1
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Mustile M, Kourtis D, Edwards MG, Donaldson DI, Ietswaart M. Neural correlates of motor imagery and execution in real-world dynamic behavior: evidence for similarities and differences. Front Hum Neurosci 2024; 18:1412307. [PMID: 38974480 PMCID: PMC11224467 DOI: 10.3389/fnhum.2024.1412307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Accepted: 05/20/2024] [Indexed: 07/09/2024] Open
Abstract
A large body of evidence shows that motor imagery and action execution behaviors result from overlapping neural substrates, even in the absence of overt movement during motor imagery. To date it is unclear how neural activations in motor imagery and execution compare for naturalistic whole-body movements, such as walking. Neuroimaging studies have not directly compared imagery and execution during dynamic walking movements. Here we recorded brain activation with mobile EEG during walking compared to during imagery of walking, with mental counting as a control condition. We asked 24 healthy participants to either walk six steps on a path, imagine taking six steps, or mentally count from one to six. We found beta and alpha power modulation during motor imagery resembling action execution patterns; a correspondence not found performing the control task of mental counting. Neural overlap occurred early in the execution and imagery walking actions, suggesting activation of shared action representations. Remarkably, a distinctive walking-related beta rebound occurred both during action execution and imagery at the end of the action suggesting that, like actual walking, motor imagery involves resetting or inhibition of motor processes. However, we also found that motor imagery elicits a distinct pattern of more distributed beta activity, especially at the beginning of the task. These results indicate that motor imagery and execution of naturalistic walking involve shared motor-cognitive activations, but that motor imagery requires additional cortical resources.
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Affiliation(s)
- Magda Mustile
- Department of Psychology, Faculty of Natural Sciences, University of Stirling, Stirling, United Kingdom
- The Psychological Sciences Research Institute, University of Louvain, Louvain-la-Neuve, Belgium
| | - Dimitrios Kourtis
- Department of Psychology, Faculty of Natural Sciences, University of Stirling, Stirling, United Kingdom
| | - Martin G. Edwards
- The Psychological Sciences Research Institute, University of Louvain, Louvain-la-Neuve, Belgium
| | - David I. Donaldson
- School of Psychology and Neuroscience, University of St Andrews, St. Andrews, United Kingdom
| | - Magdalena Ietswaart
- Department of Psychology, Faculty of Natural Sciences, University of Stirling, Stirling, United Kingdom
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2
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Ladouce S, Pietzker M, Manzey D, Dehais F. Evaluation of a headphones-fitted EEG system for the recording of auditory evoked potentials and mental workload assessment. Behav Brain Res 2024; 460:114827. [PMID: 38128886 DOI: 10.1016/j.bbr.2023.114827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 11/23/2023] [Accepted: 12/18/2023] [Indexed: 12/23/2023]
Abstract
Advancements in portable neuroimaging technologies open up new opportunities to gain insight into the neural dynamics and cognitive processes underlying day-to-day behaviors. In this study, we evaluated the relevance of a headphone- mounted electroencephalogram (EEG) system for monitoring mental workload. The participants (N = 12) were instructed to pay attention to auditory alarms presented sporadically while performing the Multi-Attribute Task Battery (MATB) whose difficulty was staged across three conditions to manipulate mental workload. The P300 Event-Related Potentials (ERP) elicited by the presentation of auditory alarms were used as probes of attentional resources available. The amplitude and latency of P300 ERPs were compared across experimental conditions. Our findings indicate that the P300 ERP component can be captured using a headphone-mounted EEG system. Moreover, neural responses to alarm could be used to classify mental workload with high accuracy (over 80%) at a single-trial level. Our analyses indicated that the signal-to-noise ratio acquired by the sponge-based sensors remained stable throughout the recordings. These results highlight the potential of portable neuroimaging technology for the development of neuroassistive applications while underscoring the current limitations and challenges associated with the integration of EEG sensors in everyday-life wearable technologies. Overall, our study contributes to the growing body of research exploring the feasibility and validity of wearable neuroimaging technologies for the study of human cognition and behavior in real-world settings.
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Affiliation(s)
- Simon Ladouce
- Human Factors and Neuroergonomics, ISAE-SUPAERO, 10 Av. Edouard Belin, Toulouse 31400, Haute-Garonne, France.
| | - Max Pietzker
- Department of Psychology and Ergonomics, Technical University Berlin, Strafte des 17.Juni 135, 10623 Berlin, Berlin, 10623 Berlin, Germany
| | - Dietrich Manzey
- Department of Psychology and Ergonomics, Technical University Berlin, Strafte des 17.Juni 135, 10623 Berlin, Berlin, 10623 Berlin, Germany
| | - Frederic Dehais
- Human Factors and Neuroergonomics, ISAE-SUPAERO, 10 Av. Edouard Belin, Toulouse 31400, Haute-Garonne, France; School of Biomedical Engineering, Science Health Systems, Drexel University, 3141 Chestnut St, Philadelphia 19104, PA, United States
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3
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Wu Z, Tang X, Wu J, Huang J, Shen J, Hong H. Portable deep-learning decoder for motor imaginary EEG signals based on a novel compact convolutional neural network incorporating spatial-attention mechanism. Med Biol Eng Comput 2023; 61:2391-2404. [PMID: 37095297 DOI: 10.1007/s11517-023-02840-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 04/13/2023] [Indexed: 04/26/2023]
Abstract
Due to high computational requirements, deep-learning decoders for motor imaginary (MI) electroencephalography (EEG) signals are usually implemented on bulky and heavy computing devices that are inconvenient for physical actions. To date, the application of deep-learning techniques in independent portable brain-computer-interface (BCI) devices has not been extensively explored. In this study, we proposed a high-accuracy MI EEG decoder by incorporating spatial-attention mechanism into convolution neural network (CNN), and deployed it on fully integrated single-chip microcontroller unit (MCU). After the CNN model was trained on workstation computer using GigaDB MI datasets (52 subjects), its parameters were then extracted and converted to build deep-learning architecture interpreter on MCU. For comparison, EEG-Inception model was also trained using the same dataset, and was deployed on MCU. The results indicate that our deep-learning model can independently decode imaginary left-/right-hand motions. The mean accuracy of the proposed compact CNN reaches 96.75 ± 2.41% (8 channels: Frontocentral3 (FC3), FC4, Central1 (C1), C2, Central-Parietal1 (CP1), CP2, C3, and C4), versus 76.96 ± 19.08% of EEG-Inception (6 channels: FC3, FC4, C1, C2, CP1, and CP2). To the best of our knowledge, this is the first portable deep-learning decoder for MI EEG signals. The findings demonstrate high-accuracy deep-learning decoding of MI EEG in a portable mode, which has great implications for hand-disabled patients. Our portable system can be used for developing artificial-intelligent wearable BCI devices, as it is less computationally expensive and convenient for real-life application.
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Affiliation(s)
- Zhanxiong Wu
- School of Electronic Information, Hangzhou Dianzi University, Hangzhou, 310018, Zhejiang, China.
| | - Xudong Tang
- School of Electronic Information, Hangzhou Dianzi University, Hangzhou, 310018, Zhejiang, China
| | - Jinhui Wu
- School of Electronic Information, Hangzhou Dianzi University, Hangzhou, 310018, Zhejiang, China
| | - Jiye Huang
- School of Electronic Information, Hangzhou Dianzi University, Hangzhou, 310018, Zhejiang, China
| | - Jian Shen
- Neurosurgery Department, The First Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, 310003, Zhejiang, China
| | - Hui Hong
- School of Electronic Information, Hangzhou Dianzi University, Hangzhou, 310018, Zhejiang, China
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4
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Schmidt-Kassow M, Kaiser J. The brain in motion-cognitive effects of simultaneous motor activity. Front Integr Neurosci 2023; 17:1127310. [PMID: 37304529 PMCID: PMC10248180 DOI: 10.3389/fnint.2023.1127310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 05/08/2023] [Indexed: 06/13/2023] Open
Abstract
During the last 30 years, a large number of behavioral studies have investigated the effect of simultaneous exercise on cognitive functions. The heterogeneity of the results has been attributed to different parameters, such as intensity or modality of physical activity, and the investigated cognitive processes. More recent methodological improvements have enabled to record electroencephalography (EEG) during physical exercise. EEG studies combining cognitive tasks with exercise have described predominantly detrimental effects on cognitive processes and EEG parameters. However, differences in the underlying rationale and the design of EEG versus behavioral studies make direct comparisons between both types of studies difficult. In this narrative review of dual-task experiments we evaluated behavioral and EEG studies and discuss possible explanations for the heterogeneity of results and for the discrepancy between behavioral and EEG studies. Furthermore, we provide a proposal for future EEG studies on simultaneous motion to be a useful complement to behavioral studies. A crucial factor might be to find for each cognitive function the motor activity that matches this function in terms of attentional focus. This hypothesis should be investigated systematically in future studies.
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Affiliation(s)
- Maren Schmidt-Kassow
- Institute of Medical Psychology, Goethe University, Frankfurt, Germany
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University, Frankfurt, Germany
| | - Jochen Kaiser
- Institute of Medical Psychology, Goethe University, Frankfurt, Germany
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5
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Russo C, Senese VP. Functional near-infrared spectroscopy is a useful tool for multi-perspective psychobiological study of neurophysiological correlates of parenting behaviour. Eur J Neurosci 2023; 57:258-284. [PMID: 36485015 DOI: 10.1111/ejn.15890] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 12/02/2022] [Accepted: 12/08/2022] [Indexed: 12/13/2022]
Abstract
The quality of the relationship between caregiver and child has long-term effects on the cognitive and socio-emotional development of children. A process involved in human parenting is the bio-behavioural synchrony that occurs between the partners in the relationship during interaction. Through interaction, bio-behavioural synchronicity allows the adaptation of the physiological systems of the parent to those of the child and promotes the positive development and modelling of the child's social brain. The role of bio-behavioural synchrony in building social bonds could be investigated using functional near-infrared spectroscopy (fNIRS). In this paper we have (a) highlighted the importance of the quality of the caregiver-child relationship for the child's cognitive and socio-emotional development, as well as the relevance of infantile stimuli in the activation of parenting behaviour; (b) discussed the tools used in the study of the neurophysiological substrates of the parental response; (c) proposed fNIRS as a particularly suitable tool for the study of parental responses; and (d) underlined the need for a multi-systemic psychobiological approach to understand the mechanisms that regulate caregiver-child interactions and their bio-behavioural synchrony. We propose to adopt a multi-system psychobiological approach to the study of parental behaviour and social interaction.
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Affiliation(s)
- Carmela Russo
- Psychometric Laboratory, Department of Psychology, University of Campania "Luigi Vanvitelli", Caserta, Italy
| | - Vincenzo Paolo Senese
- Psychometric Laboratory, Department of Psychology, University of Campania "Luigi Vanvitelli", Caserta, Italy
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6
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Rominger C, Gubler DA, Makowski LM, Troche SJ. More creative ideas are associated with increased right posterior power and frontal-parietal/occipital coupling in the upper alpha band: A within-subjects study. Int J Psychophysiol 2022; 181:95-103. [PMID: 36057407 DOI: 10.1016/j.ijpsycho.2022.08.012] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 08/29/2022] [Accepted: 08/30/2022] [Indexed: 11/26/2022]
Abstract
The neurophysiological investigation of creative idea generation is a growing research area. EEG studies congruently reported the sensitivity of upper alpha power (10-12 Hz) for the creative ideation process and its outcome. However, the majority of studies were between-subject design studies and research directly comparing the neurophysiological activation pattern when generating more and less creative ideas within a person are rare. Therefore, the present study was specifically focused on investigating brain activation patterns associated with the generation of more vs. less creative ideas. We applied an alternate uses task (AU-task; i.e., finding original uses for everyday objects such as a brick) in a sample of 74 participants and recorded the brain activation during the AU-task and reference period. A portable EEG system with 21 dry electrodes arranged in the international 10-20 system and linked ear as reference was used. We found a higher increase of upper alpha power during creative ideation (relative to reference period, i.e., task-related power, TRP) over right posterior sites when people generated more compared to less creative ideas. This was accompanied by an increase of functional coupling (i.e., task-related coherence increase) between frontal and parietal/occipital sites, which suggests higher internal attention and more control over sensory processes. Taken together, these findings complement the existing creativity research literature and indicate the importance of alpha power for the creative ideation process also within people.
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Affiliation(s)
| | | | - Lisa M Makowski
- Department of Psychology, University of Bern, Bern, Switzerland
| | - Stefan J Troche
- Department of Psychology, University of Bern, Bern, Switzerland
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7
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Chiu NT, Huwiler S, Ferster ML, Karlen W, Wu HT, Lustenberger C. Get rid of the beat in mobile EEG applications: A framework towards automated cardiogenic artifact detection and removal in single-channel EEG. Biomed Signal Process Control 2022. [DOI: 10.1016/j.bspc.2021.103220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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8
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Teng CL, Zhang YY, Wang W, Luo YY, Wang G, Xu J. A Novel Method Based on Combination of Independent Component Analysis and Ensemble Empirical Mode Decomposition for Removing Electrooculogram Artifacts From Multichannel Electroencephalogram Signals. Front Neurosci 2021; 15:729403. [PMID: 34707475 PMCID: PMC8542780 DOI: 10.3389/fnins.2021.729403] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 09/01/2021] [Indexed: 12/03/2022] Open
Abstract
Electrooculogram (EOG) is one of common artifacts in recorded electroencephalogram (EEG) signals. Many existing methods including independent component analysis (ICA) and wavelet transform were applied to eliminate EOG artifacts but ignored the possible impact of the nature of EEG signal. Therefore, the removal of EOG artifacts still faces a major challenge in EEG research. In this paper, the ensemble empirical mode decomposition (EEMD) and ICA algorithms were combined to propose a novel EEMD-based ICA method (EICA) for removing EOG artifacts from multichannel EEG signals. First, the ICA method was used to decompose original EEG signals into multiple independent components (ICs), and the EOG-related ICs were automatically identified through the kurtosis method. Then, by performing the EEMD algorithm on EOG-related ICs, the intrinsic mode functions (IMFs) linked to EOG were discriminated and eliminated. Finally, artifact-free IMFs were projected to obtain the ICs without EOG artifacts, and the clean EEG signals were ultimately reconstructed by the inversion of ICA. Both EOGs correction from simulated EEG signals and real EEG data were studied, which verified that the proposed method could achieve an improved performance in EOG artifacts rejection. By comparing with other existing approaches, the EICA obtained the optimal performance with the highest increase in signal-to-noise ratio and decrease in root mean square error and correlation coefficient after EOG artifacts removal, which demonstrated that the proposed method could more effectively eliminate blink artifacts from multichannel EEG signals with less error influence. This study provided a novel promising method to eliminate EOG artifacts with high performance, which is of great importance for EEG signals processing and analysis.
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Affiliation(s)
- Chao-Lin Teng
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.,The Key Laboratory of Neuro-informatics and Rehabilitation Engineering of Ministry of Civil Affairs, Xi'an, China.,National Engineering Research Center for Healthcare Devices, Guangzhou, China
| | - Yi-Yang Zhang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.,The Key Laboratory of Neuro-informatics and Rehabilitation Engineering of Ministry of Civil Affairs, Xi'an, China.,National Engineering Research Center for Healthcare Devices, Guangzhou, China
| | - Wei Wang
- Department of Psychiatry, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China
| | - Yuan-Yuan Luo
- Department of Psychology, Xi'an Mental Health Center, Xi'an, China
| | - Gang Wang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.,The Key Laboratory of Neuro-informatics and Rehabilitation Engineering of Ministry of Civil Affairs, Xi'an, China.,National Engineering Research Center for Healthcare Devices, Guangzhou, China
| | - Jin Xu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.,The Key Laboratory of Neuro-informatics and Rehabilitation Engineering of Ministry of Civil Affairs, Xi'an, China.,National Engineering Research Center for Healthcare Devices, Guangzhou, China
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9
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Abstract
Abstract
Neurofeedback (NF) is a versatile non-invasive neuromodulation technique. In combination with motor imagery (MI), NF has considerable potential for enhancing motor performance or supplementing motor rehabilitation. However, not all users achieve reliable NF control. While research has focused on various brain signal properties and the optimisation of signal processing to solve this issue, the impact of context, i.e. the conditions in which NF motor tasks occur, is comparatively unknown. We review current research on the impact of context on MI NF and related motor domains. We identify long-term factors that act at the level of the individual or of the intervention, and short-term factors, with levels before/after and during a session. The reviewed literature indicates that context plays a significant role. We propose considering context factors as well as within-level and across-level interactions when studying MI NF.
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10
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Cao L, Chen X, Haendel BF. Overground Walking Decreases Alpha Activity and Entrains Eye Movements in Humans. Front Hum Neurosci 2021; 14:561755. [PMID: 33414709 PMCID: PMC7782973 DOI: 10.3389/fnhum.2020.561755] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 12/02/2020] [Indexed: 01/25/2023] Open
Abstract
Experiments in animal models have shown that running increases neuronal activity in early visual areas in light as well as in darkness. This suggests that visual processing is influenced by locomotion independent of visual input. Combining mobile electroencephalography, motion- and eye-tracking, we investigated the influence of overground free walking on cortical alpha activity (~10 Hz) and eye movements in healthy humans. Alpha activity has been considered a valuable marker of inhibition of sensory processing and shown to negatively correlate with neuronal firing rates. We found that walking led to a decrease in alpha activity over occipital cortex compared to standing. This decrease was present during walking in darkness as well as during light. Importantly, eye movements could not explain the change in alpha activity. Nevertheless, we found that walking and eye related movements were linked. While the blink rate increased with increasing walking speed independent of light or darkness, saccade rate was only significantly linked to walking speed in the light. Pupil size, on the other hand, was larger during darkness than during light, but only showed a modulation by walking in darkness. Analyzing the effect of walking with respect to the stride cycle, we further found that blinks and saccades preferentially occurred during the double support phase of walking. Alpha power, as shown previously, was lower during the swing phase than during the double support phase. We however could exclude the possibility that the alpha modulation was introduced by a walking movement induced change in electrode impedance. Overall, our work indicates that the human visual system is influenced by the current locomotion state of the body. This influence affects eye movement pattern as well as neuronal activity in sensory areas and might form part of an implicit strategy to optimally extract sensory information during locomotion.
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Affiliation(s)
- Liyu Cao
- Department of Psychology (III), Julius-Maximilians-Universität Würzburg, Würzburg, Germany
| | - Xinyu Chen
- Department of Psychology (III), Julius-Maximilians-Universität Würzburg, Würzburg, Germany
| | - Barbara F Haendel
- Department of Psychology (III), Julius-Maximilians-Universität Würzburg, Würzburg, Germany
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11
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Exploring the Limitations of Event-Related Potential Measures in Moving Subjects: Pilot Studies of Four Different Technical Modifications in Ergometer Rowing. SENSORS 2020; 20:s20195618. [PMID: 33019577 PMCID: PMC7583081 DOI: 10.3390/s20195618] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 09/22/2020] [Accepted: 09/29/2020] [Indexed: 12/31/2022]
Abstract
Measuring brain activity in moving subjects is of great importance for investigating human behavior in ecological settings. For this purpose, EEG measures are applicable; however, technical modifications are required to reduce the typical massive movement artefacts. Four different approaches to measure EEG/ERPs during rowing were tested: (i) a purpose-built head-mounted preamplifier, (ii) a laboratory system with active electrodes, and a wireless headset combined with (iii) passive or (iv) active electrodes. A standard visual oddball task revealed very similar (within subjects) visual evoked potentials for rowing and rest (without movement). The small intraindividual differences between rowing and rest, in comparison to the typically larger interindividual differences in the ERP waveforms, revealed that ERPs can be measured reliably even in an athletic movement such as rowing. On the other hand, the expected modulation of the motor-related activity by force output was largely affected by movement artefacts. Therefore, for a successful application of ERP measures in movement research, further developments to differentiate between movement-related neuronal activity and movement-related artefacts are required. However, activities with small magnitudes related to motor learning and motor control may be difficult to detect because they are superimposed by the very large motor potential, which increases with force output.
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12
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Abiri R, Borhani S, Kilmarx J, Esterwood C, Jiang Y, Zhao X. A Usability Study of Low-cost Wireless Brain-Computer Interface for Cursor Control Using Online Linear Model. IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS 2020; 50:287-297. [PMID: 33777542 PMCID: PMC7990128 DOI: 10.1109/thms.2020.2983848] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
Computer cursor control using electroencephalogram (EEG) signals is a common and well-studied brain-computer interface (BCI). The emphasis of the literature has been primarily on evaluation of the objective measures of assistive BCIs such as accuracy of the neural decoder whereas the subjective measures such as user's satisfaction play an essential role for the overall success of a BCI. As far as we know, the BCI literature lacks a comprehensive evaluation of the usability of the mind-controlled computer cursor in terms of decoder efficiency (accuracy), user experience, and relevant confounding variables concerning the platform for the public use. To fill this gap, we conducted a two-dimensional EEG-based cursor control experiment among 28 healthy participants. The computer cursor velocity was controlled by the imagery of hand movement using a paradigm presented in the literature named imagined body kinematics (IBK) with a low-cost wireless EEG headset. We evaluated the usability of the platform for different objective and subjective measures while we investigated the extent to which the training phase may influence the ultimate BCI outcome. We conducted pre- and post- BCI experiment interview questionnaires to evaluate the usability. Analyzing the questionnaires and the testing phase outcome shows a positive correlation between the individuals' ability of visualization and their level of mental controllability of the cursor. Despite individual differences, analyzing training data shows the significance of electrooculogram (EOG) on the predictability of the linear model. The results of this work may provide useful insights towards designing a personalized user-centered assistive BCI.
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Affiliation(s)
- Reza Abiri
- Dept. of Neurology at University of California, San Francisco/Berkeley and Dept. of Mechanical, Aerospace, and Biomedical Engineering at the University of Tennessee, Knoxville
| | - Soheil Borhani
- Department of Mechanical, Aerospace, and Biomedical Engineering, The University of Tennessee, Knoxville, TN 37996 USA
| | - Justin Kilmarx
- Department of Mechanical, Aerospace, and Biomedical Engineering, The University of Tennessee, Knoxville, TN 37996 USA
| | - Connor Esterwood
- College Communication and Information at the University of Tennessee, Knoxville, TN, USA
| | - Yang Jiang
- Department of Behavioral Science, College of Medicine, at University of Kentucky, Lexington KY, USA
| | - Xiaopeng Zhao
- Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee, Knoxville, TN 37996 USA
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13
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Power L, Neyedli HF, Boe SG, Bardouille T. Efficacy of low-cost wireless neurofeedback to modulate brain activity during motor imagery. Biomed Phys Eng Express 2020; 6:035024. [DOI: 10.1088/2057-1976/ab872c] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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14
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Balart-Sánchez SA, Vélez-Pérez H, Rivera-Tello S, Gómez Velázquez FR, González-Garrido AA, Romo-Vázquez R. A step forward in the quest for a mobile EEG-designed epoch for psychophysiological studies. ACTA ACUST UNITED AC 2020; 64:655-667. [PMID: 31322998 DOI: 10.1515/bmt-2017-0189] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2017] [Accepted: 03/01/2019] [Indexed: 11/15/2022]
Abstract
The aim of this study was to compare a reconfigurable mobile electroencephalography (EEG) system (M-EMOTIV) based on the Emotiv Epoc® (which has the ability to record up to 14 electrode sites in the 10/20 International System) and a commercial, clinical-grade EEG system (Neuronic MEDICID-05®), and then validate the rationale and accuracy of recordings obtained with the prototype proposed. In this approach, an Emotiv Epoc® was modified to enable it to record in the parieto-central area. All subjects (15 healthy individuals) performed a visual oddball task while connected to both devices to obtain electrophysiological data and behavioral responses for comparative analysis. A Pearson's correlation analysis revealed a good between-devices correlation with respect to electrophysiological measures. The present study not only corroborates previous reports on the ability of the Emotiv Epoc® to suitably record EEG data but presents an alternative device that allows the study of a wide range of psychophysiological experiments with simultaneous behavioral and mobile EEG recordings.
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Affiliation(s)
- Sebastián A Balart-Sánchez
- Instituto de Neurociencias, CUCBA, Universidad de Guadalajara, Francisco de Quevedo 180, Arcos Vallarta, C.P. 44130, Guadalajara, Jalisco, Mexico
| | - Hugo Vélez-Pérez
- Departamento de Ciencias Computacionales, CUCEI, Universidad de Guadalajara, Blvd. Marcelino García Barragán 1421, esq. Calzada Olímpica, C.P. 44430, Guadalajara, Jalisco, Mexico
| | - Sergio Rivera-Tello
- Instituto de Neurociencias, CUCBA, Universidad de Guadalajara, Francisco de Quevedo 180, Arcos Vallarta, C.P. 44130, Guadalajara, Jalisco, Mexico.,Departamento de Ciencias Computacionales, CUCEI, Universidad de Guadalajara, Blvd. Marcelino García Barragán 1421, esq. Calzada Olímpica, C.P. 44430, Guadalajara, Jalisco, Mexico
| | - Fabiola R Gómez Velázquez
- Instituto de Neurociencias, CUCBA, Universidad de Guadalajara, Francisco de Quevedo 180, Arcos Vallarta, C.P. 44130, Guadalajara, Jalisco, Mexico
| | - Andrés A González-Garrido
- Instituto de Neurociencias, CUCBA, Universidad de Guadalajara, Francisco de Quevedo 180, Arcos Vallarta, C.P. 44130, Guadalajara, Jalisco, Mexico.,O.P.D. Hospital Civil de Guadalajara, Salvador Quevedo y Zubieta 876, Independencia Oriente, C.P. 44340, Guadalajara, Jalisco, Mexico
| | - Rebeca Romo-Vázquez
- Departamento de Ciencias Computacionales, CUCEI, Universidad de Guadalajara, Blvd. Marcelino García Barragán 1421, esq. Calzada Olímpica, C.P. 44430, Guadalajara, Jalisco, Mexico, E-mail:
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15
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Daeglau M, Wallhoff F, Debener S, Condro IS, Kranczioch C, Zich C. Challenge Accepted? Individual Performance Gains for Motor Imagery Practice with Humanoid Robotic EEG Neurofeedback. SENSORS 2020; 20:s20061620. [PMID: 32183285 PMCID: PMC7146190 DOI: 10.3390/s20061620] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Revised: 03/03/2020] [Accepted: 03/10/2020] [Indexed: 01/10/2023]
Abstract
Optimizing neurofeedback (NF) and brain–computer interface (BCI) implementations constitutes a challenge across many fields and has so far been addressed by, among others, advancing signal processing methods or predicting the user’s control ability from neurophysiological or psychological measures. In comparison, how context factors influence NF/BCI performance is largely unexplored. We here investigate whether a competitive multi-user condition leads to better NF/BCI performance than a single-user condition. We implemented a foot motor imagery (MI) NF with mobile electroencephalography (EEG). Twenty-five healthy, young participants steered a humanoid robot in a single-user condition and in a competitive multi-user race condition using a second humanoid robot and a pseudo competitor. NF was based on 8–30 Hz relative event-related desynchronization (ERD) over sensorimotor areas. There was no significant difference between the ERD during the competitive multi-user condition and the single-user condition but considerable inter-individual differences regarding which condition yielded a stronger ERD. Notably, the stronger condition could be predicted from the participants’ MI-induced ERD obtained before the NF blocks. Our findings may contribute to enhance the performance of NF/BCI implementations and highlight the necessity of individualizing context factors.
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Affiliation(s)
- Mareike Daeglau
- Neurocognition and Functional Neurorehabilitation Group, Neuropsychology Lab, Department of Psychology, School of Medicine and Health Sciences, Carl von Ossietzky University Oldenburg, 26111 Oldenburg, Germany; (C.K.); (C.Z.)
- Correspondence:
| | - Frank Wallhoff
- Institute for Assistive Technologies, Jade University of Applied Science, 26389 Oldenburg, Germany; (F.W.); (I.S.C.)
| | - Stefan Debener
- Neuropsychology Lab, Department of Psychology, School of Medicine and Health Sciences, Carl von Ossietzky University Oldenburg, 26111 Oldenburg, Germany;
- Cluster of Excellence Hearing4All, Carl von Ossietzky University Oldenburg, 26111 Oldenburg, Germany
- Research Center Neurosensory Science, Carl von Ossietzky University Oldenburg, 26111 Oldenburg, Germany
| | - Ignatius Sapto Condro
- Institute for Assistive Technologies, Jade University of Applied Science, 26389 Oldenburg, Germany; (F.W.); (I.S.C.)
| | - Cornelia Kranczioch
- Neurocognition and Functional Neurorehabilitation Group, Neuropsychology Lab, Department of Psychology, School of Medicine and Health Sciences, Carl von Ossietzky University Oldenburg, 26111 Oldenburg, Germany; (C.K.); (C.Z.)
- Research Center Neurosensory Science, Carl von Ossietzky University Oldenburg, 26111 Oldenburg, Germany
| | - Catharina Zich
- Neurocognition and Functional Neurorehabilitation Group, Neuropsychology Lab, Department of Psychology, School of Medicine and Health Sciences, Carl von Ossietzky University Oldenburg, 26111 Oldenburg, Germany; (C.K.); (C.Z.)
- Department of Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK;
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16
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Cao L, Händel B. Walking enhances peripheral visual processing in humans. PLoS Biol 2019; 17:e3000511. [PMID: 31603894 PMCID: PMC6808500 DOI: 10.1371/journal.pbio.3000511] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Revised: 10/23/2019] [Accepted: 09/30/2019] [Indexed: 02/08/2023] Open
Abstract
Cognitive processes are almost exclusively investigated under highly controlled settings during which voluntary body movements are suppressed. However, recent animal work suggests differences in sensory processing between movement states by showing drastically changed neural responses in early visual areas between locomotion and stillness. Does locomotion also modulate visual cortical activity in humans, and what are the perceptual consequences? Our study shows that walking increased the contrast-dependent influence of peripheral visual input on central visual input. This increase is prevalent in stimulus-locked electroencephalogram (EEG) responses (steady-state visual evoked potential [SSVEP]) alongside perceptual performance. Ongoing alpha oscillations (approximately 10 Hz) further positively correlated with the walking-induced changes of SSVEP amplitude, indicating the involvement of an altered inhibitory process during walking. The results predicted that walking leads to an increased processing of peripheral visual input. A second study indeed showed an increased contrast sensitivity for peripheral compared to central stimuli when subjects were walking. Our work shows complementary neurophysiological and behavioural evidence corroborating animal findings that walking leads to a change in early visual neuronal activity in humans. That neuronal modulation due to walking is indeed linked to specific perceptual changes extends the existing animal work.
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Affiliation(s)
- Liyu Cao
- Department of Psychology, University of Würzburg, Würzburg, Germany
| | - Barbara Händel
- Department of Psychology, University of Würzburg, Würzburg, Germany
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17
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Šumak B, Špindler M, Debeljak M, Heričko M, Pušnik M. An empirical evaluation of a hands-free computer interaction for users with motor disabilities. J Biomed Inform 2019; 96:103249. [DOI: 10.1016/j.jbi.2019.103249] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2018] [Revised: 06/19/2019] [Accepted: 07/07/2019] [Indexed: 10/26/2022]
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18
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Detecting the neural correlates of episodic memory with mobile EEG: Recollecting objects in the real world. Neuroimage 2019; 193:1-9. [DOI: 10.1016/j.neuroimage.2019.03.013] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2018] [Revised: 02/26/2019] [Accepted: 03/06/2019] [Indexed: 11/17/2022] Open
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19
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Wang D, Yu H, Wu J, Meng Q, Lin Q. Integrating fuzzy based QFD and AHP for the design and implementation of a hand training device. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2019. [DOI: 10.3233/jifs-181025] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Duojin Wang
- Shanghai Engineering Research Center of Assistive Devices/Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China
| | - Hongliu Yu
- Shanghai Engineering Research Center of Assistive Devices/Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China
| | - Jing Wu
- School of Economics & Management, Tongji University, Shanghai, China
| | - Qingyun Meng
- College of Rehabilitation Sciences, Shanghai University of Medicine & Health Sciences, Shanghai, China
| | - Qinglian Lin
- School of Management, Xiamen University, Siming South Road, Xiamen, China
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20
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Lau-Zhu A, Lau MPH, McLoughlin G. Mobile EEG in research on neurodevelopmental disorders: Opportunities and challenges. Dev Cogn Neurosci 2019; 36:100635. [PMID: 30877927 PMCID: PMC6534774 DOI: 10.1016/j.dcn.2019.100635] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Revised: 03/06/2019] [Accepted: 03/06/2019] [Indexed: 11/23/2022] Open
Abstract
Mobile electroencephalography (mobile EEG) represents a next-generation neuroscientific technology – to study real-time brain activity – that is relatively inexpensive, non-invasive and portable. Mobile EEG leverages state-of-the-art hardware alongside established advantages of traditional EEG and recent advances in signal processing. In this review, we propose that mobile EEG could open unprecedented possibilities for studying neurodevelopmental disorders. We first present a brief overview of recent developments in mobile EEG technologies, emphasising the proliferation of studies in several neuroscientific domains. As these developments have yet to be exploited by neurodevelopmentalists, we then identify three research opportunities: 1) increase in the ease and flexibility of brain data acquisition in neurodevelopmental populations; 2) integration into powerful developmentally-informative research designs; 3) development of innovative non-stationary EEG-based paradigms. Critically, we address key challenges that should be considered to fully realise the potential of mobile EEG for neurodevelopmental research and for understanding developmental psychopathology more broadly, and suggest future research directions.
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Affiliation(s)
- Alex Lau-Zhu
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
| | - Michael P H Lau
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Gráinne McLoughlin
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
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21
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An EEG Experimental Study Evaluating the Performance of Texas Instruments ADS1299. SENSORS 2018; 18:s18113721. [PMID: 30388836 PMCID: PMC6263632 DOI: 10.3390/s18113721] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/09/2018] [Revised: 10/26/2018] [Accepted: 10/30/2018] [Indexed: 11/17/2022]
Abstract
Texas Instruments ADS1299 is an attractive choice for low cost electroencephalography (EEG) devices owing to its low power consumption and low input referred noise. To date, there have been no rigorous evaluations of its performance. In this EEG experimental study we evaluated the performance of the ADS1299 against a high quality laboratory-based system. Two self-paced lower limb motor tasks were performed by 22 healthy participants. Recorded power across delta, theta, alpha, and beta EEG bands, the power ratio across the motor tasks, pre-movement noise, and signal-to-noise ratio were obtained for evaluation. The amplitude and time of the negative peak in the movement-related cortical potentials (MRCPs) extracted from the EEG data were also obtained. Using linear mixed models, no statistically significant differences (p > 0.05) were found in any of these measures across the two systems. These findings were further supported by evaluation of cosine similarity, waveform differences, and topographic maps. There were statistically significant differences in MRCPs across the motor tasks in both systems. We conclude that the performance of the ADS1299 in combination with wet Ag/AgCl electrodes is analogous to that of a laboratory-based system in a low frequency (<40 Hz) EEG recording.
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22
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Wang D, Meng Q, Meng Q, Li X, Yu H. Design and Development of a Portable Exoskeleton for Hand Rehabilitation. IEEE Trans Neural Syst Rehabil Eng 2018; 26:2376-2386. [PMID: 30387735 DOI: 10.1109/tnsre.2018.2878778] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Improvement in hand function to promote functional recovery is one of the major goals of stroke rehabilitation. This paper introduces a newly developed exoskeleton for hand rehabilitation with a user-centered design concept, which integrates the requirements of practical use, mechanical structure, and control system. The paper also evaluated the function with two prototypes in a local hospital. Results of functional evaluation showed that significant improvements were found in ARAT (P = 0.014), WMFT (P = 0.020), and FMA_WH (P = 0.021). Increase in the mean values of FMA_SE was observed but without significant difference (P = 0.071). The improvement in ARAT score reflects the motor recovery in hand and finger functions. The increased FMA scores suggest there is a motor improvement in the whole upper limb, and especially in the hand after the training. The product met patients' requirements and has practical significance. It is portable, cost-effective, easy to use and supports multiple control modes to adapt to different rehabilitation phases.
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23
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Wang F, Zhang X, Fu R, Sun G. Study of the Home-Auxiliary Robot Based on BCI. SENSORS (BASEL, SWITZERLAND) 2018; 18:E1779. [PMID: 29865175 PMCID: PMC6021918 DOI: 10.3390/s18061779] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/31/2018] [Revised: 05/20/2018] [Accepted: 05/29/2018] [Indexed: 01/13/2023]
Abstract
A home-auxiliary robot platform is developed in the current study which could assist patients with physical disabilities and older persons with mobility impairments. The robot, mainly controlled by brain computer interface (BCI) technology, can not only perform actions in a person's field of vision, but also work outside the field of vision. The wavelet decomposition (WD) is used in this study to extract the δ (0~4 Hz) and θ (4~8 Hz) sub-bands of subjects' electroencephalogram (EEG) signals. The correlation between pairs of 14 EEG channels is determined with synchronization likelihood (SL), and the brain network structure is generated. Then, the motion characteristics are analyzed using the brain network parameters clustering coefficient (C) and global efficiency (G). Meanwhile, the eye movement characteristics in the F3 and F4 channels are identified. Finally, the motion characteristics identified by brain networks and eye movement characteristics can be used to control the home-auxiliary robot platform. The experimental result shows that the accuracy rate of left and right motion recognition using this method is more than 93%. Additionally, the similarity between that autonomous return path and the real path of the home-auxiliary robot reaches up to 0.89.
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Affiliation(s)
- Fuwang Wang
- School of Mechanic Engineering, Northeast Electric Power University, Jilin 132012, China.
| | - Xiaolei Zhang
- School of Mechanic Engineering, Northeast Electric Power University, Jilin 132012, China.
| | - Rongrong Fu
- College of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China.
| | - Guangbin Sun
- Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing 100094, China.
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24
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Bagarinao E, Yoshida A, Ueno M, Terabe K, Kato S, Isoda H, Nakai T. Improved Volitional Recall of Motor-Imagery-Related Brain Activation Patterns Using Real-Time Functional MRI-Based Neurofeedback. Front Hum Neurosci 2018; 12:158. [PMID: 29740302 PMCID: PMC5928248 DOI: 10.3389/fnhum.2018.00158] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2017] [Accepted: 04/05/2018] [Indexed: 11/13/2022] Open
Abstract
Motor imagery (MI), a covert cognitive process where an action is mentally simulated but not actually performed, could be used as an effective neurorehabilitation tool for motor function improvement or recovery. Recent approaches employing brain–computer/brain–machine interfaces to provide online feedback of the MI during rehabilitation training have promising rehabilitation outcomes. In this study, we examined whether participants could volitionally recall MI-related brain activation patterns when guided using neurofeedback (NF) during training. The participants’ performance was compared to that without NF. We hypothesized that participants would be able to consistently generate the relevant activation pattern associated with the MI task during training with NF compared to that without NF. To assess activation consistency, we used the performance of classifiers trained to discriminate MI-related brain activation patterns. Our results showed significantly higher predictive values of MI-related activation patterns during training with NF. Additionally, this improvement in the classification performance tends to be associated with the activation of middle temporal gyrus/inferior occipital gyrus, a region associated with visual motion processing, suggesting the importance of performance monitoring during MI task training. Taken together, these findings suggest that the efficacy of MI training, in terms of generating consistent brain activation patterns relevant to the task, can be enhanced by using NF as a mechanism to enable participants to volitionally recall task-related brain activation patterns.
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Affiliation(s)
| | - Akihiro Yoshida
- Department of Radiological Sciences, Nagoya University Graduate School of Medicine, Nagoya University, Nagoya, Japan.,NeuroImaging and Informatics Lab, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Mika Ueno
- NeuroImaging and Informatics Lab, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Kazunori Terabe
- Graduate School of Engineering, Nagoya Institute of Technology, Nagoya, Japan
| | - Shohei Kato
- Graduate School of Engineering, Nagoya Institute of Technology, Nagoya, Japan
| | - Haruo Isoda
- Brain & Mind Research Center, Nagoya University, Nagoya, Japan.,Department of Radiological Sciences, Nagoya University Graduate School of Medicine, Nagoya University, Nagoya, Japan
| | - Toshiharu Nakai
- Department of Radiological Sciences, Nagoya University Graduate School of Medicine, Nagoya University, Nagoya, Japan.,NeuroImaging and Informatics Lab, National Center for Geriatrics and Gerontology, Obu, Japan
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25
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Wang F, Wang H, Fu R. Real-Time ECG-Based Detection of Fatigue Driving Using Sample Entropy. ENTROPY (BASEL, SWITZERLAND) 2018; 20:E196. [PMID: 33265287 PMCID: PMC7512712 DOI: 10.3390/e20030196] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/03/2018] [Revised: 03/03/2018] [Accepted: 03/13/2018] [Indexed: 11/25/2022]
Abstract
In present work, the heart rate variability (HRV) characteristics, calculated by sample entropy (SampEn), were used to analyze the driving fatigue state at successive driving stages. Combined with the relative power spectrum ratio β/(θ + α), subjective questionnaire, and brain network parameters of electroencephalogram (EEG) signals, the relationships between the different characteristics for driving fatigue were discussed. Thus, it can conclude that the HRV characteristics (RR SampEn and R peaks SampEn), as well as the relative power spectrum ratio β/(θ + α) of the channels (C3, C4, P3, P4), the subjective questionnaire, and the brain network parameters, can effectively detect driving fatigue at various driving stages. In addition, the method for collecting ECG signals from the palm part does not need patch electrodes, is convenient, and will be practical to use in actual driving situations in the future.
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Affiliation(s)
- Fuwang Wang
- School of Mechanic Engineering, Northeast Electric Power University, Jilin 132012, China
| | - Hong Wang
- School of Mechanic Engineering, Northeastern University, Shenyang 110819, China
| | - Rongrong Fu
- College of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
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26
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Oliveira SMSD, Medeiros CSPD, Pacheco TBF, Bessa NPOS, Silva FGM, Tavares NSA, Rego IAO, Campos TF, Cavalcanti FADC. Electroencephalographic changes using virtual reality program: technical note. Neurol Res 2018; 40:160-165. [DOI: 10.1080/01616412.2017.1420584] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- Síria Monyelle Silva de Oliveira
- Laboratory of Virtual Reality and Rehabilitation, Department of Physical Therapy, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Candice Simões Pimenta de Medeiros
- Laboratory of Virtual Reality and Rehabilitation, Department of Physical Therapy, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Thaiana Barbosa Ferreira Pacheco
- Laboratory of Virtual Reality and Rehabilitation, Department of Physical Therapy, Federal University of Rio Grande do Norte, Natal, Brazil
| | | | - Fernanda Gabrielle Mendonça Silva
- Laboratory of Virtual Reality and Rehabilitation, Department of Physical Therapy, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Nathália Stéphany Araújo Tavares
- Laboratory of Virtual Reality and Rehabilitation, Department of Physical Therapy, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Isabelle Ananda Oliveira Rego
- Laboratory of Virtual Reality and Rehabilitation, Department of Physical Therapy, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Tania Fernandes Campos
- Laboratory of Virtual Reality and Rehabilitation, Department of Physical Therapy, Federal University of Rio Grande do Norte, Natal, Brazil
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27
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Pacheco TBF, Oliveira Rego IA, Campos TF, Cavalcanti FADC. Brain activity during a lower limb functional task in a real and virtual environment: A comparative study. NeuroRehabilitation 2017; 40:391-400. [PMID: 28222559 DOI: 10.3233/nre-161426] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Virtual Reality (VR) has been contributing to Neurological Rehabilitation because of its interactive and multisensory nature, providing the potential of brain reorganization. Given the use of mobile EEG devices, there is the possibility of investigating how the virtual therapeutic environment can influence brain activity. OBJECTIVE To compare theta, alpha, beta and gamma power in healthy young adults during a lower limb motor task in a virtual and real environment. METHODS Ten healthy adults were submitted to an EEG assessment while performing a one-minute task consisted of going up and down a step in a virtual environment - Nintendo Wii virtual game "Basic step" - and in a real environment. RESULTS Real environment caused an increase in theta and alpha power, with small to large size effects mainly in the frontal region. VR caused a greater increase in beta and gamma power, however, with small or negligible effects on a variety of regions regarding beta frequency, and medium to very large effects on the frontal and the occipital regions considering gamma frequency. CONCLUSIONS Theta, alpha, beta and gamma activity during the execution of a motor task differs according to the environment that the individual is exposed - real or virtual - and may have varying size effects if brain area activation and frequency spectrum in each environment are taken into consideration.
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28
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Categorisation of Mobile EEG: A Researcher's Perspective. BIOMED RESEARCH INTERNATIONAL 2017; 2017:5496196. [PMID: 29349078 PMCID: PMC5733835 DOI: 10.1155/2017/5496196] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/03/2017] [Revised: 09/06/2017] [Accepted: 10/16/2017] [Indexed: 11/17/2022]
Abstract
Researchers are increasingly attempting to undertake electroencephalography (EEG) recordings in novel environments and contexts outside of the traditional static laboratory setting. The term “mobile EEG,” although commonly used to describe many of these undertakings, is ambiguous, since it attempts to encompass a wide range of EEG device mobility, participant mobility, and system specifications used across investigations. To provide quantitative parameters for “mobile EEG,” we developed a Categorisation of Mobile EEG (CoME) scheme based upon scoring of device mobility (D, from 0, off-body, to 5, head-mounted with no additional equipment), participant mobility (P, from 0, static, to 5, unconstrained running), system specification (S, from 4, lowest, to 20, highest), and number of channels (C) used. The CoME scheme was applied to twenty-nine published mobile EEG studies. Device mobility scores ranged from 0D to 4D, participant mobility scores from 0P to 4P, and system specification scores from 6S to 17S. The format of the scores for the four parameters is given, for example, as (2D, 4P, 17S, 32C) and readily enables comparisons across studies. Our CoME scheme enables researchers to quantify the degree of device mobility, participant mobility, and system specification used in their “mobile EEG” investigations in a standardised way.
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29
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Zich C, Debener S, Schweinitz C, Sterr A, Meekes J, Kranczioch C. High-Intensity Chronic Stroke Motor Imagery Neurofeedback Training at Home: Three Case Reports. Clin EEG Neurosci 2017; 48:403-412. [PMID: 28677413 DOI: 10.1177/1550059417717398] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Motor imagery (MI) with neurofeedback has been suggested as promising for motor recovery after stroke. Evidence suggests that regular training facilitates compensatory plasticity, but frequent training is difficult to integrate into everyday life. Using a wireless electroencephalogram (EEG) system, we implemented a frequent and efficient neurofeedback training at the patients' home. Aiming to overcome maladaptive changes in cortical lateralization patterns we presented a visual feedback, representing the degree of contralateral sensorimotor cortical activity and the degree of sensorimotor cortex lateralization. Three stroke patients practiced every other day, over a period of 4 weeks. Training-related changes were evaluated on behavioral, functional, and structural levels. All 3 patients indicated that they enjoyed the training and were highly motivated throughout the entire training regime. EEG activity induced by MI of the affected hand became more lateralized over the course of training in all three patients. The patient with a significant functional change also showed increased white matter integrity as revealed by diffusion tensor imaging, and a substantial clinical improvement of upper limb motor functions. Our study provides evidence that regular, home-based practice of MI neurofeedback has the potential to facilitate cortical reorganization and may also increase associated improvements of upper limb motor function in chronic stroke patients.
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Affiliation(s)
- Catharina Zich
- 1 Neuropsychology Lab, Department of Psychology, European Medical School, University of Oldenburg, Oldenburg, Germany.,2 Department of Experimental Psychology, University of Oxford, Oxford, UK
| | - Stefan Debener
- 1 Neuropsychology Lab, Department of Psychology, European Medical School, University of Oldenburg, Oldenburg, Germany.,3 Cluster of Excellence Hearing4all, University of Oldenburg, Oldenburg, Germany.,4 Research Center Neurosensory Systems, University of Oldenburg, Oldenburg, Germany
| | - Clara Schweinitz
- 1 Neuropsychology Lab, Department of Psychology, European Medical School, University of Oldenburg, Oldenburg, Germany
| | - Annette Sterr
- 5 Brain and Behaviour Research Group, School of Psychology, University of Surrey, Guildford, UK
| | - Joost Meekes
- 1 Neuropsychology Lab, Department of Psychology, European Medical School, University of Oldenburg, Oldenburg, Germany
| | - Cornelia Kranczioch
- 1 Neuropsychology Lab, Department of Psychology, European Medical School, University of Oldenburg, Oldenburg, Germany.,4 Research Center Neurosensory Systems, University of Oldenburg, Oldenburg, Germany
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30
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Wöhrle H, Tabie M, Kim SK, Kirchner F, Kirchner EA. A Hybrid FPGA-Based System for EEG- and EMG-Based Online Movement Prediction. SENSORS (BASEL, SWITZERLAND) 2017; 17:E1552. [PMID: 28671632 PMCID: PMC5539567 DOI: 10.3390/s17071552] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/07/2017] [Revised: 06/19/2017] [Accepted: 06/28/2017] [Indexed: 01/22/2023]
Abstract
A current trend in the development of assistive devices for rehabilitation, for example exoskeletons or active orthoses, is to utilize physiological data to enhance their functionality and usability, for example by predicting the patient's upcoming movements using electroencephalography (EEG) or electromyography (EMG). However, these modalities have different temporal properties and classification accuracies, which results in specific advantages and disadvantages. To use physiological data analysis in rehabilitation devices, the processing should be performed in real-time, guarantee close to natural movement onset support, provide high mobility, and should be performed by miniaturized systems that can be embedded into the rehabilitation device. We present a novel Field Programmable Gate Array (FPGA) -based system for real-time movement prediction using physiological data. Its parallel processing capabilities allows the combination of movement predictions based on EEG and EMG and additionally a P300 detection, which is likely evoked by instructions of the therapist. The system is evaluated in an offline and an online study with twelve healthy subjects in total. We show that it provides a high computational performance and significantly lower power consumption in comparison to a standard PC. Furthermore, despite the usage of fixed-point computations, the proposed system achieves a classification accuracy similar to systems with double precision floating-point precision.
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Affiliation(s)
- Hendrik Wöhrle
- DFKI GmbH, Robotics Innovation Center (RIC), Robert-Hooke-Str. 1, D-28359 Bremen, Germany.
| | - Marc Tabie
- DFKI GmbH, Robotics Innovation Center (RIC), Robert-Hooke-Str. 1, D-28359 Bremen, Germany.
| | - Su Kyoung Kim
- DFKI GmbH, Robotics Innovation Center (RIC), Robert-Hooke-Str. 1, D-28359 Bremen, Germany.
| | - Frank Kirchner
- DFKI GmbH, Robotics Innovation Center (RIC), Robert-Hooke-Str. 1, D-28359 Bremen, Germany.
- Robotics Group, Department of Mathematics and Computer Science, University of Bremen, Robert-Hooke-Str. 1, D-28359 Bremen, Germany.
| | - Elsa Andrea Kirchner
- DFKI GmbH, Robotics Innovation Center (RIC), Robert-Hooke-Str. 1, D-28359 Bremen, Germany.
- Robotics Group, Department of Mathematics and Computer Science, University of Bremen, Robert-Hooke-Str. 1, D-28359 Bremen, Germany.
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Malcolm BR, Foxe JJ, Butler JS, Mowrey WB, Molholm S, De Sanctis P. Long-term test-retest reliability of event-related potential (ERP) recordings during treadmill walking using the mobile brain/body imaging (MoBI) approach. Brain Res 2017; 1716:62-69. [PMID: 28532853 DOI: 10.1016/j.brainres.2017.05.021] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2016] [Revised: 04/19/2017] [Accepted: 05/18/2017] [Indexed: 10/19/2022]
Abstract
Advancements in acquisition technology and signal-processing techniques have spurred numerous recent investigations on the electro-cortical signals generated during whole-body motion. This approach, termed Mobile Brain/Body Imaging (MoBI), has the potential to elucidate the neural correlates of perceptual and cognitive processes during real-life activities, such as locomotion. However, as of yet, no one has assessed the long-term stability of event-related potentials (ERPs) recorded under these conditions. Therefore, the objective of the current study was to evaluate the test-retest reliability of cognitive ERPs recorded while walking. High-density EEG was acquired from 12 young adults on two occasions, separated by an average of 2.3years, as they performed a Go/No-Go response inhibition paradigm. During each testing session, participants performed the task while walking on a treadmill and seated. Using the intraclass correlation coefficient (ICC) as a measure of agreement, we focused on two well-established neurophysiological correlates of cognitive control, the N2 and P3 ERPs. Following ICA-based artifact rejection, the earlier N2 yielded good to excellent levels of reliability for both amplitude and latency, while measurements for the later P3 component were generally less robust but still indicative of adequate to good levels of stability. Interestingly, the N2 was more consistent between walking sessions, compared to sitting, for both hits and correct rejection trials. In contrast, the P3 waveform tended to have a higher degree of consistency during sitting conditions. Overall, these results suggest that the electro-cortical signals obtained during active walking are representative of stable indices of neurophysiological function.
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Affiliation(s)
- Brenda R Malcolm
- The Sheryl & Daniel R. Tishman Cognitive Neurophysiology Laboratory, Children's Evaluation and Rehabilitation Center (CERC), Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY 10461, USA; Program in Cognitive Neuroscience, The Graduate Center of the City University of New York, New York, NY 10016, USA
| | - John J Foxe
- The Sheryl & Daniel R. Tishman Cognitive Neurophysiology Laboratory, Children's Evaluation and Rehabilitation Center (CERC), Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY 10461, USA; Program in Cognitive Neuroscience, The Graduate Center of the City University of New York, New York, NY 10016, USA; The Del Monte Institute for Neuroscience, Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA; The Dominick P. Purpura Department of Neuroscience, Rose F. Kennedy Intellectual and Developmental Disabilities Research Center, Albert Einstein College of Medicine, Bronx, NY 10461, USA; Trinity College Institute of Neuroscience, Dublin, Ireland.
| | - John S Butler
- The Sheryl & Daniel R. Tishman Cognitive Neurophysiology Laboratory, Children's Evaluation and Rehabilitation Center (CERC), Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY 10461, USA; Trinity College Institute of Neuroscience, Dublin, Ireland; Trinity College Dublin, Centre for Bioengineering, Trinity Biomedical Sciences Institute, Dublin, Ireland; School of Mathematical Sciences, Dublin Institute of Technology, Dublin, Ireland
| | - Wenzhu B Mowrey
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Sophie Molholm
- The Sheryl & Daniel R. Tishman Cognitive Neurophysiology Laboratory, Children's Evaluation and Rehabilitation Center (CERC), Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY 10461, USA; Program in Cognitive Neuroscience, The Graduate Center of the City University of New York, New York, NY 10016, USA; The Del Monte Institute for Neuroscience, Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA; The Dominick P. Purpura Department of Neuroscience, Rose F. Kennedy Intellectual and Developmental Disabilities Research Center, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Pierfilippo De Sanctis
- The Sheryl & Daniel R. Tishman Cognitive Neurophysiology Laboratory, Children's Evaluation and Rehabilitation Center (CERC), Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY 10461, USA; Program in Cognitive Neuroscience, The Graduate Center of the City University of New York, New York, NY 10016, USA; The Saul R. Korey Department of Neurology, Albert Einstein College of Medicine, Bronx, NY 10461, USA.
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Ladouce S, Donaldson DI, Dudchenko PA, Ietswaart M. Understanding Minds in Real-World Environments: Toward a Mobile Cognition Approach. Front Hum Neurosci 2017; 10:694. [PMID: 28127283 PMCID: PMC5226959 DOI: 10.3389/fnhum.2016.00694] [Citation(s) in RCA: 61] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2016] [Accepted: 12/29/2016] [Indexed: 11/13/2022] Open
Abstract
There is a growing body of evidence that important aspects of human cognition have been marginalized, or overlooked, by traditional cognitive science. In particular, the use of laboratory-based experiments in which stimuli are artificial, and response options are fixed, inevitably results in findings that are less ecologically valid in relation to real-world behavior. In the present review we highlight the opportunities provided by a range of new mobile technologies that allow traditionally lab-bound measurements to now be collected during natural interactions with the world. We begin by outlining the theoretical support that mobile approaches receive from the development of embodied accounts of cognition, and we review the widening evidence that illustrates the importance of examining cognitive processes in their context. As we acknowledge, in practice, the development of mobile approaches brings with it fresh challenges, and will undoubtedly require innovation in paradigm design and analysis. If successful, however, the mobile cognition approach will offer novel insights in a range of areas, including understanding the cognitive processes underlying navigation through space and the role of attention during natural behavior. We argue that the development of real-world mobile cognition offers both increased ecological validity, and the opportunity to examine the interactions between perception, cognition and action-rather than examining each in isolation.
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Friesen CL, Bardouille T, Neyedli HF, Boe SG. Combined Action Observation and Motor Imagery Neurofeedback for Modulation of Brain Activity. Front Hum Neurosci 2017; 10:692. [PMID: 28119594 PMCID: PMC5223402 DOI: 10.3389/fnhum.2016.00692] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2016] [Accepted: 12/26/2016] [Indexed: 12/27/2022] Open
Abstract
Motor imagery (MI) and action observation have proven to be efficacious adjuncts to traditional physiotherapy for enhancing motor recovery following stroke. Recently, researchers have used a combined approach called imagined imitation (II), where an individual watches a motor task being performed, while simultaneously imagining they are performing the movement. While neurofeedback (NFB) has been used extensively with MI to improve patients' ability to modulate sensorimotor activity and enhance motor recovery, the effectiveness of using NFB with II to modulate brain activity is unknown. This project tested the ability of participants to modulate sensorimotor activity during electroencephalography-based II-NFB of a complex, multi-part unilateral handshake, and whether this ability transferred to a subsequent bout of MI. Moreover, given the goal of translating findings from NFB research into practical applications, such as rehabilitation, the II-NFB system was designed with several user interface and user experience features, in an attempt to both drive user engagement and match the level of challenge to the abilities of the subjects. In particular, at easy difficulty levels the II-NFB system incentivized contralateral sensorimotor up-regulation (via event related desynchronization of the mu rhythm), while at higher difficulty levels the II-NFB system incentivized sensorimotor lateralization (i.e., both contralateral up-regulation and ipsilateral down-regulation). Thirty-two subjects, receiving real or sham NFB attended four sessions where they engaged in II-NFB training and subsequent MI. Results showed the NFB group demonstrated more bilateral sensorimotor activity during sessions 2–4 during II-NFB and subsequent MI, indicating mixed success for the implementation of this particular II-NFB system. Here we discuss our findings in the context of the design features included in the II-NFB system, highlighting limitations that should be considered in future designs.
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Affiliation(s)
- Christopher L Friesen
- Laboratory for Brain Recovery and Function, Dalhousie UniversityHalifax, NS, Canada; Department of Psychology and Neuroscience, Dalhousie UniversityHalifax, NS, Canada
| | - Timothy Bardouille
- Department of Psychology and Neuroscience, Dalhousie UniversityHalifax, NS, Canada; Biomedical Translational Imaging Centre, IWK Health CentreHalifax, NS, Canada; School of Physiotherapy, Dalhousie UniversityHalifax, NS, Canada
| | - Heather F Neyedli
- Department of Psychology and Neuroscience, Dalhousie UniversityHalifax, NS, Canada; School of Health and Human Performance, Dalhousie UniversityHalifax, NS, Canada
| | - Shaun G Boe
- Laboratory for Brain Recovery and Function, Dalhousie UniversityHalifax, NS, Canada; Department of Psychology and Neuroscience, Dalhousie UniversityHalifax, NS, Canada; School of Physiotherapy, Dalhousie UniversityHalifax, NS, Canada; School of Health and Human Performance, Dalhousie UniversityHalifax, NS, Canada
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Lacko D, Vleugels J, Fransen E, Huysmans T, De Bruyne G, Van Hulle MM, Sijbers J, Verwulgen S. Ergonomic design of an EEG headset using 3D anthropometry. APPLIED ERGONOMICS 2017; 58:128-136. [PMID: 27633205 DOI: 10.1016/j.apergo.2016.06.002] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2015] [Revised: 04/25/2016] [Accepted: 06/10/2016] [Indexed: 06/06/2023]
Abstract
Although EEG experiments over the past decades have shown numerous applications for brain-computer interfacing (BCI), there is a need for user-friendly BCI devices that can be used in real-world situations. 3D anthropometry and statistical shape modeling have been shown to improve the fit of devices such as helmets and respirators, and thus they might also be suitable to design BCI headgear that better fits the size and shape variation of the human head. In this paper, a new design method for BCI devices is proposed and evaluated. A one-size-fits-all BCI headset frame is designed on the basis of three digital mannequins derived from a shape model of the human head. To verify the design, the geometric fit, stability and repeatability of the prototype were compared to an EEG cap and a commercial BCI headset in a preliminary experiment. Most design specifications were met, and all the results were found to be similar to those of the commercial headset. Therefore, the suggested design method is a feasible alternative to traditional anthropometric design for BCI headsets and similar headgear.
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Affiliation(s)
- Daniël Lacko
- iMinds-Vision Lab, University of Antwerp, Antwerp, Belgium; Department of Design Science, Product Development, University of Antwerp, Antwerp, Belgium; Laboratorium voor Neuro- en Psychofysiologie, KU Leuven, Leuven, Belgium.
| | - Jochen Vleugels
- Department of Design Science, Product Development, University of Antwerp, Antwerp, Belgium
| | - Erik Fransen
- StatUa Center for Statistics, University of Antwerp, Belgium
| | - Toon Huysmans
- iMinds-Vision Lab, University of Antwerp, Antwerp, Belgium
| | - Guido De Bruyne
- Department of Design Science, Product Development, University of Antwerp, Antwerp, Belgium
| | - Marc M Van Hulle
- Laboratorium voor Neuro- en Psychofysiologie, KU Leuven, Leuven, Belgium
| | - Jan Sijbers
- iMinds-Vision Lab, University of Antwerp, Antwerp, Belgium
| | - Stijn Verwulgen
- Department of Design Science, Product Development, University of Antwerp, Antwerp, Belgium
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Elsawy AS, Eldawlatly S, Taher M, Aly GM. Performance analysis of a Principal Component Analysis ensemble classifier for Emotiv headset P300 spellers. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2016; 2014:5032-5. [PMID: 25571123 DOI: 10.1109/embc.2014.6944755] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
The current trend to use Brain-Computer Interfaces (BCIs) with mobile devices mandates the development of efficient EEG data processing methods. In this paper, we demonstrate the performance of a Principal Component Analysis (PCA) ensemble classifier for P300-based spellers. We recorded EEG data from multiple subjects using the Emotiv neuroheadset in the context of a classical oddball P300 speller paradigm. We compare the performance of the proposed ensemble classifier to the performance of traditional feature extraction and classifier methods. Our results demonstrate the capability of the PCA ensemble classifier to classify P300 data recorded using the Emotiv neuroheadset with an average accuracy of 86.29% on cross-validation data. In addition, offline testing of the recorded data reveals an average classification accuracy of 73.3% that is significantly higher than that achieved using traditional methods. Finally, we demonstrate the effect of the parameters of the P300 speller paradigm on the performance of the method.
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Oliveira AS, Schlink BR, Hairston WD, König P, Ferris DP. Proposing Metrics for Benchmarking Novel EEG Technologies Towards Real-World Measurements. Front Hum Neurosci 2016; 10:188. [PMID: 27242467 PMCID: PMC4861738 DOI: 10.3389/fnhum.2016.00188] [Citation(s) in RCA: 64] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2015] [Accepted: 04/14/2016] [Indexed: 11/13/2022] Open
Abstract
Recent advances in electroencephalographic (EEG) acquisition allow for recordings using wet and dry sensors during whole-body motion. The large variety of commercially available EEG systems contrasts with the lack of established methods for objectively describing their performance during whole-body motion. Therefore, the aim of this study was to introduce methods for benchmarking the suitability of new EEG technologies for that context. Subjects performed an auditory oddball task using three different EEG systems (Biosemi wet—BSM, Cognionics Wet—Cwet, Conionics Dry—Cdry). Nine subjects performed the oddball task while seated and walking on a treadmill. We calculated EEG epoch rejection rate, pre-stimulus noise (PSN), signal-to-noise ratio (SNR) and EEG amplitude variance across the P300 event window (CVERP) from a subset of 12 channels common to all systems. We also calculated test-retest reliability and the subject’s level of comfort while using each system. Our results showed that using the traditional 75 μV rejection threshold BSM and Cwet epoch rejection rates are ~25% and ~47% in the seated and walking conditions respectively. However, this threshold rejects ~63% of epochs for Cdry in the seated condition and excludes 100% of epochs for the majority of subjects during walking. BSM showed predominantly no statistical differences between seated and walking condition for all metrics, whereas Cwet showed increases in PSN and CVERP, as well as reduced SNR in the walking condition. Data quality from Cdry in seated conditions were predominantly inferior in comparison to the wet systems. Test-retest reliability was mostly moderate/good for these variables, especially in seated conditions. In addition, subjects felt less discomfort and were motivated for longer recording periods while using wet EEG systems in comparison to the dry system. The proposed method was successful in identifying differences across systems that are mostly caused by motion-related artifacts and usability issues. We conclude that the extraction of the selected metrics from an auditory oddball paradigm may be used as a benchmark method for testing the performance of different EEG systems in mobile conditions. Moreover dry EEG systems may need substantial improvements to meet the quality standards of wet electrodes.
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Affiliation(s)
- Anderson S Oliveira
- Human Neuromechanics Laboratory, School of Kinesiology, University of Michigan Ann Arbor, MI, USA
| | - Bryan R Schlink
- Human Neuromechanics Laboratory, School of Kinesiology, University of Michigan Ann Arbor, MI, USA
| | - W David Hairston
- Translational Neuroscience, Human Research and Engineering Directorate, U.S. Army Research Laboratory Adelphi, MD, USA
| | - Peter König
- Institute of Cognitive Science, University of OsnabrückOsnabrück, Germany; Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-EppendorfHamburg, Germany
| | - Daniel P Ferris
- Human Neuromechanics Laboratory, School of Kinesiology, University of Michigan Ann Arbor, MI, USA
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Furlan L, Conforto AB, Cohen LG, Sterr A. Upper Limb Immobilisation: A Neural Plasticity Model with Relevance to Poststroke Motor Rehabilitation. Neural Plast 2015; 2016:8176217. [PMID: 26843992 PMCID: PMC4710952 DOI: 10.1155/2016/8176217] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2015] [Revised: 10/13/2015] [Accepted: 10/19/2015] [Indexed: 11/26/2022] Open
Abstract
Advances in our understanding of the neural plasticity that occurs after hemiparetic stroke have contributed to the formulation of theories of poststroke motor recovery. These theories, in turn, have underpinned contemporary motor rehabilitation strategies for treating motor deficits after stroke, such as upper limb hemiparesis. However, a relative drawback has been that, in general, these strategies are most compatible with the recovery profiles of relatively high-functioning stroke survivors and therefore do not easily translate into benefit to those individuals sustaining low-functioning upper limb hemiparesis, who otherwise have poorer residual function. For these individuals, alternative motor rehabilitation strategies are currently needed. In this paper, we will review upper limb immobilisation studies that have been conducted with healthy adult humans and animals. Then, we will discuss how the findings from these studies could inspire the creation of a neural plasticity model that is likely to be of particular relevance to the context of motor rehabilitation after stroke. For instance, as will be elaborated, such model could contribute to the development of alternative motor rehabilitation strategies for treating poststroke upper limb hemiparesis. The implications of the findings from those immobilisation studies for contemporary motor rehabilitation strategies will also be discussed and perspectives for future research in this arena will be provided as well.
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Affiliation(s)
- Leonardo Furlan
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK
| | - Adriana Bastos Conforto
- Neurology Clinical Division, Clinics Hospital, São Paulo University, Avenida Dr. Enéas C. Aguiar 255/5084, 05403-010 São Paulo, SP, Brazil
- Instituto de Ensino e Pesquisa, Hospital Israelita Albert Einstein, Avenida Albert Einstein 627/701, 05601-901 São Paulo, SP, Brazil
| | - Leonardo G. Cohen
- Human Cortical Physiology and Stroke Rehabilitation Section, National Institutes of Neurological Disorders and Stroke, National Institutes of Health, Building 10, Room 7D54, Bethesda, MD 20892, USA
| | - Annette Sterr
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK
- Neurology Clinical Division, Clinics Hospital, São Paulo University, Avenida Dr. Enéas C. Aguiar 255/5084, 05403-010 São Paulo, SP, Brazil
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Investigation of the effect of EEG-BCI on the simultaneous execution of flight simulation and attentional tasks. Med Biol Eng Comput 2015; 54:1503-13. [PMID: 26645694 DOI: 10.1007/s11517-015-1420-6] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2015] [Accepted: 11/11/2015] [Indexed: 12/20/2022]
Abstract
Brain-computer interfaces (BCIs) are widely used for clinical applications and exploited to design robotic and interactive systems for healthy people. We provide evidence to control a sensorimotor electroencephalographic (EEG) BCI system while piloting a flight simulator and attending a double attentional task simultaneously. Ten healthy subjects were trained to learn how to manage a flight simulator, use the BCI system, and answer to the attentional tasks independently. Afterward, the EEG activity was collected during a first flight where subjects were required to concurrently use the BCI, and a second flight where they were required to simultaneously use the BCI and answer to the attentional tasks. Results showed that the concurrent use of the BCI system during the flight simulation does not affect the flight performances. However, BCI performances decrease from the 83 to 63 % while attending additional alertness and vigilance tasks. This work shows that it is possible to successfully control a BCI system during the execution of multiple tasks such as piloting a flight simulator with an extra cognitive load induced by attentional tasks. Such framework aims to foster the knowledge on BCI systems embedded into vehicles and robotic devices to allow the simultaneous execution of secondary tasks.
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Real-time EEG feedback during simultaneous EEG–fMRI identifies the cortical signature of motor imagery. Neuroimage 2015; 114:438-47. [DOI: 10.1016/j.neuroimage.2015.04.020] [Citation(s) in RCA: 114] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2014] [Revised: 02/27/2015] [Accepted: 04/07/2015] [Indexed: 02/02/2023] Open
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Liu Y, Zhao Q, Zhang L. Uncorrelated Multiway Discriminant Analysis for Motor Imagery EEG Classification. Int J Neural Syst 2015; 25:1550013. [DOI: 10.1142/s0129065715500136] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Motor imagery-based brain–computer interfaces (BCIs) training has been proved to be an effective communication system between human brain and external devices. A practical problem in BCI-based systems is how to correctly and efficiently identify and extract subject-specific features from the blurred scalp electroencephalography (EEG) and translate those features into device commands in order to control external devices. In real BCI-based applications, we usually define frequency bands and channels configuration that related to brain activities beforehand. However, a steady configuration usually loses effects due to individual variability among different subjects in practical applications. In this study, a robust tensor-based method is proposed for a multiway discriminative subspace extraction from tensor-represented EEG data, which performs well in motor imagery EEG classification without the prior neurophysiologic knowledge like channels configuration and active frequency bands. Motor imagery EEG patterns in spatial-spectral-temporal domain are detected directly from the multidimensional EEG, which may provide insights to the underlying cortical activity patterns. Extensive experiment comparisons have been performed on a benchmark dataset from the famous BCI competition III as well as self-acquired data from healthy subjects and stroke patients. The experimental results demonstrate the superior performance of the proposed method over the contemporary methods.
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Affiliation(s)
- Ye Liu
- Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Qibin Zhao
- Laboratory for Advanced Brain Signal Processing, Brain Science Institute, RIKEN, Saitama, Japan
| | - Liqing Zhang
- Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
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Zich C, Debener S, De Vos M, Frerichs S, Maurer S, Kranczioch C. Lateralization patterns of covert but not overt movements change with age: An EEG neurofeedback study. Neuroimage 2015; 116:80-91. [PMID: 25979668 DOI: 10.1016/j.neuroimage.2015.05.009] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2014] [Revised: 04/23/2015] [Accepted: 05/05/2015] [Indexed: 01/10/2023] Open
Abstract
The mental practice of movements has been suggested as a promising add-on therapy to facilitate motor recovery after stroke. In the case of mentally practised movements, electroencephalogram (EEG) can be utilized to provide feedback about an otherwise covert act. The main target group for such an intervention are elderly patients, though research so far is largely focused on young populations (<30 years). The present study therefore aimed to examine the influence of age on the neural correlates of covert movements (CMs) in a real-time EEG neurofeedback framework. CM-induced event-related desynchronization (ERD) was studied in young (mean age: 23.6 years) and elderly (mean age: 62.7 years) healthy adults. Participants performed covert and overt hand movements. CMs were based on kinesthetic motor imagery (MI) or quasi-movements (QM). Based on previous studies investigating QM in the mu frequency range (8-13Hz) QM were expected to result in more lateralized ERD% patterns and accordingly higher classification accuracies. Independent of CM strategy the elderly were characterized by a significantly reduced lateralization of ERD%, due to stronger ipsilateral ERD%, and in consequence, reduced classification accuracies. QM were generally perceived as more vivid, but no differences were evident between MI and QM in ERD% or classification accuracies. EEG feedback enhanced task-related activity independently of strategy and age. ERD% measures of overt and covert movements were strongly related in young adults, whereas in the elderly ERD% lateralization is dissociated. In summary, we did not find evidence in support of more pronounced ERD% lateralization patterns in QM. Our finding of a less lateralized activation pattern in the elderly is in accordance to previous research and with the idea that compensatory processes help to overcome neurodegenerative changes related to normal ageing. Importantly, it indicates that EEG neurofeedback studies should place more emphasis on the age of the potential end-users.
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Affiliation(s)
- Catharina Zich
- Neuropsychology Lab, Department of Psychology, European Medical School, University of Oldenburg, Germany.
| | - Stefan Debener
- Neuropsychology Lab, Department of Psychology, European Medical School, University of Oldenburg, Germany; Cluster of Excellence Hearing4all, University of Oldenburg, Germany; Research Center Neurosensory Systems, University of Oldenburg, Germany
| | - Maarten De Vos
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, UK
| | - Stella Frerichs
- Neuropsychology Lab, Department of Psychology, European Medical School, University of Oldenburg, Germany
| | - Stefanie Maurer
- Neuropsychology Lab, Department of Psychology, European Medical School, University of Oldenburg, Germany
| | - Cornelia Kranczioch
- Neuropsychology Lab, Department of Psychology, European Medical School, University of Oldenburg, Germany; Research Center Neurosensory Systems, University of Oldenburg, Germany
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Bleichner MG, Lundbeck M, Selisky M, Minow F, Jäger M, Emkes R, Debener S, De Vos M. Exploring miniaturized EEG electrodes for brain-computer interfaces. An EEG you do not see? Physiol Rep 2015; 3:3/4/e12362. [PMID: 25847919 PMCID: PMC4425967 DOI: 10.14814/phy2.12362] [Citation(s) in RCA: 65] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
Electroencephalography (EEG) allows the study of the brain–behavior relationship in humans. Most of what we have learned with EEG was through observing the brain–behavior relationship under well-controlled laboratory conditions. However, by reducing “normal” behavior to a minimum the ecological validity of the results can be limited. Recent developments toward mobile EEG solutions allow to study the brain–behavior relationship outside the laboratory in more natural situations. Besides mobility and robustness with respect to motion, mobile EEG systems should also interfere as little as possible with the participant's behavior. For example, natural interaction with other people could be hindered when it is obvious that a participant wears an EEG cap. This study evaluates the signal quality obtained with an unobtrusive solution for EEG monitoring through the integration of miniaturized EEG ton-electrodes into both a discreet baseball cap and an individualized ear piece. We show that such mini electrodes located at scalp and ear locations can reliably record event related potentials in a P300 brain–computer–interface application.
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Affiliation(s)
- Martin G Bleichner
- Neuropsychology Lab, Department of Psychology, European Medical School, University of Oldenburg, Oldenburg, Germany Cluster of Excellence Hearing4all, University of Oldenburg, Oldenburg, Germany
| | - Micha Lundbeck
- Neuropsychology Lab, Department of Psychology, European Medical School, University of Oldenburg, Oldenburg, Germany
| | - Matthias Selisky
- Neuropsychology Lab, Department of Psychology, European Medical School, University of Oldenburg, Oldenburg, Germany
| | | | - Manuela Jäger
- Neuropsychology Lab, Department of Psychology, European Medical School, University of Oldenburg, Oldenburg, Germany
| | - Reiner Emkes
- Neuropsychology Lab, Department of Psychology, European Medical School, University of Oldenburg, Oldenburg, Germany
| | - Stefan Debener
- Neuropsychology Lab, Department of Psychology, European Medical School, University of Oldenburg, Oldenburg, Germany Cluster of Excellence Hearing4all, University of Oldenburg, Oldenburg, Germany Neurosensory Science, University of Oldenburg, Oldenburg, Germany
| | - Maarten De Vos
- Neuropsychology Lab, Department of Psychology, European Medical School, University of Oldenburg, Oldenburg, Germany Institute of Biomedical Engineering, Department of Engineering, University Oxford, Oxford, UK
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Wrzus C, Mehl MR. Lab And/Or Field? Measuring Personality Processes and Their Social Consequences. EUROPEAN JOURNAL OF PERSONALITY 2015. [DOI: 10.1002/per.1986] [Citation(s) in RCA: 133] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
How can researchers study personality processes and their social consequences? In our methodology overview, we first introduce ambulatory assessment methods, which repeatedly measure experiences, physiology and behaviour in people's daily lives based on real–time assessments of self–reports, physiological activity and behavioural observations. Then, we describe methods suitable for assessing personality processes in laboratory settings: self–reports on interpersonal perception, physiological measurements and behavioural observation. We discuss the combination of field and laboratory assessment methods based on their respective strengths and limitations and then highlight ethical issues surrounding the use of these methods. Finally, we propose future avenues for how developments in mobile technology can be used to advance personality research. The increasing availability and the decreasing costs of smartphones, wearable sensors and Internet connectivity offer unique potentials for further understanding the processes underlying how personality exerts broad and important social consequences. Copyright © 2015 European Association of Personality Psychology
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De Vos M, Debener S. Mobile EEG: towards brain activity monitoring during natural action and cognition. Int J Psychophysiol 2013; 91:1-2. [PMID: 24144634 DOI: 10.1016/j.ijpsycho.2013.10.008] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Affiliation(s)
- Maarten De Vos
- Methods in Neurocognitive Psychology, Department of Psychology, University of Oldenburg, Germany; Research Center Neurosensory Science, University of Oldenburg, Germany; Cluster of Excellence Hearing4all, University of Oldenburg, Germany.
| | - Stefan Debener
- Neuropsychology Lab, Department of Psychology, University of Oldenburg, Germany; Research Center Neurosensory Science, University of Oldenburg, Germany; Cluster of Excellence Hearing4all, University of Oldenburg, Germany
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