Métodos Computacionales para el Reconocimiento de Patrones Mioeléctricos en el Control de Exoesqueletos Robóticos: Una Revisión

El desarrollo de las interfaces hombre-máquina ha representado una línea de investigación interesante y ampliamente estudiada en el campo de la rehabilitación. En este sentido, para potencializar los procesos de rehabilitación física de las personas con discapacidad motora hay un esfuerzo creciente en la comunidad científica hacia el desarrollo de nuevos dispositivos robóticos, como los exoesqueletos. El control mioeléctrico es una técnica avanzada concerniente con la detección, procesamiento, clasificación y aplicación de señales electromiográficas para el control de sistemas externos y dispositivos de rehabilitación. En la terapia física efectuada mediante el uso de sistemas robóticos, es fundamental una identificación efectiva de la intención de los movimientos humanos para comandar tales sistemas. En la literatura se han utilizado ampliamente las señales electromiográficas de superficie, teniendo en cuenta que las mismas pueden reflejar la intención del movimiento. Este artículo proporciona una revisión de las técnicas y métodos computacionales que han sido utilizados, basados en técnicas de extracción de características y reconocimiento de patrones para el control mioléctrico de exoesqueletos. Se abordan trabajos que hacen uso de estos métodos, para el control de los dispositivos robóticos, y se plantean direcciones futuras en este campo de investigación

Characterization of the cicatrization process in diabetic foot ulcers based on the production of reactive oxygen species

The present study aims at evaluating the correlation between the free radical formation and the healing action of lower limbs’ ulcers in a randomized controlled trial with the use of an adhesive derived from natural latex associated with a light-emitting diode (LED) circuit. The sample consists of 15 participants with lower limb lesions divided into three groups: group 1 case (5 participants) received the proposed dressing system adhesive of the natural latex associated with the LED circuit; group 2 control (5 participants) received the dressings at home performed by nurses according to and established by the clinic of wounds (treated with calcium alginate or silver foam); and group 3 (5 participants) also received the dressing in their homes with the use of the dressing adhesive derived from the natural latex associated with the LED circuit. The collected data were analyzed qualitatively and quantitatively by electron paramagnetic resonance for determination of free radical formation. Kruskal-Wallis statistical test was used to evaluate the effect of treatment on the lower limb’s ulcer cicatrization process and its correlation with free radical. The results obtained corroborated the hypothesis about the reduction of the quantity of these molecules in the end of treatment related to the healing wound

Evolving trends in the management of acute appendicitis during COVID-19 waves. The ACIE appy II study

Background: In 2020, ACIE Appy study showed that COVID-19 pandemic heavily affected the management of patients with acute appendicitis (AA) worldwide, with an increased rate of non-operative management (NOM) strategies and a trend toward open surgery due to concern of virus transmission by laparoscopy and controversial recommendations on this issue. The aim of this study was to survey again the same group of surgeons to assess if any difference in management attitudes of AA had occurred in the later stages of the outbreak. Methods: From August 15 to September 30, 2021, an online questionnaire was sent to all 709 participants of the ACIE Appy study. The questionnaire included questions on personal protective equipment (PPE), local policies and screening for SARS-CoV-2 infection, NOM, surgical approach and disease presentations in 2021. The results were compared with the results from the previous study. Results: A total of 476 answers were collected (response rate 67.1%). Screening policies were significatively improved with most patients screened regardless of symptoms (89.5% vs. 37.4%) with PCR and antigenic test as the preferred test (74.1% vs. 26.3%). More patients tested positive before surgery and commercial systems were the preferred ones to filter smoke plumes during laparoscopy. Laparoscopic appendicectomy was the first option in the treatment of AA, with a declined use of NOM. Conclusion: Management of AA has improved in the last waves of pandemic. Increased evidence regarding SARS-COV-2 infection along with a timely healthcare systems response has been translated into tailored attitudes and a better care for patients with AA worldwide

Infected pancreatic necrosis: outcomes and clinical predictors of mortality. A post hoc analysis of the MANCTRA-1 international study

: The identification of high-risk patients in the early stages of infected pancreatic necrosis (IPN) is critical, because it could help the clinicians to adopt more effective management strategies. We conducted a post hoc analysis of the MANCTRA-1 international study to assess the association between clinical risk factors and mortality among adult patients with IPN. Univariable and multivariable logistic regression models were used to identify prognostic factors of mortality. We identified 247 consecutive patients with IPN hospitalised between January 2019 and December 2020. History of uncontrolled arterial hypertension (p = 0.032; 95% CI 1.135-15.882; aOR 4.245), qSOFA (p = 0.005; 95% CI 1.359-5.879; aOR 2.828), renal failure (p = 0.022; 95% CI 1.138-5.442; aOR 2.489), and haemodynamic failure (p = 0.018; 95% CI 1.184-5.978; aOR 2.661), were identified as independent predictors of mortality in IPN patients. Cholangitis (p = 0.003; 95% CI 1.598-9.930; aOR 3.983), abdominal compartment syndrome (p = 0.032; 95% CI 1.090-6.967; aOR 2.735), and gastrointestinal/intra-abdominal bleeding (p = 0.009; 95% CI 1.286-5.712; aOR 2.710) were independently associated with the risk of mortality. Upfront open surgical necrosectomy was strongly associated with the risk of mortality (p < 0.001; 95% CI 1.912-7.442; aOR 3.772), whereas endoscopic drainage of pancreatic necrosis (p = 0.018; 95% CI 0.138-0.834; aOR 0.339) and enteral nutrition (p = 0.003; 95% CI 0.143-0.716; aOR 0.320) were found as protective factors. Organ failure, acute cholangitis, and upfront open surgical necrosectomy were the most significant predictors of mortality. Our study confirmed that, even in a subgroup of particularly ill patients such as those with IPN, upfront open surgery should be avoided as much as possible. Study protocol registered in ClinicalTrials.Gov (I.D. Number NCT04747990)

Metodology for estimation of knee angle for detection motion intention

Tese (doutorado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2010.O sinal mioelétrico de superfície pode ser utilizado de maneira eficaz para detectar a intenção de movimento no controle de próteses mecânicas. Quando se trata da concepção de um projeto que utiliza o controle mioelétrico, a implementação de um algoritmo que utiliza tal técnica é de fundamental importância. Este trabalho propõe dois algoritmos de estimação do ângulo do joelho para detectar a intenção de movimento em uma prótese de perna. A primeira proposta usa como dados a informação extraída a partir de dois canais de eletromiografia e um canal para eletrogoniômetro. A informação é processada por meio de três estágios: (1) extração de características utilizando modelos auto-regressivos e histograma; (2) projeção de características por meio de mapas auto-organizáveis e (3) classificação de padrões usando rede neural perceptron multicamada. A segunda proposta de algoritmo usa a informação extraída a partir de sensores giroscópios como dados adicionais à primeira proposta. A informação é processada por meio de três estágios: (1) extração de características utilizando coeficientes cepstrais e a entropia no sinal mioelétrico, (2) classificação de padrões usando rede neural perceptron multicamada e (3) fusão de dados a partir do filtro de Kalman, utilizando três variantes para a estimação do ângulo do joelho. A plataforma experimental desenvolvida é um sistema micro-controlado para a aquisição e pré-processamento dos sinais mioelétricos em tempo real. É apresentada uma comparação quantitativa entre os algoritmos propostos, o método de Ferreira et al. e o método wavelet packets – análise de componentes principais, baseada em indicadores como percentual erro–sinal, coeficiente de correlação e número, amplitude e duração do erro. Os resultados obtidos demonstram que é possível estimar continuamente a posição do ângulo do joelho a partir dos sinais mioelétricos e sua fusão com sensores proprioceptivos. _________________________________________________________________________________ ABSTRACTThe myoelectric signal can be used in an effective way for detecting motion intention in order to control mechanical prostheses. In the design and implementation of a myoelectric controller, the implementation of the myoelectric algorithm is very important. This work proposes two algorithms to estimate knee angle to detect motion intention in leg prostheses. The first algorithm uses the information extracted from two electromyography (EMG) channels and one electrogoniometer channel. This information is processed through three stages: (1) feature extraction using auto-regressive models and histogram, (2) feature projections through self-organizing maps and (3) pattern classification using a perceptron neural network. The second algorithm uses information from gyroscopic sensors as additional data. This information is processed through three stages: (1) feature extraction using cepstral coefficients and the myoelectric signal entropy, (2) pattern classification using a perceptron neural network and (3) data fusion from kalman filter using three variant for knee angle estimation. A micro-controlled bioinstrumentation system has been developed for the acquisition and pre-processing of the electromyographic signal in real-time. A quantitative comparison between the proposed algorithms, the method by Ferreira et al. and the wavelet packet – principal components analysis are presented, based on several metrics such as the error-to-signal percentage (ESP), the correlation coefficients, and the number, amplitude and duration of error events. The results demonstrate that it is possible to estimate continuously the knee angle from mioelectric signals and their fusion with proprioceptive sensors

Robotic Training System for Upper Limb Rehabilitation

Background: Robot-assisted therapy or exoskeleton is an active mechanical device that can be easily adjusted to fit a different patient limb length, and is able to coordinate and amplify movements. The aim of this study focuses on developing a robotic training system and quantification methods for upper limbs rehabilitation in clinic environments to be used in survivor stroke patients with motor disorders or loss of physical strength on one side of the body. Methods: From an integrated approach, a design of one exoskeleton is presented which allows patients perform complex movements in four degrees of freedom (DOF) rehabilitation system. The system is controlled by means of user interface developed with Lab view v8.6 software that supports control and user interaction with the exoskeleton; so it's possible for therapist to modify the patient routine including new movements and a number of repetitions in articulating joints of shoulder, elbow and wrist. On other hand system permits bio-feedback of electromyogram patient activity during rehabilitation sessions. Results: Biomechanical analyses and structure design, implementation of power systems, the development of the control system and user interface as well as its integration with the mechanical system is presented. Conclusions: A robot arm exoskeleton device with four DOF; able to develop complex, accurate and repetitive therapeutic routines for articulating joints of shoulder, elbow and wrist trough an interface is shown. The device permits to follow chronologically patient outcomes recording the electromyogram activity during rehabilitation progress.Introducción: Un exoesqueleto se conceptualiza como un mecanismo estructural externo cuyos segmentos y articulaciones se corresponden con las del cuerpo humano y es capaz de coordinar y amplificar sus movimientos. El objetivo del trabajo se enfoca en desarrollar una tecnología de plataforma robótica de asistencia y métodos de cuantifica-ción para la rehabilitación motora de miembros superiores en ambientes clínicos y ambulatorios para pacientes con afecciones motoras como resultado de enfermedades cerebro-vasculares. Métodos: Se presenta a partir de una concepción integradora el diseño del prototipo de un exoesqueleto que permite al paciente realizar movimientos combinados a partir de los cuatro grados de libertad que provee el dispositivo de rehabilitación. El sistema es controlado por medio de una interfaz de usuario desarrollada en Labview, que soporta el control e interacción del usuario con el exoesqueleto, lo cual posibilita que el terapeuta puede modificar la rutina que debe realizar el paciente incluyendo nuevas trayectorias y el número de repeticiones a seguir por el exoesqueleto en las articulaciones de hombro, codo y muñeca. Adicionalmente, posibilita la retroalimentación visual de la actividad electromiográfica del paciente durante la rehabilitación. Resultados: Se presenta el diseño mecánico de la armadura, la implementación de los sistemas de potencia, el desarrollo del sistema de control y de la interfaz de usuario, así como su integración con el sistema mecánico. Conclusiones: Se desarrolla y pone en funcionamiento una avanzada plataforma robótica capaz de desarrollar diversas rutinas terapéuticas combinando 4 grados de libertad en hombro, codo y muñeca, capaz de controlar a través de la interfaz desarrollada desplazamientos regulados, exactos y repetitivos, así como seguir cronológicamente la evolución del paciente registrando la actividad mioeléctrica durante el proceso de rehabilitación

Adaptive Spatial Filter Based on Similarity Indices to Preserve the Neural Information on EEG Signals during On-Line Processing

This work presents a new on-line adaptive filter, which is based on a similarity analysis between standard electrode locations, in order to reduce artifacts and common interferences throughout electroencephalography (EEG) signals, but preserving the useful information. Standard deviation and Concordance Correlation Coefficient (CCC) between target electrodes and its correspondent neighbor electrodes are analyzed on sliding windows to select those neighbors that are highly correlated. Afterwards, a model based on CCC is applied to provide higher values of weight to those correlated electrodes with lower similarity to the target electrode. The approach was applied to brain computer-interfaces (BCIs) based on Canonical Correlation Analysis (CCA) to recognize 40 targets of steady-state visual evoked potential (SSVEP), providing an accuracy (ACC) of 86.44 ± 2.81%. In addition, also using this approach, features of low frequency were selected in the pre-processing stage of another BCI to recognize gait planning. In this case, the recognition was significantly (p < 0.01) improved for most of the subjects (ACC ¿ 74.79%), when compared with other BCIs based on Common Spatial Pattern, Filter Bank - Common Spatial Pattern, and Riemannian Geometry.This research was partially supported by the Spanish Government, Ministry of Economy and Competitiveness (grants NeuroMOD, DPI2015-68664-C4-1-R, and ESSENTIAL, DPI2015-72638-EXP). Authors would like to thank CNPq (304192/2016-3), CAPES (88887.095626/2015-01), and FAPES (72982608) from Brazil, Emerging Leaders in the America’s Program (ELAP, Canada), and SENESCYT (Ecuador) for supporting this researchPeer Reviewe

Control of a robotic knee exoskeleton for assistance and rehabilitation based on motion intention from sEMG

Introduction: This work presents the development of a novel robotic knee exoskeleton controlled by motion intention based on sEMG, which uses admittance control to assist people with reduced mobility and improve their locomotion. Clinical research remark that these devices working in constant interaction with the neuromuscular and skeletal human system improves functional compensation and rehabilitation. Hence, the users become an active part of the training/rehabilitation, facilitating their involvement and improving their neural plasticity. For recognition of the lower-limb motion intention and discrimination of knee movements, sEMG from both lower-limb and trunk are used, which implies a new approach to control robotic assistive devices. Methods A control system that includes a stage for human-motion intention recognition (HMIR), based on techniques to classify motion classes related to knee joint were developed. For translation of the user&#8217;s intention to a desired state for the robotic knee exoskeleton, the system also includes a finite state machine and admittance, velocity and trajectory controllers with a function that allows stopping the movement according to the users intention. Results The proposed HMIR showed an accuracy between 76% to 83% for lower-limb muscles, and 71% to 77% for trunk muscles to classify motor classes of lower-limb movements. Experimental results of the controller showed that the admittance controller proposed here offers knee support in 50% of the gait cycle and assists correctly the motion classes. Conclusion The robotic knee exoskeleton introduced here is an alternative method to empower knee movements using sEMG signals from lower-limb and trunk muscles

Evolving trends in the management of acute appendicitis during COVID-19 waves. The ACIE appy II study (vol 46, pg 2021, 2022)

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Global attitudes in the management of acute appendicitis during COVID-19 pandemic: ACIE Appy Study

Background: Surgical strategies are being adapted to face the COVID-19 pandemic. Recommendations on the management of acute appendicitis have been based on expert opinion, but very little evidence is available. This study addressed that dearth with a snapshot of worldwide approaches to appendicitis. Methods: The Association of Italian Surgeons in Europe designed an online survey to assess the current attitude of surgeons globally regarding the management of patients with acute appendicitis during the pandemic. Questions were divided into baseline information, hospital organization and screening, personal protective equipment, management and surgical approach, and patient presentation before versus during the pandemic. Results: Of 744 answers, 709 (from 66 countries) were complete and were included in the analysis. Most hospitals were treating both patients with and those without COVID. There was variation in screening indications and modality used, with chest X-ray plus molecular testing (PCR) being the commonest (19\ub78 per cent). Conservative management of complicated and uncomplicated appendicitis was used by 6\ub76 and 2\ub74 per cent respectively before, but 23\ub77 and 5\ub73 per cent, during the pandemic (both P < 0\ub7001). One-third changed their approach from laparoscopic to open surgery owing to the popular (but evidence-lacking) advice from expert groups during the initial phase of the pandemic. No agreement on how to filter surgical smoke plume during laparoscopy was identified. There was an overall reduction in the number of patients admitted with appendicitis and one-third felt that patients who did present had more severe appendicitis than they usually observe. Conclusion: Conservative management of mild appendicitis has been possible during the pandemic. The fact that some surgeons switched to open appendicectomy may reflect the poor guidelines that emanated in the early phase of SARS-CoV-2