
José L Contreras-VidalUniversity of Houston | U of H, UH · Department of Electrical & Computer Engineering
José L Contreras-Vidal
Ph.D., M.S.E.E., Engineer
About
299
Publications
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Introduction
Professor Contreras-Vidal (IEEE M’88–SM’08) directs the Noninvasive Brain–Machine Interface Systems Lab at the University of Houston. His research interests include neuroprosthetics and powered exoskeletons, neuroaesthetics studies conducted in public settings, mobile neuroimaging, reverse-translational studies of brain plasticity, computational neuroscience and regulatory aspects of human-machine systems. See:
http://www.ee.uh.edu/faculty/contreras-vidal
http://www.facebook.com/UHBMIST
Additional affiliations
August 1999 - October 2011
Education
August 1990 - December 1993
August 1988 - December 1989
June 1982 - May 1987
Publications
Publications (299)
This report contains a description of physiological and motion data, recorded simultaneously and in synchrony using the hyperscanning method from two professional dancers using wireless mobile brain-body imaging (MoBI) technology during rehearsals and public performances of “LiveWire” - a new composition comprised of five choreographed music and da...
Background
Dissecting the neurobiology of dance would shed light on a complex, yet ubiquitous, form of human communication. In this experiment, we sought to study, via mobile electroencephalography (EEG), the brain activity of five experienced dancers while dancing butoh, a postmodern dance that originated in Japan.
Results
We report the experimen...
Neurological disorders affecting speech production adversely impact quality of
life for over 7 million individuals in the US. Traditional speech interfaces like eyetracking
devices and P300 spellers are slow and unnatural for these patients. An
alternative solution, speech Brain-Computer Interfaces (BCIs), directly decodes speech
characteristics, o...
Although significant progress has been made in understanding the cortical correlates underlying balance control, these studies focused on a single task, limiting the ability to generalize the findings. Different balance tasks may elicit cortical activations in the same regions but show different levels of activation because of distinct underlying m...
Implanted brain–computer interfaces (iBCIs) translate brain activity recorded intracranially into commands for virtual or physical machines to restore or rehabilitate motor, sensory or speech functions. Currently, no iBCIs have been approved by regulatory agencies for the medical device market despite being in clinical trials since 1998, with littl...
Although significant progress has been made in understanding the cortical correlates underlying balance control, these studies focused on a single task limiting the ability to generalize the find-ings. Different balance tasks may elicit cortical activations in the same regions but show different levels of activation because of distinct underlying m...
Balance control is an important indicator of mobility and independence in activities of daily living. How the functional coupling between the cortex and the muscle for balance control is affected following stroke remains to be known. We investigated the changes in coupling between the cortex and leg muscles during a challenging balance task over mu...
Neurological disorders affecting speech production adversely impact quality of life for over 7 million individuals in the US. Traditional speech interfaces like eyetracking devices and P300 spellers are slow and unnatural for these patients. An alternative solution, speech Brain-Computer Interfaces (BCIs), directly decodes speech characteristics, o...
Background
This research focused on the development of a motor imagery (MI) based brain–machine interface (BMI) using deep learning algorithms to control a lower-limb robotic exoskeleton. The study aimed to overcome the limitations of traditional BMI approaches by leveraging the advantages of deep learning, such as automated feature extraction and...
Objective. Currently, few non-invasive measures exist for directly measuring spinal sensorimotor networks. Electrospinography (ESG) is one non-invasive method but is primarily used to measure evoked responses or for monitoring the spinal cord during surgery. Our objectives were to evaluate the feasibility of ESG to measure spinal sensorimotor netwo...
Sixty percent of elderly hand movements involve grasping, which is unarguably why grasp restoration is a major component of upper-limb rehabilitation therapy. Neuromuscular electrical stimulation is effective in assisting grasping, but challenges around patient engagement and control, as well as poor movement regulation due to fatigue and muscle no...
Understanding and predicting others' actions in ecological settings is an important research goal in social neuroscience. Here, we deployed a mobile brain-body imaging (MoBI) methodology to analyze inter-brain communication between professional musicians during a live jazz performance. Specifically, bispectral analysis was conducted to assess the s...
The art of theatre acting involves the recruitment of social and cognitive processes that may provide insights into several functional brain network dynamics, within and between actors and actresses. During rehearsal and performance, actors are required to portray characters by adopting their body language, affective states, and behavior. They assu...
Balance control is an important indicator of mobility and independence in activities of
daily living. How the changes in functional integrity of corticospinal tract due to stroke
affects the maintenance of upright stance remains to be known. We investigated the
changes in functional coupling between the cortex and lower limb muscles during a
challe...
Understanding and predicting others' actions in ecological settings is an important research goal in social neuroscience. Here, we deployed a mobile brain-body imaging (MoBI) methodology to analyze inter-brain communication between professional musicians during a live jazz performance. Specifically, bispectral analysis was conducted to assess the s...
Understanding and predicting others' actions in ecological settings is an important research goal in social neuroscience. Here, we deployed a mobile brain-body imaging (MoBI) methodology to analyze inter-brain communication between professional musicians during a live jazz performance. Specifically, bispectral analysis was conducted to assess the s...
Understanding and predicting others' actions in ecological settings is an important research goal in social neuroscience. Here, we deployed a mobile brain-body imaging (MoBI) methodology to analyze inter-brain communication between professional musicians during a live jazz performance. Specifically, bispectral analysis was conducted to assess the s...
Many individuals with disabling conditions have difficulty with gait and balance control that may result in a fall. Exoskeletons are becoming an increasingly popular technology to aid in walking. Despite being a significant aid in increasing mobility, little attention has been paid to exoskeleton features to mitigate falls. To develop improved exos...
Objective. Transcutaneous spinal cord stimulation (TSS) has been shown to be a promising non-invasive alternative to epidural spinal cord stimulation for improving outcomes of people with spinal cord injury (SCI). However, studies on the effects of TSS on cortical activation are limited. Our objectives were to evaluate the spatiotemporal effects of...
Objective: Falls are a leading cause of death in adults 65 and older. Recent efforts to restore lower-limb function in these populations have seen an increase in the use of wearable robotic systems; however, fall prevention measures in these systems require early detection of balance loss to be effective. Prior studies have investigated whether kin...
This Research Topic is composed of 11 accepted papers: seven dedicated to original research, a perspective, a mini review and two opinion pieces, and are dedicated to various themes and perspectives. These contributions address the multi-faceted nature of non-clinical BCIs, ranging from ethical ramifications of these neurotechnologies, applications...
Editorial to a Frontiers' Research Topic. The Research Topic is composed of 11 accepted papers: seven dedicated to original research, a perspective, a mini review and two opinion pieces, and are dedicated to various themes and perspectives. These contributions address the multi-faceted nature of non-clinical BCIs, ranging from ethical ramifications...
Naturally occurring postural instabilities that occur while standing and walking elicit specific cortical responses in the fronto-central regions (N1 potentials) followed by corrective balance responses to prevent falling. However, no framework could simultaneously track different biomechanical parameters preceding N1s, predict N1s, and assess thei...
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...
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...
Real-time continuous tracking of seizure state is necessary to develop feedback neuromodulation therapy that can prevent or terminate a seizure early. Due to its high temporal resolution, high scalp coverage, and non-invasive applicability, electroencephalography (EEG) is a good candidate for seizure tracking. In this research, we make multiple sei...
Using wearable robotic systems that assist people in their daily activities or provide them with the needed therapeutic support is not new. Some systems are designed around microelectromechanical properties for monitoring or feedback purposes (such as smart systems that monitor heartbeat or muscle activity). Others are designed at the macroscale fo...
Objective. Powered exoskeletons have been used to help persons with gait impairment regain some walking ability. However, little is known about its impact on neuromuscular coordination in persons with stroke. The objective of this study is to investigate how a powered exoskeleton could affect the neuromuscular coordination of persons with post-stro...
Editorial template does not require an abstract and thus one is not included herein. I would like to thank Kara for her valuable assistance in the preparation of this Editorial and accompanying articles.
The control and manipulation of various types of end effectors such as powered exoskeletons, prostheses, and neural cursors by brain-machine interface (BMI) systems has been the target of many research projects. A seamless plug and play interface between any BMI and end effector is desired, wherein similar user's intent cause similar end effectors...
Neurotechnology has traditionally been central to the diagnosis and treatment of neurological disorders. While these devices have initially been utilized in clinical and research settings, recent advancements in neurotechnology have yielded devices that are more portable, user friendly, and less expensive. These improvements allow laypeople to moni...
Wearable robotic devices are being designed to assist the elderly population and other patients with locomotion disabilities. However, wearable robotics increases the risk from falling. Neuroimaging studies have provided evidence for the involvement of frontocentral and parietal cortices in postural control and this opens up the possibility of usin...
Two stages of the creative writing process were characterized through mobile scalp electroencephalography (EEG) in a 16-week creative writing workshop. Portable dry EEG systems (four channels: TP09, AF07, AF08, TP10) with synchronized head acceleration, video recordings, and journal entries, recorded mobile brain-body activity of Spanish heritage s...
Brain-machine interfaces (BMI) based on scalp EEG have the potential to promote cortical plasticity following stroke, which has been shown to improve motor recovery outcomes. However, the efficacy of BMI enabled robotic training for upper-limb recovery is seldom quantified using clinical, EEG-based, and kinematics-based metrics. Further, a movement...
There have been significant advances in the technologies for robot-assisted lower limb rehabilitation in the past decade. However, the development of similar systems for children has been slow despite the fact that children with conditions, such as cerebral palsy, spina bifida, and spinal cord injury (SCI), can benefit greatly from these technologi...
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...
Mobile Brain-Body Imaging (MoBI) technology was used to acquire scalp electroencephalography during rehearsals from three actor-actress dyads, culminating in a public performance at the University of Houston theater. Here, we show how visual representation of two variables that are synchronized in time can improve the annotation of the gathered dat...
Brain Computer Interfaces (BCIs) allow individuals to control devices, machines and prostheses with their thoughts. Most feasibility studies with BCIs have utilized scalp electroencephalography (EEG), due to it being accessible, noninvasive, and portable. While BCIs have been studied with magnetoencephalography (MEG), the modality has limited appli...
Background: Brain-machine interfaces (BMI) based on scalp electroencephalography (EEG) have the potential to promote cortical plasticity following stroke, which has been shown to improve motor recovery outcomes. However, clinical efficacy of BMI-enabled robotic rehabilitation in chronic stroke population is confounded by the spectrum of motor impai...
Previous studies of Brain Computer Interfaces (BCI) based on scalp electroencephalography (EEG) have demonstrated the feasibility of decoding kinematics for lower limb movements during walking. In this computational study, we investigated offline decoding analysis with different models and conditions to assess how they influence the performance and...
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...
In neuroaesthetics, there is a need for expansion in the discussion of building relationships between scientists, artists, academia, and arts institutions. In this chapter, we identify current efforts and opportunities for art–science integration and convergent research, the study of individuality and variance in human behavior, and strategies for...
We introduce a novel convergent research framework based on context-aware, mobile brain–body imaging (MoBI) technology to track, record, and annotate the creative process of an artist as she conceived and created a new composition over a period of several months. We discuss behavioral, technological, scientific, and artistic challenges for the long...
We have developed the first available longitudinal dry-electrode electroencephalography (EEG) dataset, seeking to investigate the brain in action and in context. This project focuses on the validity of the dataset by investigating EEG data during specific tasks in the alpha-band (8-12 Hz) domain, finding discoveries and consistencies with the curre...
Objective. Robotic devices show promise in restoring motor abilities to individuals with upper limb paresis or amputations. However, these systems are still limited in obtaining reliable signals from the human body to effectively control them. We propose that these robotic devices can be controlled through scalp electroencephalography (EEG), a neur...
The reliable classification of Electroencephalography (EEG) signals is a crucial step towards making EEG-controlled non-invasive neuro-exoskeleton rehabilitation a practical reality. EEG signals collected during motor imagery tasks have been proposed to act as a control signal for exoskeleton applications. Here, a Deep Convolutional Neural Network...
Neural signals provide key information for decision-making processes in multiple disciplines including medicine, engineering, and neuroscience. The correct interpretation of these signals, however, requires substantial processing, especially when the signals exhibit low Signal to Noise Ratio (SNR). Electroencephalographic (EEG) signals are consider...
Objective. Accurate implementation of real-time non-invasive brain-machine/computer interfaces (BMI/BCI) requires handling physiological and nonphysiological artifacts associated with the measurement modalities. For example, scalp electroencephalographic (EEG) measurements are often considered prone to excessive motion artifacts and other types of...
Neuroimaging studies have provided evidence for the involvement of frontal and parietal cortices in postural control. However, the specific role of these brain areas for postural control remain to be known. In this study, we investigated the effects of disruptive TMS over supplementary motor areas (SMA) during challenging continuous balance task in...
The intermingling of art and science has often been seen as equivocal, as noncommittal, the art world dubious of the certainty of science and science seeking function in art, but both disciplines very often are in search of the same thing, something we can generalize, something common among us. Neuroscience in particular seeks to give definition to...
We propose a novel experimental paradigm to investigate the human creative process in artistic expression using mobile brain-body imaging (MoBI) technology, which allows the study of brain dynamics in freely behaving individuals performing in natural settings that promote authentic artistic experiences. Our proposed multimodal experimental protocol...
Here, we provide the case study for the development of a low cost, 3D printed, myoelectric prosthetic arm to enable a 7- year old to grasp everyday objects and navigate daily tasks. This project contributes to the increased access to affordable assistive devices for individuals with upper limb differences.
Objective. Understanding neural activity patterns in the developing brain remains one of the grand challenges in neuroscience. Developing neural networks are likely to be endowed with functionally important variability associated with the environmental context, age, gender, and other variables. Therefore, we conducted experiments with typically dev...
Objective. Electroencephalography (EEG) analysis has been an important tool in neuroscience with applications in neuroscience, neural engineering (e.g. Brain–computer interfaces, BCI’s), and even commercial applications. Many of the analytical tools used in EEG studies have used machine learning to uncover relevant information for neural classifica...
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...
Focus:
• Understand the neural representations of gait in
children walking and develop neural interfaces for the
intuitive control of a powered exoskeleton.