31 research outputs found

    Cognitive Assessment and Rehabilitation of subjects with Traumatic Brain Injury

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    This thesis regards the study and the development of new cognitive assessment and rehabilitation techniques of subjects with traumatic brain injury (TBI). In particular, this thesis i) provides an overview about the state of art of this new assessment and rehabilitation technologies, ii) suggests new methods for the assessment and rehabilitation and iii) contributes to the explanation of the neurophysiological mechanism that is involved in a rehabilitation treatment. Some chapters provide useful information to contextualize TBI and its outcome; they describe the methods used for its assessment/rehabilitation. The other chapters illustrate a series of experimental studies conducted in healthy subjects and TBI patients that suggest new approaches to assessment and rehabilitation. The new proposed approaches have in common the use of electroencefalografy (EEG). EEG was used in all the experimental studies with a different purpose, such as diagnostic tool, signal to command a BCI-system, outcome measure to evaluate the effects of a treatment, etc. The main achieved results are about: i) the study and the development of a system for the communication with patients with disorders of consciousness. It was possible to identify a paradigm of reliable activation during two imagery task using EEG signal or EEG and NIRS signal; ii) the study of the effects of a neuromodulation technique (tDCS) on EEG pattern. This topic is of great importance and interest. The emerged founding showed that the tDCS can manipulate the cortical network activity and through the research of optimal stimulation parameters, it is possible move the working point of a neural network and bring it in a condition of maximum learning. In this way could be possible improved the performance of a BCI system or to improve the efficacy of a rehabilitation treatment, like neurofeedback

    Sinc-Windowing and Multiple Correlation Coefficients Improve SSVEP Recognition Based on Canonical Correlation Analysis

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    Canonical Correlation Analysis (CCA) is an increasingly used approach in the field of Steady-State Visually Evoked Potential (SSVEP) recognition. The efficacy of the method has been widely proven, and several variations have been proposed. However, most CCA variations tend to complicate the method, usually requiring additional user training or increasing computational load. Taking simple procedures and low computational costs may be, however, a relevant aspect, especially in view of low-cost and high-portability devices. In addition, it would be desirable that the proposed variations are as general and modular as possible to facilitate the translation of results to different algorithms and setups. In this work, we evaluated the impact of two simple, modular variations of the classical CCA method. The variations involved (i) the number of canonical correlations used for classification and (ii) the inclusion of a prefiltering step by means of sinc-windowing. We tested ten volunteers in a 4-class SSVEP setup. Both variations significantly improved classification accuracy when they were used separately or in conjunction and led to accuracy increments up to 7-8% on average and peak of 25\u201330%. Additionally, variations had no (variation (i)) or minimal (variation (ii)) impact on the number of algorithm steps required for each classification. Given the modular nature of the proposed variations and their positive impact on classification accuracy, they might be easily included in the design of CCA-based algorithms that are even different from ours

    CENTRE OF MASS TRAJECTORY IN SNOWBOARD GIANT SLALOM USING INERTIAL SENSORS: LABORATORY AND IN-FIELD PRELIMINARY EVALUATION

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    The purpose of the present study was to evaluate the reconstruction accuracy of the centre of mass during snowboard giant slalom using inertial sensors (Opal, APDM, 128 Hz). Two approaches were implemented and tested: i) a multi-segment model using 7 inertial sensors on the trunk, the pelvis, the thighs, the shanks, and the board; and ii) a double integration of the acceleration at L5 level measured with one inertial sensor. The accuracy of the algorithms was verified in two laboratory conditions: a) the multi-segment model approach was tested indoor during controlled movements using stereo-photogrammetry as gold standard, and b) the double integration of acceleration approach was tested outdoor in simulated movements on a longboard using GPS as gold standard. Successively, to verify the application in real conditions, an in-field acquisition of a forerunner athlete during a snowboard world cup competition was performed. The position of the centre of mass estimated indoor with multi-segmental model approach reported in the local reference frame of the board showed high correlation with respect to stereo-photogrammetry (r=0.87) and a RMS error of 3.8 [%] expressed as percentage of the range of motion during the trial (1.32m). For the simulated movements test in outdoor conditions on the longboard applying the double integration approach, high correlation was found with respect to the GPS data (r=0.95) on the trajectory but , for the 4 turns trial, a RMS difference on the distance equal to 15.3 [%] expressed as percentage of the whole distance covered (46m). Finally, the in-field acquisition showed how using inertial sensors is a viable option for collecting centre of mass data during training session useful for coaches and athletes. The approach using one sensors at L5 level showed low level of accuracy with respect to the one using a multi-segment model. Further developments should be performed in the direction of a better estimation of the orientation of the inertial sensors and of the boundary conditions for the integration algorithm

    Transcranial direct current stimulation and power spectral parameters: a tDCS/EEG co-registration study

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    Transcranial direct current stimulation (tDCS) delivers low electric currents to the brain through the scalp. Constant electric currents induce shifts in neuronal membrane excitability, resulting in secondary changes in cortical activity. Concomitant electroencephalography (EEG) monitoring during tDCS can provide valuable information on the tDCS mechanisms of action. This study examined the effects of anodal tDCS on spontaneous cortical activity in a resting brain to disclose possible modulation of spontaneous oscillatory brain activity. EEG activity was measured in ten healthy subjects during and after a session of anodal stimulation of the postero-parietal cortex to detect the tDCS-induced alterations. Changes in the theta, alpha, beta, and gamma power bands were investigated. Three main findings emerged: (1) an increase in theta band activity during the first minutes of stimulation; (2) an increase in alpha and beta power during and after stimulation; (3) a widespread activation in several brain regions

    Single-session tDCS over the dominant hemisphere affects contralateral spectral EEG power, but does not enhance neurofeedback-guided event-related desynchronization of the non-dominant hemisphere\u2019s sensorimotor rhythm

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    Background and objective Transcranial direct current stimulation (tDCS) and neurofeedback-guided motor imagery (MI) have attracted considerable interest in neurorehabilitation, given their ability to influence neuroplasticity. As tDCS has been shown to modulate event-related desynchronization (ERD), the neural signature of motor imagery detected for neurofeedback, a combination of the techniques was recently proposed. One limitation of this approach is that the area targeted for stimulation is the same from which the signal for neurofeedback is acquired. As tDCS may interfere with proximal electroencephalographic (EEG) electrodes, in this study our aim was to test whether contralateral tDCS could have interhemispheric effects on the spectral power of the unstimulated hemisphere, possibly mediated by transcallosal connection, and whether such effects could be used to enhance ERD magnitudes. A contralateral stimulation approach would indeed facilitate co-registration, as the stimulation electrode would be far from the recording sites. Methods Twenty right-handed healthy volunteers (aged 21 to 32) participated in the study: ten assigned to cathodal, ten to anodal versus sham stimulation. We applied stimulation over the dominant (left) hemisphere, and assessed ERD and spectral power over the non-dominant (right) hemisphere. The effect of tDCS was evaluated over time. Spectral power was assessed in theta, alpha and beta bands, under both rest and MI conditions, while ERD was evaluated in alpha and beta bands. Results Two main findings emerged: (1) contralateral alpha-ERD was reduced after anodal (p = 0.0147), but not enhanced after cathodal tDCS; (2) both stimulations had remote effects on the spectral power of the contralateral hemisphere, particularly in theta and alpha (significant differences in the topographical t-value maps). Conclusion The absence of contralateral cathodal ERD enhancement suggests that the protocol is not applicable in the context of MI training. Nevertheless, ERD results of anodal and spectral power results of both stimulations complement recent findings on the distant tDCS effects between functionally related areas

    Data from: Single-session tDCS over the dominant hemisphere affects contralateral spectral EEG power, but does not enhance neurofeedback-guided event-related desynchronization of the non-dominant hemisphere's sensorimotor rhythm

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    Background and objective: Transcranial direct current stimulation (tDCS) and neurofeedback-guided motor imagery (MI) have attracted considerable interest in neurorehabilitation, given their ability to influence neuroplasticity. As tDCS has been shown to modulate event-related desynchronization (ERD), the neural signature of motor imagery detected for neurofeedback, a combination of the techniques was recently proposed. One limitation of this approach is that the area targeted for stimulation is the same from which the signal for neurofeedback is acquired. As tDCS may interfere with proximal electroencephalographic (EEG) electrodes, in this study our aim was to test whether contralateral tDCS could have interhemispheric effects on the spectral power of the unstimulated hemisphere, possibly mediated by transcallosal connection, and whether such effects could be used to enhance ERD magnitudes. A contralateral stimulation approach would indeed facilitate co-registration, as the stimulation electrode would be far from the recording sites. Methods: Twenty right-handed healthy volunteers (aged 21 to 32) participated in the study: ten assigned to cathodal, ten to anodal versus sham stimulation. We applied stimulation over the dominant (left) hemisphere, and assessed ERD and spectral power over the non-dominant (right) hemisphere. The effect of tDCS was evaluated over time. Spectral power was assessed in theta, alpha and beta bands, under both rest and MI conditions, while ERD was evaluated in alpha and beta bands. Results: Two main findings emerged: (1) contralateral alpha-ERD was reduced after anodal (p = 0.0147), but not enhanced after cathodal tDCS; (2) both stimulations had remote effects on the spectral power of the contralateral hemisphere, particularly in theta and alpha (significant differences in the topographical t-value maps). Conclusion: The absence of contralateral cathodal ERD enhancement suggests that the protocol is not applicable in the context of MI training. Nevertheless, ERD results of anodal and spectral power results of both stimulations complement recent findings on the distant tDCS effects between functionally related areas

    EEG-Based BCI System Using Adaptive Features Extraction and Classification Procedures

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    Motor imagery is a common control strategy in EEG-based brain-computer interfaces (BCIs). However, voluntary control of sensorimotor (SMR) rhythms by imagining a movement can be skilful and unintuitive and usually requires a varying amount of user training. To boost the training process, a whole class of BCI systems have been proposed, providing feedback as early as possible while continuously adapting the underlying classifier model. The present work describes a cue-paced, EEG-based BCI system using motor imagery that falls within the category of the previously mentioned ones. Specifically, our adaptive strategy includes a simple scheme based on a common spatial pattern (CSP) method and support vector machine (SVM) classification. The system's efficacy was proved by online testing on 10 healthy participants. In addition, we suggest some features we implemented to improve a system's "flexibility" and "customizability," namely, (i) a flexible training session, (ii) an unbalancing in the training conditions, and (iii) the use of adaptive thresholds when giving feedback

    Magnetometer Calibration and Field Mapping through Thin Plate Splines

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    While the undisturbed Earth’s magnetic field represents a fundamental information source for orientation purposes, magnetic distortions have been mostly considered as a source of error. However, when distortions are temporally stable and spatially distinctive, they could provide a unique magnetic landscape that can be used in different applications, from indoor localization to sensor fusion algorithms for attitude estimation. The main purpose of this work, therefore, is to present a method to characterize the 3D magnetic vector in every point of the measurement volume. The possibility of describing the 3D magnetic field map through Thin Plate Splines (TPS) interpolation is investigated and demonstrated. An algorithm for the simultaneous estimation of the parameters related to magnetometer calibration and those describing the magnetic map, is proposed and tested on both simulated and real data. Results demonstrate that an accurate description of the local magnetic field using TPS interpolation is possible. The proposed procedure leads to errors in the estimation of the local magnetic direction with a standard deviation lower than 1 degree. Magnetometer calibration and magnetic field mapping could be integrated into different algorithms, for example to improve attitude estimation in highly distorted environments or as an aid to indoor localization
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