Papers by John Jairo Villarejo Mayor
Anais do V Congresso Brasileiro de Eletromiografia e Cinesiologia e X Simpósio de Engenharia Biomédica, 2018
This work evaluates the performance of classification of dexterous hand movements based on low-de... more This work evaluates the performance of classification of dexterous hand movements based on low-density myoelectric signals (MES) from a group of tem amputees for the control of a myoelectric prosthesis. A pattern recognition system based on neural networks it was used as a classification system. A total of five grasp movements were considered to be recognized. Results showed an average classification 97%, indicating that all participants were able to perform muscle contractions with distinguishable sEMG patterns for different movements.
Acquisition Protocol and Comparison of Myoelectric Signals of the Muscles Innervated by the Ulnar, Radial and Medial Nerves for a Hand Orthoses
This paper proposes a protocol for obtaining surface myoelectric signals in muscles of the upper ... more This paper proposes a protocol for obtaining surface myoelectric signals in muscles of the upper limb for characterization of hand movement patterns. To characterize the movement patterns, the magnitude of the signal from each muscle is compared, for eight movements: (i) flexion, (ii) extension, (iii) ulnar and (iv) radial deviation of the hand, (v) metacarpophalangeal flexion, (vi) metacarpophalangeal extension, (vii) opposition and (viii) adduction thumb. Specific points were considered to acquire the signals from muscles innervated by the radial, medial and ulnar nerve, following the recommendations of the SENIAM project, in six intact people, using a myoelectric signal acquisition system. Seven protocols with recommendations for the location of sensors in the muscles were obtained, intended to establish combinations to reduce the number of sensors for future designs of assistive technologies, such as active orthoses. The suitable characteristic patterns for the hand movements st...
Sensors, 2021
Motor Imagery (MI)-based Brain–Computer Interfaces (BCIs) have been widely used as an alternative... more Motor Imagery (MI)-based Brain–Computer Interfaces (BCIs) have been widely used as an alternative communication channel to patients with severe motor disabilities, achieving high classification accuracy through machine learning techniques. Recently, deep learning techniques have spotlighted the state-of-the-art of MI-based BCIs. These techniques still lack strategies to quantify predictive uncertainty and may produce overconfident predictions. In this work, methods to enhance the performance of existing MI-based BCIs are proposed in order to obtain a more reliable system for real application scenarios. First, the Monte Carlo dropout (MCD) method is proposed on MI deep neural models to improve classification and provide uncertainty estimation. This approach was implemented using Shallow Convolutional Neural Network (SCNN-MCD) and with an ensemble model (E-SCNN-MCD). As another contribution, to discriminate MI task predictions of high uncertainty, a threshold approach is introduced an...
Exergames Training Effects on Gait During Single and Dual Tasks in Sexagenarian Women
Games for Health Journal, 2021
Objective: This study was designed to analyze the effects of an exergames training program on gai... more Objective: This study was designed to analyze the effects of an exergames training program on gait parameters while holding a cellphone conversation at self-selected walking speed (SSWS) and fast walking speed (FWS). Materials and Methods: Twenty-one older women (66.3 ± 4.0 years) practiced exergames for 12 weeks and were assessed for spatiotemporal gait parameters at SSWS and FWS under single task and dual task. The strength of the lower limbs was measured by an isokinetic dynamometer (Byodex System 3). The cognitive function was assessed with the Montreal Cognitive Assessment (MoCA). The tests were assessed 4 weeks before the start of the exergames training (baseline, T0), immediately before (pretraining, T1), and at the end of 12 weeks of the exergame training (post-training, T2), except for the MoCA test that was assessed at T0 and T2. Results: The spatiotemporal gait parameters at SSWS and FWS showed extensive changes when a cellphone conversation was sustained (e.g., 6.5% and 5.8% reduction in walking speed, respectively). Exergames training was not effective in minimizing these changes or improving muscle strength after 12 weeks (<3.0%). Minor cognitive improvements (0.5 points) were observed in response to training. Conclusion: Holding a cellphone conversation while walking changed several gait parameters, irrespective of the walking speed. The spatiotemporal gait parameters and lower limb muscle strength in sexagenarian women remained unchanged after the exergames training program.
International Journal on Advanced Science, Engineering and Information Technology, 2020
The reduced mobility in hand is a problem that prevents daily activities such as feeding, bathing... more The reduced mobility in hand is a problem that prevents daily activities such as feeding, bathing, brushing, dressing, grabbing objects, and losing autonomy in everyday situations. The hand disability is mainly due to the deficiency of the ulnar, medial, and radial nerves, which prevents adequate hand movements. In consequence, various assistive technologies are proposed to assist mobility, communication, self-help, and domestic activities. An alternative is the use of active orthosis, which by this proof of concept, the person can perform adequate hand movements. This paper aims to introduce a 3D active orthosis of PLA Plus designed by the Creative Lab in the Universidad Santiago de Cali, which includes an actuator and a low-cost myoelectric signal acquisition system, with two input channels. Finger flexion/extension movements and resting-state were performed. The user's intention is decoded processing rectified and integrated myoelectric signals. An on-off control algorithm was implemented to generate commands that control orthosis movements. The system is controlled by a person who has a disability due to a C5 and C6 spinal trauma that generated muscular atrophy in the distal level of the hand. Results showed the controlled flexion and extension of the fingers with a good performance. This system assists people with disabilities in the ulnar, medial, and radial nerves to make proper hand movements. The design of the above-mentioned orthosis allows individuals to carry out daily living activities to improve their quality of life.
The Effects of Different Exergame Intensity Training on Walking Speed in Older Women
Games for Health Journal, 2020
Objective: It is not known if the intensity in which exergames are performed can change gait para... more Objective: It is not known if the intensity in which exergames are performed can change gait parameters at different walking speeds. This study was designed to determine if a training program based on exergame exercises performed at different intensities (moderate vs. vigorous) influences walking speed and gait parameters in older adult women. Methods: After applying the inclusion criteria, 20 participants (69.5 ± 5.4 years) were randomized into two groups: moderate (11-13 perceived exertion) and vigorous (14-16 perceived exertion). Walking speed and gait parameters at self-selected walking speed (SSWS) and maximal walking speed (MWS) were evaluated before and after 3 months of exergame training. The walking speed and gait parameters were measured with an instrumented walkway. The walking speed reserve (WSR) was calculated as a difference and ratio. Results: There was pre-to-post effect of walking speed at self-selected walking pace (pre = 112.1 ± 16.4 cm.s-1; post = 124.8 ± 16.4 cm.s-1), in WSR calculated as ratio (pre = 1.35 ± 0.08; post = 1.28 ± 0.09), in a number of gait parameters at SSWS (step length, stride length, stride velocity, step time, stride time, swing time, stance time, single support, double support, gait cycle time, and cadence) and at MWS (step time, stride time, swing time, single support, double support, gait cycle time, and cadence). Conclusion: Irrespective of the exercise intensity, exergame training improved walking speed only at a self-selected walking pace and some gait parameters at self-selected and MWS in older women.
International Journal of Biosensors & Bioelectronics, 2018
Improving the functionality of hand prostheses using non-invasive techniques controlled by the us... more Improving the functionality of hand prostheses using non-invasive techniques controlled by the user intention continues being a focus of interest. Although myoelectric control has been widely studied, there are still lacks in the functionality and its applicability in real-time. Additionally, the application of myoelectric prostheses on amputees is still a challenge due to different factors related to non-clinical environments, as well as variations inherent in these subjects. This opinion includes a brief perspective of the trends to be addressed, in order to improve the functionality of these prosthetic devices.
Aging Clinical and Experimental Research, 2019
Background Tripping during walking is known to be the predominant cause of falls in elderly and p... more Background Tripping during walking is known to be the predominant cause of falls in elderly and prosthetic limb users. To standardise measurements and analysis of trips, it is critical to summarise the methods used in laboratory-controlled trials. Aim The aim of this study was to reach a clearer standardisation measurement and analysis of trips during elderly and prosthetic gait through a systematic review. Methods Studies that assessed elderly and prosthetic tripping gait characteristics were included in this review. The search resulted in an initial yield of 2493 unique articles after duplicates were removed (PubMed, Scopus and Science Direct). Title analysis resulted in 1697 articles excluded and 659 articles were assessed for further eligibility on the basis of the abstract. 174 articles were excluded based on a full-text appraisal. The final yield was 21 unique articles that met all the inclusion criteria. Results The findings revealed a number of inconsistencies among the studies, namely ambiguity in relation to gait speed, differences in overground and treadmill locomotion. Subsequently, different experimental setups such as trip inducement strategies may influence the collected data, and thus have implications for study outcomes. Conclusion A gold standard should be set to have better standardised results, thus creating a more robust and holistic approach towards the rehabilitation of prosthetic gait and in the elderly.
Revista Ingeniería Biomédica, 2019
Los robots proporcionan nuevas formas de terapia para pacientes con desórdenes neurológicos. Las ... more Los robots proporcionan nuevas formas de terapia para pacientes con desórdenes neurológicos. Las terapias de marcha asistidas con exoesqueletos pueden incrementar la duración y la intensidad de los entrenamientos para los pacientes y reducir el esfuerzo físico del terapeuta. Sin embargo, el uso de estos dispositivos para el entrenamiento de la marcha limita la interacción física entre el terapeuta y el paciente, en comparación con la terapia manual. Una apropiada realimentación de las funciones corporales y biomecánicas en la interacción con el sistema robótico facilita la evaluación del desempeño del paciente, motivándolo en el reaprendizaje de la marcha con resultados superiores. Este artículo presenta el diseño de una interfaz de usuario para un exoesqueleto de miembros inferiores para asistencia en la marcha y en terapias de rehabilitación. Se consideraron aspectos técnicos y clínicos para proporcionar ventajas del exoesqueleto durante las terapias, estableciendo una herramienta...
Research on Biomedical Engineering, 2018
This work presents the development of a novel robotic knee exoskeleton controlled by motion inten... more 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'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.
Revista Iberoamericana de Automática e Informática Industrial RIAI, 2017
Uno de los principales retos en el diseño de prótesis de mano es poder establecer un control intu... more Uno de los principales retos en el diseño de prótesis de mano es poder establecer un control intuitivo que reduzca el esfuerzo del usuario durante su entrenamiento. Este trabajo presenta un esquema para identificar tareas de motricidad fina de la mano, agrupadas en movimientos de los dedos individuales y gestos para el agarre de objetos el cual se ha validado con sujetos amputados. Se han comparado diferentes métodos de selección de características y clasificadores para el reconocimiento de patrones mioeléctricos, utilizando cuatro electrodos superficiales. Las características de las señales en el dominio del tiempo y la frecuencia se han combinado con métodos no lineales basados en análisis de fractales, mostrando una diferencia significativa en comparación con los métodos expuestos en la literatura para clasificar tareas de fuerza. Los resultados con amputados mostraron una exactitud de hasta 99,4% en los movimientos individuales de los dedos, superior a la obtenida con los gestos de agarre, de hasta 93,3%. El sistema ha obtenido una tasa de acierto promedio de 86,3% utilizando máquinas de soporte vectorial (SVM), seguido muy de cerca por K-vecinos más cercanos (KNN) con 83,4%. Sin embargo, KNN ha obtenido un mejor rendimiento global, debido a que es más rápido que SVM, lo que representa una ventaja para aplicaciones en tiempo real. El método aquí propuesto ofrece una mayor funcionalidad en el control de prótesis de mano, lo que mejoraría su aceptación por parte de los amputados.
Research on Biomedical Engineering, 2017
Intuitive prosthesis control is one of the most important challenges in order to reduce the user ... more Intuitive prosthesis control is one of the most important challenges in order to reduce the user effort in learning how to use an artificial hand. This work presents the development of a novel method for pattern recognition of sEMG signals able to discriminate, in a very accurate way, dexterous hand and fingers movements using a reduced number of electrodes, which implies more confidence and usability for amputees. Methods: The system was evaluated for ten forearm amputees and the results were compared with the performance of able-bodied subjects. Multiple sEMG features based on fractal analysis (detrended fluctuation analysis and Higuchi's fractal dimension) combined with traditional magnitude-based features were analyzed. Genetic algorithms and sequential forward selection were used to select the best set of features. Support vector machine (SVM), K-nearest neighbors (KNN) and linear discriminant analysis (LDA) were analyzed to classify individual finger flexion, hand gestures and different grasps using four electrodes, performing contractions in a natural way to accomplish these tasks. Statistical significance was computed for all the methods using different set of features, for both groups of subjects (able-bodied and amputees). Results: The results showed average accuracy up to 99.2% for able-bodied subjects and 98.94% for amputees using SVM, followed very closely by KNN. However, KNN also produces a good performance, as it has a lower computational complexity, which implies an advantage for real-time applications. Conclusion: The results show that the method proposed is promising for accurately controlling dexterous prosthetic hands, providing more functionality and better acceptance for amputees.
Upper Limb Prosthesis Devices
Individual Finger Control of Prosthetic Hand from Weak and Single-Channel Surface EMG
Dexterous hand gestures recognition based on low-density sEMG signals for upper-limb forearm amputees
Identification of low level sEMG signals for individual finger prosthesis
5th ISSNIP-IEEE Biosignals and Biorobotics Conference (2014): Biosignals and Robotics for Better and Safer Living (BRC), 2014
ABSTRACT This research reports the identification of motor tasks in a human hand from weak myoele... more ABSTRACT This research reports the identification of motor tasks in a human hand from weak myoelectric signals, aimed to control a prosthesis with individual finger flexion and wrist and grasps movements. The gestures were evaluated in two groups, independently. Four channel sEMG signals were captured on the forearm from able-body and amputees volunteers, taking into account low level contraction. Linear and non-linear parameters were extracted based on time and frequency domain and Detrended Fluctuation Analysis (DFA), to represent EMG patterns. The average classification accuracies were computed using Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) to evaluate the results. Confusion matrix from some experiments show the success rate identifying the gestures.
An exoskeleton for assisted rehabilitation of the knee is being developed to reduce the time spen... more An exoskeleton for assisted rehabilitation of the knee is being developed to reduce the time spent in the recovery of a patient and also, to help the therapist. A user interface was designed to interact with the exoskeleton through the system configuration, biofeedback and monitoring of kinetic y kinematic of the device and the biological data from the user. The conception of the user interface is the focus of this article. We describe the configuration of the exoskeleton central processing card through the user interface for a particular therapy, also convenient ways to submit relevant information for the therapist and other health professionals, and finally we describe the strategies used to provide biofeedback to the patient during the operation in real time.
Resumen. En este artículo se propone la evaluación de un sistema de reconocimiento de patrones a ... more Resumen. En este artículo se propone la evaluación de un sistema de reconocimiento de patrones a partir de la señal sEMG capturada en la superficie del brazo. Se definieron diferentes tipos de tareas motoras realizadas por la mano para ser reconocidas y controlar una prótesis robótica de brazo y mano. Los experimentos fueron realizados con personas saludables y se tomaron en cuenta las tareas con mayor capacidad de diferenciación entre sí. El sistema incluye una etapa de pre-procesamiento de la señal con filtros digitales; un sistema de extracción de características con transformada Wavelet Packet; y un clasificador de lógica difusa. Los resultados permitieron diferenciar hasta tres tareas diferentes.
Energia Elettrica
RESUMEN En este trabajo se presenta el desarrollo de un sistema software para el procesamiento, c... more RESUMEN En este trabajo se presenta el desarrollo de un sistema software para el procesamiento, caracterización y clasificación de señales electromiográficas de superficie aplicando técnicas de inteligencia computacional, a fin de detectar intencionalidad en cambios repentinos de movimiento durante la marcha y determinar la función que debe realizar una prótesis transfemoral basada en un sistema de control mioeléctrico en tiempo real, que sea adaptable al usuario y al terreno. Las señales adquiridas en individuos no amputados de diferente sexo y edad, son segmentadas para realizar un proceso de extracción de características en tiempo real combinando estimativos temporales y frecuenciales conformando un conjunto de patrones característicos aplicando reducción de dimensionalidad con análisis de componentes principales (PCA). Se realizó un reconocimiento de patrones relacionados con seis clases de movimientos, con redes neuronales perceptrón multicapa, redes de base radial y redes prob...
Upper Limb Prosthesis Devices
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Papers by John Jairo Villarejo Mayor