Jose M. Azorin

Universidad Miguel Hernández de Elche | UMH · Brain-Machine Interface Systems Lab

A new pandemic was declared at the end of 2019 because of coronavirus disease 2019 (COVID-19). One of the effects of COVID-19 infection is anosmia (i.e., a loss of smell). Unfortunately, this olfactory dysfunction is persistent in around 5% of the world’s population, and there is not an effective treatment for it yet. The aim of this paper is to de...

One important point in the development of a brain-machine Interface (BMI) commanding an exoskeleton is the assessment of the cognitive engagement of the subject during the motor imagery tasks conducted. However, there are not many databases that provide electroencephalography (EEG) data during the use of a lower-limb exoskeleton. The current paper...

This study explores the use of a brain-computer interface (BCI) based on motor imagery (MI) for the control of a lower limb exoskeleton to aid in motor recovery after a neural injury. The BCI was evaluated in ten able-bodied subjects and two patients with spinal cord injuries. Five able-bodied subjects underwent a virtual reality (VR) training sess...

Introduction: Brain-machine interfaces (BMIs) attempt to establish communication between the user and the device to be controlled. BMIs have great challenges to face in order to design a robust control in the real field of application. The artifacts, high volume of training data, and non-stationarity of the signal of EEG-based interfaces are chall...

This chapter introduces the reader to the use of brain-machine interfaces (BMIs) for use in combination with robotic entities. The content explores topics ranging from the different applications of neurorobotics to the actual difficulties a neuroengineer must confront in order to implement and assess the performance of a BMI designed to work with a...

Nowadays, several strategies for treating neuropsychologic function loss in Parkinson’s disease (PD) have been proposed, such as physical activity performance and developing games to exercise the mind. However, few studies illustrate the incidence of these therapies in neuronal activity. This work aims to study the feasibility of a virtual reality-...

EEG signals contain information directly related to cognitive activity. This paper presents a method to classify the images a person imagines via the information provided by the EEG signals. The images relating to the objects ‘tree’, ‘house’, ‘plane’ and ‘dog’ have been reconstructed. We have used a convolutional neural networks to obtain the recon...

Las Jornadas de Automática (JA) son el evento más importante del Comité Español de Automática (CEA), entidad científico-técnica con más de cincuenta años de vida y destinada a la difusión e implantación de la Automática en la sociedad. Este año se celebra la cuadragésima tercera edición de las JA, que constituyen el punto de encuentro de la comunida...

Las Jornadas de Automática (JA) son el evento más importante del Comité Español de Automática (CEA), entidad científico-técnica con más de cincuenta años de vida y destinada a la difusión e implantación de la Automática en la sociedad. Este año se celebra la cuadragésima tercera edición de las JA, que constituyen el punto de encuentro de la comunida...

Non-invasive brain-computer interfaces can be implemented through different paradigms, the most used one being motor imagery and evoked potentials, although recently there has been an interest in paradigms based on perception and visual imagery. Following this approach, this work demonstrates the classification of visual imagery, visual perception...

In the EEG literature, there is a lack of asynchronous intention models that realistically propose interfaces for applications that must operate in real time. In this work, a novel BMI approach to detect in real time the intention to turn is proposed. For this purpose, an offline, pseudo-online and online analysis is presented to validate the EEG a...

Spinal Cord Injury (SCI) refers to damage to the spinal cord that can affect different body functionalities. Recovery after SCI depends on multiple factors, being the rehabilitation therapy one of them. New approaches based on robot-assisted training offer the possibility to make training sessions longer and with a reproducible pattern of movements...

In this paper, the paradigm of the intention of speed changes from EEG signals with Riemannian classifiers methods is studied in 10 subjects. In addition, the best frequency band and how different electrode configurations affect the accuracy of the model are analyzed. In the prediction of the intention to change speed, results of 68.6% were obtaine...

Motor imagery (MI) brain-computer interfaces (BCI) have a critical function in the neurological rehabilitation of people with motor impairment. BCI are systems that employ brain activity to control any external device and MI is a commonly used control paradigm based on the imagination of a movement without executing it. The main limitation of these...

Neurorehabilitation has gradually become one of the most hopeful tools in some kind of injuries and diseases during the last decade. Several studies have shown that conscious movement effected by patients with mobility difficulties, assisted by a clinical device such as an exoskeleton, contributes positively to their mobility recovery, shortening t...

This study examines the feasibility of using a robot-assisted therapy methodology based on the Bobath concept to perform exercises applied in conventional therapy for gait rehabilitation in stroke patients. The aim of the therapy is to improve postural control and movement through exercises based on repetitive active-assisted joint mobilization, wh...

Stroke is a medical condition characterized by the rapid loss of focal brain function. Post-stroke patients attend rehabilitation training to prevent the degeneration of physical function and improve upper limb movements and functional status after stroke. Promising rehabilitation therapies include functional electrical stimulation (FES), exergamin...

In this paper a pseudo-online analysis has been performed to detect the reaction of both healthy users and incomplete Spinal Cord Injury patients to obstacle appearance during walking. A new methodology to improve model gas been described. It consist of discardind trials where brain responses to the obstacles does not correspond with the expected....

En este trabajo se ha realizado un análisis de la fatiga muscular mediante una arquitectura de bajo coste. Ésta está basada en Arduino y eHealth. Uno de los objetivos principales ha sido el de realizar todo el procesamiento en tiempo real dentro de la propia arquitectura utilizando Matlab únicamente como medio de visualización y envío de ordenes si...

This article presents an exhaustive analysis of the works present in the literature pertaining to transcranial direct current stimulation(tDCS) applications. The aim of this work is to analyze the specific characteristics of lower-limb stimulation, identifying the strengths and weaknesses of these works and framing them with the current knowledge o...

This work presents the development and implementation of an interface to control a robotic exoskeleton for gait rehabilitation in patients with stroke through exercises based on conventional neuro-rehabilitation therapies. Movement patterns of each exercise were acquired using an optoelectronic ten-camera system in a group of subjects without patho...

The combination of a lower-limb exoskeleton with brain computer interfaces (BCI) can assist patients with motor impairment to walk again. In addition, it can promote the neural plasticity of the affected brain region. The present paper shows a research performed on seven able-bodied subjects that walked with an assistive exoskeleton controlled by e...

The design of solid interfaces based on the patterns of brain activity that underlie human decision-making are a field of interest in creating interfaces that allow recover the pathway between the brain and the muscular system to be rectified. In this work, a Brain Machine Interface is presented to detect the user's intention through the differenti...

Brain Machine Interfaces (BMI) combined with lower-limb exoskeletons can assist patients that have difficulties in walking. However, BMI need some calibration to adjust their parameters to each user. This process is time-consuming and can be fatiguing for the users. In this work, the optimal number of recordings needed to adjust a EEG-based BMI to...

Control of assistive devices by voluntary user intention is an underdeveloped topic in the Brain–Machine Interfaces (BMI) literature. In this work, a preliminary real-time BMI for the speed control of an exoskeleton is presented. First, an offline analysis for the selection of the intention patterns based on the optimum features and electrodes is p...

Brain-Computer interface systems allow the recognition of neuronal activity to create a direct communication channel between the brain and the outside world without using the peripheral nervous system. Many of the paradigms used are based on the detection of motor imagery and evoked potentials. In this work we study the use of visual imagery of geo...

Footwear comfort is one of the determinant factors in a buyout decision. The understanding of which brain patterns are involved in the comfort perception of footwear could be an important element to develop the consumer neuroscience field, and could even help during the development phase of new products. The present paper studies the comfort percep...

Brain–Computer Interfaces (BCI) are systems that allow external devices to be controlled by means of brain activity. There are different such technologies, and electroencephalography (EEG) is an example. One of the most common EEG control methods is based on detecting changes in sensorimotor rhythms (SMRs) during motor imagery (MI). The aim of this...

El uso de interfaces cerebro máquina (BCIs) supone un importante avance en el control de dispositivos para la rehabilitación de pacientes. Además, la detección de la atención durante la marcha puede ser fundamental a la hora de garantizar la seguridad en el control de estos dispositivos mediante electroencefalogramas (EEG) y evitar activaciones inv...

Las interfaces cerebro-máquina (BMIs de Brain- Machine Interfaces) son sistemas que utilizan la actividad cerebral para controlar dispositivos externos. Existen diversos paradigmas de control y uno de los más utilizados se basa en la imaginación motora (IM). La combinación de BMIs basadas en IM con dispositivos de asistencia como exoesqueletos robó...

Objective Brain–machine interfaces have performed continuous trajectory reconstruction of limb movements from brain signals relying on multiple linear regression. Most reported approaches deal with the reconstruction of the entire motion trajectory using a single regression and choosing its parameters arbitrarily. This study proposes the reconstruc...

Lower-limb robotic exoskeletons are wearable devices that can be beneficial for people with lower-extremity motor impairment because they can be valuable in rehabilitation or assistance. These devices can be controlled mentally by means of brain–machine interfaces (BMI). The aim of the present study was the design of a BMI based on motor imagery (M...

Motor imagery (MI) is one of the most common paradigms used in brain-computer interfaces (BCIs). This mental process is defined as the imagination of movement without any motion. In some lower-limb exoskeletons controlled by BCIs, users have to perform MI continuously in order to move the exoskeleton. This makes it difficult to design a closed-loop...

Robotic devices can provide physical assistance to people who have suffered neurological impairments such as stroke. Neurological disorders related to this condition induce abnormal gait patterns, which impede the independence to execute different Activities of Daily Living (ADLs). From the fundamental role of the ankle in walking, Powered Ankle-Fo...

Brain-machine interfaces (BMIs) are useful tools for controlling assistive devices. One current approach in this field is continuous trajectory reconstruction (CTR), which decodes variables from electroencephalographic (EEG) signals. In this study, the CTR approach was applied to estimate kinetic variables from lower limb joints during pre-gait mov...

Brain–Computer Interfaces (BCIs) are becoming an important technological tool for the rehabilitation process of patients with locomotor problems, due to their ability to recover the connection between brain and limbs by promoting neural plasticity. They can be used as assistive devices to improve the mobility of handicapped people. For this reason,...

This article shows the lessons learned from clinical trials of a new neurorehabilitation therapy for cerebro-vascular accident (CVA) patients. The new therapy is based on the combination of a transcranial direct current stimulation (tDCS) strategy, a brain–machine interface (BMI) based on electroencephalographic signals, and a pedaling system. The...

Brain-machine interfaces (BMIs) can improve the control of assistance mobility devices making its use more intuitive and natural. In the case of an exoskeleton, they can also help rehabilitation therapies due to the reinforcement of neuro-plasticity through repetitive motor actions and cognitive engagement of the subject. Therefore, the cognitive i...

The use of brain-machine interfaces in combination with robotic exoskeletons is usually based on the analysis of the changes in power that some brain rhythms experience during a motion event. However, this variation in power is frequently obtained through frequency filtering and power estimation using the Fourier analysis. This paper explores the d...

Background: Functional electrical stimulation (FES) is a modality of motor rehabilitation that consists of the programmed application of bursts of electrical current to the a ected neuromuscular region that aims to improve muscle strength, increase the range of motion, facilitate movement control and decrease spasticity. The present study aimed to...

Brain–Computer Interface (BCI) systems establish a channel for direct communication between the brain and the outside world without having to use the peripheral nervous system. While most BCI systems use evoked potentials and motor imagery, in the present work we present a technique that employs visual imagery. Our technique uses neural networks to...

Background: Robotic devices can provide physical assistance to people who have suffered neurological impairments such as stroke. Neurological disorders related to this condition induce abnormal gait patterns, which harm the independence to execute different Activities of Daily Living (ADL). From the fundamental role of the ankle in walking, Active...

Spinal cord injury (SCI) limits life expectancy and causes a restriction of patient's daily activities. In the last years, robotics exoskeletons have appeared as a promising rehabilitation and assistance tool for patients with motor limitations, as people that have suffered a SCI. The usability and clinical relevance of these robotics systems could...

This paper studies the direction changes during the gait by means of two different distributions of electrodes located in the motor, premotor and occipital areas. The objective is analyzing which areas are involved in the detection of the intention of turning while the person is walking. The signals in both options are characterized with frequency...

The use of transcranial direct current stimulation (tDCS) has been related to the improvement of motor and learning tasks. The current research studies the effects of an asymmetric tDCS setup over brain connectivity, when the subject is performing a motor imagery (MI) task during five consecutive days. A brain–computer interface (BCI) based on elec...

The aim of this paper is to describe new methods for detecting the appearance of unexpected obstacles during normal gait from EEG signals, improving the accuracy and reducing the false positive rate obtained in previous studies. This way, an exoskeleton for rehabilitation or assistance of people with motor limitations commanded by a Brain-Machine I...

Hackathons are becoming these days more and more popular. The present chapter introduces the concept of brain on art hackathon. This new type of hackathon, based on the interaction of art, science, and engineering, is a successful event where learning, innovativeness, art and neuro-technology meet.

Creativity and the experience of aesthetic reflection are two of the most profound mysteries of the human brain, both enabling us to continually innovate through problem-solving and express complex emotions that help define what it means to be human. The burgeoning field of neuroaesthetics offers a unique possibility to work in a genuinely interdis...

El análisis de las señales cerebrales para la asistencia en pacientes con movilidad reducida es un área de investigación continua en la que las nuevas tecnologías ofrecen un amplio espectro de posibilidades para la ayuda activa como los exoesqueletos y las interfaces cerebro-maquinas (BMI). En este trabajo nos centramos en realizar una interfaz BMI...

Lower-limb exoskeletons have been used in gait rehabilitation to facilitate the restoration of motor skills. These robotics systems could be complemented by Brain-Computer Interfaces (BCIs) to assist or rehabilitate people with walking disabilities. In this preliminary study, electroencephalography-based brain functional connectivity is analyzed du...

This research will study the effects of a rehabilitation program assisted by a powered lower extremity exoskeleton in patients after stroke. It will compare clinical and biomechanical features of patients at baseline and after intervention. Additionally, it will also examine the use of a brain-computer-interface (BCI) to command movements on the po...

Transcranial direct current stimulation (tDCS) is a non-invasive technique for brain stimulation capable of modulating brain excitability. Although beneficial effects of tDCS have been shown, the underlying brain mechanisms have not been described. In the present study, we aim to investigate the effects of tDCS on EEG-based functional connectivity,...

This article surveys the main lower limb exoskeletons developed, or under development, in Latin-America, under the REASISTE Ibero American Network. There are several groups working in this field, which approaches and results are comparable to those reported by other groups in Europe or North America (ALLOR, CPWalker, BioMot, Kinesis and CHIEF exosk...

The paper compares different signal processing algorithms and classifiers to evaluate the accuracy of a BMI based on lower-limb motor imagery. The methods were based on the analysis of the peaks of the different processing epochs for the alpha, beta and gamma EEG bands through the Marginal Hilbert Spectrum, Power Spectral Density and Fourier harmon...

Mobile Brain–Body Imaging and the Neuroscience of Art, Innovation and Creativity is a trans-disciplinary, collective, multimedia collaboration that critically uncovers the challenges and opportunities for transformational and innovative research and performance at the nexus of art, science and engineering. This book addresses a set of universal an...

El patrón de marcha de las personas con hemiparesia se caracteriza por su baja velocidad, patrón asimétrico de movimiento, disminución del largo de paso y la alteración cinemática de cadera, rodilla y tobillo. El pie caído es una alteración de la marcha que ocurre en la hemiparesia, que se caracteriza por la dificultad de realizar flexión dorsal de...

The aim of this work was to test if a novel transcranial direct current stimulation (tDCS) montage boosts the accuracy of lower limb motor imagery (MI) detection by using a real-time brain-machine interface (BMI) based on electroencephalographic (EEG) signals. The tDCS montage designed was composed of two anodes and one cathode: one anode over the...

Detection of the Visual Imagination using EEG

p>El uso de interfaces cerebro-máquina en personas que han sufrido un accidente cerebro-vascular puede ayudar en su proceso de rehabilitación mediante la implicación cognitiva del paciente. Dichas interfaces traducen las ondas cerebrales en comandos con el fin de controlar un dispositivo mecánico de movimiento asistido. No obstante, el control de e...

Force is generated by muscle units according to the neural activation sent by motor neurons. The motor unit is therefore the interface between the neural coding of movement and the musculotendinous system. Here we propose a method to accurately measure the latency between an estimate of the neural drive to muscle and force. Further, we systematical...

This work studies a novel transcranial direct current stimulation (tDCS) montage to improve a brain-machine interface (BMI) lower limb motor imagery detection. The tDCS montage is composed by two anodes and one cathode. One anode is located over the motor cortex and the other one over the cerebellum. Ten healthy subjects participated in this experi...

The use of motion assistance devices improves the rehabilitation process of patients that have motor disabilities. In the case these devices are controlled by brain-machine interfaces, the rehabilitation process can be improved due to neuroplasticity. However, in the case of lower limb rehabilitation, the limited accuracy of the control algorithms...