1,166 research outputs found

    Vibrotactile Feedback for Brain-Computer Interface Operation

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    To be correctly mastered, brain-computer interfaces (BCIs) need an uninterrupted flow of feedback to the user. This feedback is usually delivered through the visual channel. Our aim was to explore the benefits of vibrotactile feedback during users' training and control of EEG-based BCI applications. A protocol for delivering vibrotactile feedback, including specific hardware and software arrangements, was specified. In three studies with 33 subjects (including 3 with spinal cord injury), we compared vibrotactile and visual feedback, addressing: (I) the feasibility of subjects' training to master their EEG rhythms using tactile feedback; (II) the compatibility of this form of feedback in presence of a visual distracter; (III) the performance in presence of a complex visual task on the same (visual) or different (tactile) sensory channel. The stimulation protocol we developed supports a general usage of the tactors; preliminary experimentations. All studies indicated that the vibrotactile channel can function as a valuable feedback modality with reliability comparable to the classical visual feedback. Advantages of using a vibrotactile feedback emerged when the visual channel was highly loaded by a complex task. In all experiments, vibrotactile feedback felt, after some training, more natural for both controls and SCI users

    Vibration Propagation on the Skin of the Arm

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    Vibrotactile interfaces are an inexpensive and non-invasive way to provide performance feedback to body-machine interface users. Interfaces for the upper extremity have utilized a multi-channel approach using an array of vibration motors placed on the upper extremity. However, for successful perception of multi-channel vibrotactile feedback on the arm, we need to account for vibration propagation across the skin. If two stimuli are delivered within a small distance, mechanical propagation of vibration can lead to inaccurate perception of the distinct vibrotactile stimuli. This study sought to characterize vibration propagation across the hairy skin of the forearm. We characterized vibration propagation by measuring accelerations at various distances from a source vibration of variable intensities (100–240 Hz). Our results showed that acceleration from the source vibration was present at a distance of 4 cm at intensities \u3e150 Hz. At distances greater than 8 cm from the source, accelerations were reduced to values substantially below vibrotactile discrimination thresholds for all vibration intensities. We conclude that in future applications of vibrotactile interfaces, stimulation sites should be separated by a distance of at least 8 cm to avoid potential interference in vibration perception caused by propagating vibrations

    A brain-computer interface with vibrotactile biofeedback for haptic information

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    <p>Abstract</p> <p>Background</p> <p>It has been suggested that Brain-Computer Interfaces (BCI) may one day be suitable for controlling a neuroprosthesis. For closed-loop operation of BCI, a tactile feedback channel that is compatible with neuroprosthetic applications is desired. Operation of an EEG-based BCI using only <it>vibrotactile feedback</it>, a commonly used method to convey haptic senses of contact and pressure, is demonstrated with a high level of accuracy.</p> <p>Methods</p> <p>A Mu-rhythm based BCI using a motor imagery paradigm was used to control the position of a virtual cursor. The cursor position was shown visually as well as transmitted haptically by modulating the intensity of a vibrotactile stimulus to the upper limb. A total of six subjects operated the BCI in a two-stage targeting task, receiving only vibrotactile biofeedback of performance. The location of the vibration was also systematically varied between the left and right arms to investigate location-dependent effects on performance.</p> <p>Results and Conclusion</p> <p>Subjects are able to control the BCI using only vibrotactile feedback with an average accuracy of 56% and as high as 72%. These accuracies are significantly higher than the 15% predicted by random chance if the subject had no voluntary control of their Mu-rhythm. The results of this study demonstrate that vibrotactile feedback is an effective biofeedback modality to operate a BCI using motor imagery. In addition, the study shows that placement of the vibrotactile stimulation on the biceps ipsilateral or contralateral to the motor imagery introduces a significant bias in the BCI accuracy. This bias is consistent with a drop in performance generated by stimulation of the contralateral limb. Users demonstrated the capability to overcome this bias with training.</p

    A robot hand testbed designed for enhancing embodiment and functional neurorehabilitation of body schema in subjects with upper limb impairment or loss.

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    Many upper limb amputees experience an incessant, post-amputation "phantom limb pain" and report that their missing limbs feel paralyzed in an uncomfortable posture. One hypothesis is that efferent commands no longer generate expected afferent signals, such as proprioceptive feedback from changes in limb configuration, and that the mismatch of motor commands and visual feedback is interpreted as pain. Non-invasive therapeutic techniques for treating phantom limb pain, such as mirror visual feedback (MVF), rely on visualizations of postural changes. Advances in neural interfaces for artificial sensory feedback now make it possible to combine MVF with a high-tech "rubber hand" illusion, in which subjects develop a sense of embodiment with a fake hand when subjected to congruent visual and somatosensory feedback. We discuss clinical benefits that could arise from the confluence of known concepts such as MVF and the rubber hand illusion, and new technologies such as neural interfaces for sensory feedback and highly sensorized robot hand testbeds, such as the "BairClaw" presented here. Our multi-articulating, anthropomorphic robot testbed can be used to study proprioceptive and tactile sensory stimuli during physical finger-object interactions. Conceived for artificial grasp, manipulation, and haptic exploration, the BairClaw could also be used for future studies on the neurorehabilitation of somatosensory disorders due to upper limb impairment or loss. A remote actuation system enables the modular control of tendon-driven hands. The artificial proprioception system enables direct measurement of joint angles and tendon tensions while temperature, vibration, and skin deformation are provided by a multimodal tactile sensor. The provision of multimodal sensory feedback that is spatiotemporally consistent with commanded actions could lead to benefits such as reduced phantom limb pain, and increased prosthesis use due to improved functionality and reduced cognitive burden

    Thought-controlled games with brain-computer interfaces

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    Nowadays, EEG based BCI systems are starting to gain ground in games for health research. With reduced costs and promising an innovative and exciting new interaction paradigm, attracted developers and researchers to use them on video games for serious applications. However, with researchers focusing mostly on the signal processing part, the interaction aspect of the BCIs has been neglected. A gap between classification performance and online control quality for BCI based systems has been created by this research disparity, resulting in suboptimal interactions that lead to user fatigue and loss of motivation over time. Motor-Imagery (MI) based BCIs interaction paradigms can provide an alternative way to overcome motor-related disabilities, and is being deployed in the health environment to promote the functional and structural plasticity of the brain. A BCI system in a neurorehabilitation environment, should not only have a high classification performance, but should also provoke a high level of engagement and sense of control to the user, for it to be advantageous. It should also maximize the level of control on user’s actions, while not requiring them to be subject to long training periods on each specific BCI system. This thesis has two main contributions, the Adaptive Performance Engine, a system we developed that can provide up to 20% improvement to user specific performance, and NeuRow, an immersive Virtual Reality environment for motor neurorehabilitation that consists of a closed neurofeedback interaction loop based on MI and multimodal feedback while using a state-of-the-art Head Mounted Display.Hoje em dia, os sistemas BCI baseados em EEG estão a começar a ganhar terreno em jogos relacionados com a saúde. Com custos reduzidos e prometendo um novo e inovador paradigma de interação, atraiu programadores e investigadores para usá-los em vídeo jogos para aplicações sérias. No entanto, com os investigadores focados principalmente na parte do processamento de sinal, o aspeto de interação dos BCI foi negligenciado. Um fosso entre o desempenho da classificação e a qualidade do controle on-line para sistemas baseados em BCI foi criado por esta disparidade de pesquisa, resultando em interações subótimas que levam à fadiga do usuário e à perda de motivação ao longo do tempo. Os paradigmas de interação BCI baseados em imagética motora (IM) podem fornecer uma maneira alternativa de superar incapacidades motoras, e estão sendo implementados no sector da saúde para promover plasticidade cerebral funcional e estrutural. Um sistema BCI usado num ambiente de neuro-reabilitação, para que seja vantajoso, não só deve ter um alto desempenho de classificação, mas também deve promover um elevado nível de envolvimento e sensação de controlo ao utilizador. Também deve maximizar o nível de controlo nas ações do utilizador, sem exigir que sejam submetidos a longos períodos de treino em cada sistema BCI específico. Esta tese tem duas contribuições principais, o Adaptive Performance Engine, um sistema que desenvolvemos e que pode fornecer até 20% de melhoria para o desempenho específico do usuário, e NeuRow, um ambiente imersivo de Realidade Virtual para neuro-reabilitação motora, que consiste num circuito fechado de interação de neuro-feedback baseado em IM e feedback multimodal e usando um Head Mounted Display de última geração
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