylactic acid (PLA), the most common 3-D printing filament, and acrylonitrile styrene acrylate (ASA), which is known to offer better resistance against UV radiation, greater hardness, and generally higher resistance to degradation. To validate the designs, the two prototypes were installed on a custom outdoor meteorological system and temperature and humidity measurements were made in several locations for one month and compared against a proprietary system and a system with no shield. The 3-D printed materials were also both tested multiple times for one month for UV stability of their mechanical properties, their optical transmission and deformation under outdoor high-heat conditions. The results showed that ASA is the preferred material for this design and that the open source radiation shield could match the performance of proprietary systems. The open source system can be constructed for about nine US dollars, which enables mass development of flexible weather stations for monitoring needed in smart agriculture.

Liquid State Machine on SpiNNaker for Spatio-Temporal Classification Tasks.

Liquid State Machines (LSMs) are computing reservoirs composed of recurrently connected Spiking Neural Networks which have attracted research interest for their modeling capacity of biological structures and as promising pattern recognition tools suitable for their implementation in neuromorphic processors, benefited from the modest use of computing resources in their training process. However, it has been difficult to optimize LSMs for solving complex tasks such as event-based computer vision and few implementations in large-scale neuromorphic processors have been attempted. In this work, we show that offline-trained LSMs implemented in the SpiNNaker neuromorphic processor are able to classify visual events, achieving state-of-the-art performance in the event-based N-MNIST dataset. The training of the readout layer is performed using a recent adaptation of back-propagation-through-time (BPTT) for SNNs, while the internal weights of the reservoir are kept static. Results show that mapping our LSM from a Deep Learning framework to SpiNNaker does not affect the performance of the classification task. Additionally, we show that weight quantization, which substantially reduces the memory footprint of the LSM, has a small impact on its performance.

Trade-Off Analysis of Hardware Architectures for Channel-Quality Classification Models.

The latest generation of communication networks, such as SDVN (Software-defined vehicular network) and VANETs (Vehicular ad-hoc networks), should evaluate their communication channels to adapt their behavior. The quality of the communication in data networks depends on the behavior of the transmission channel selected to send the information. Transmission channels can be affected by diverse problems ranging from physical phenomena (e.g., weather, cosmic rays) to interference or faults inherent to data spectra. In particular, if the channel has a good transmission quality, we might maximize the bandwidth use. Otherwise, although fault-tolerant schemes degrade the transmission speed by solving errors or failures should be included, these schemes spend more energy and are slower due to requesting lost packets (recovery). In this sense, one of the open problems in communications is how to design and implement an efficient and low-power-consumption mechanism capable of sensing the quality of the channel and automatically making the adjustments to select the channel over which transmit. In this work, we present a trade-off analysis based on hardware implementation to identify if a channel has a low or high quality, implementing four machine learning algorithms: Decision Trees, Multi-Layer Perceptron, Logistic Regression, and Support Vector Machines. We obtained the best trade-off with an accuracy of 95.01% and efficiency of 9.83 Mbps/LUT (LookUp Table) with a hardware implementation of a Decision Tree algorithm with a depth of five.

[Surgical wound dehiscence and exposed hardware. Infection foretold?] / Dehiscencia de herida quirúrgica y exposición material de osteosíntesis. ¿Infección segura?

INTRODUCTION: surgical wound dehiscence with exposure of internal fixation material is a serious problem in orthopedic surgery and an important factor for infection. OBJECTIVE: presentation of an unusual case of an adult patient with surgical wound dehiscence and complete exposure of 20 cm of the ulnar plate after six years of surgery, without infection signs, with bone healing and skin behind the plate. CASE PRESENTATION: 39-year-old man with an open Gustilo II Monteggia fracture-dislocation multifracture. The patient had a history of drug dependence. He had an open reduction and internal fixation with an ulnar reconstruction plate. The patient did not have any follow-up. After six years of the surgery, there was a complete exposure of the plate (20 cm) without infection and healing of the fracture with misalignment. After removing the plate, we observed spontaneous epithelialization attached to the bone bed. Skin coverage was complete at two months. CONCLUSION: although unusual, bone consolidation without infection is possible in an open fracture with long-standing exposure to a forearm plate in the adult.

INTRODUCCIÓN: la dehiscencia de herida quirúrgica con exposición de material de fijación interna es un grave problema en cirugía ortopédica y un factor importante de infección. OBJETIVO: descripción del caso inusual de un paciente adulto con dehiscencia de la herida quirúrgica y exposición completa de 20 cm de largo de una placa de cúbito tras seis años de la cirugía, sin signos de infección, consolidación ósea y reepitelización debajo de la placa y adherida al hueso. CASO CLÍNICO: hombre de 39 años que sufrió una fractura-luxación de Monteggia, abierta grado II y multifragmentaria. El paciente tenía historia de drogodependencia en tratamiento con metadona. Fue tratado con fijación interna del cúbito mediante una placa de reconstrucción larga. Postoperatoriamente, el paciente dejó de acudir para evaluación. A los seis años de la cirugía presentaba una completa exposición de la placa (20 cm de longitud), sin signos de infección y consolidación con malalineación de la fractura. Tras el retiro de la placa se observó epitelización espontánea adherida al lecho óseo cubital. La cobertura cutánea fue completa a los dos meses. CONCLUSIÓN: aunque inusual, es posible la consolidación ósea y la ausencia de infección en una fractura abierta con exposición de larga evolución de una placa de antebrazo en el adulto.