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  1. Article ; Online: A Comprehensive Review of Endogenous EEG-Based BCIs for Dynamic Device Control.

    Padfield, Natasha / Camilleri, Kenneth / Camilleri, Tracey / Fabri, Simon / Bugeja, Marvin

    Sensors (Basel, Switzerland)

    2022  Volume 22, Issue 15

    Abstract: Electroencephalogram (EEG)-based brain-computer interfaces (BCIs) provide a novel approach for controlling external devices. BCI technologies can be important enabling technologies for people with severe mobility impairment. Endogenous paradigms, which ... ...

    Abstract Electroencephalogram (EEG)-based brain-computer interfaces (BCIs) provide a novel approach for controlling external devices. BCI technologies can be important enabling technologies for people with severe mobility impairment. Endogenous paradigms, which depend on user-generated commands and do not need external stimuli, can provide intuitive control of external devices. This paper discusses BCIs to control various physical devices such as exoskeletons, wheelchairs, mobile robots, and robotic arms. These technologies must be able to navigate complex environments or execute fine motor movements. Brain control of these devices presents an intricate research problem that merges signal processing and classification techniques with control theory. In particular, obtaining strong classification performance for endogenous BCIs is challenging, and EEG decoder output signals can be unstable. These issues present myriad research questions that are discussed in this review paper. This review covers papers published until the end of 2021 that presented BCI-controlled dynamic devices. It discusses the devices controlled, EEG paradigms, shared control, stabilization of the EEG signal, traditional machine learning and deep learning techniques, and user experience. The paper concludes with a discussion of open questions and avenues for future work.
    MeSH term(s) Algorithms ; Brain-Computer Interfaces ; Electroencephalography/methods ; Humans ; Machine Learning ; Signal Processing, Computer-Assisted
    Language English
    Publishing date 2022-08-03
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2052857-7
    ISSN 1424-8220 ; 1424-8220
    ISSN (online) 1424-8220
    ISSN 1424-8220
    DOI 10.3390/s22155802
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: BCI-controlled wheelchairs: end-users' perceptions, needs, and expectations, an interview-based study.

    Padfield, Natasha / Agius Anastasi, Andrei / Camilleri, Tracey / Fabri, Simon / Bugeja, Marvin / Camilleri, Kenneth

    Disability and rehabilitation. Assistive technology

    2023  Volume 19, Issue 4, Page(s) 1539–1551

    Abstract: Purpose: Brain-computer interface (BCI)-controlled wheelchairs have the potential to improve the independence of people with mobility impairments. The low uptake of BCI devices has been linked to a lack of knowledge among researchers of the needs of end- ...

    Abstract Purpose: Brain-computer interface (BCI)-controlled wheelchairs have the potential to improve the independence of people with mobility impairments. The low uptake of BCI devices has been linked to a lack of knowledge among researchers of the needs of end-users that should influence BCI development.
    Materials and methods: This study used semi-structured interviews to learn about the perceptions, needs, and expectations of spinal cord injury (SCI) patients with regards to a BCI-controlled wheelchair. Topics discussed in the interview include: paradigms, shared control, safety, robustness, channel selection, hardware, and experimental design. The interviews were recorded and then transcribed. Analysis was carried out using coding based on grounded theory principles.
    Results: The majority of participants had a positive view of BCI-controlled wheelchair technology and were willing to use the technology. Core issues were raised regarding safety, cost and aesthetics. Interview discussions were linked to state-of-the-art BCI technology. The results challenge the current reliance of researchers on the motor-imagery paradigm by suggesting end-users expect highly intuitive paradigms. There also needs to be a stronger focus on obstacle avoidance and safety features in BCI wheelchairs. Finally, the development of control approaches that can be personalized for individual users may be instrumental for widespread adoption of these devices.
    Conclusions: This study, based on interviews with SCI patients, indicates that BCI-controlled wheelchairs are a promising assistive technology that would be well received by end-users. Recommendations for a more person-centered design of BCI controlled wheelchairs are made and clear avenues for future research are identified.
    MeSH term(s) Humans ; Wheelchairs ; Male ; Brain-Computer Interfaces ; Female ; Adult ; Spinal Cord Injuries/rehabilitation ; Middle Aged ; Interviews as Topic ; Disabled Persons/rehabilitation ; Equipment Design ; Perception ; Aged
    Language English
    Publishing date 2023-05-11
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2221782-4
    ISSN 1748-3115 ; 1748-3107
    ISSN (online) 1748-3115
    ISSN 1748-3107
    DOI 10.1080/17483107.2023.2211602
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 6301: Show issues Location:
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  3. Article ; Online: A review of foot pose and trajectory estimation methods using inertial and auxiliary sensors for kinematic gait analysis.

    Okkalidis, Nikiforos / Camilleri, Kenneth P / Gatt, Alfred / Bugeja, Marvin K / Falzon, Owen

    Biomedizinische Technik. Biomedical engineering

    2020  

    Abstract: The use of foot mounted inertial and other auxiliary sensors for kinematic gait analysis has been extensively investigated during the last years. Although, these sensors still yield less accurate results than those obtained employing optical motion ... ...

    Abstract The use of foot mounted inertial and other auxiliary sensors for kinematic gait analysis has been extensively investigated during the last years. Although, these sensors still yield less accurate results than those obtained employing optical motion capture systems, the miniaturization and their low cost have allowed the estimation of kinematic spatiotemporal parameters in laboratory conditions and real life scenarios. The aim of this work was to present a comprehensive approach of this scientific area through a systematic literature research, breaking down the state-of-the-art methods into three main parts: (1) zero velocity interval detection techniques; (2) assumptions and sensors' utilization; (3) foot pose and trajectory estimation methods. Published articles from 1995 until December of 2018 were searched in the PubMed, IEEE Xplore and Google Scholar databases. The research was focused on two categories: (a) zero velocity interval detection methods; and (b) foot pose and trajectory estimation methods. The employed assumptions and the potential use of the sensors have been identified from the retrieved articles. Technical characteristics, categorized methodologies, application conditions, advantages and disadvantages have been provided, while, for the first time, assumptions and sensors' utilization have been identified, categorized and are presented in this review. Considerable progress has been achieved in gait parameters estimation on constrained laboratory environments taking into account assumptions such as a person walking on a flat floor. On the contrary, methods that rely on less constraining assumptions, and are thus applicable in daily life, led to less accurate results. Rule based methods have been mainly used for the detection of the zero velocity intervals, while more complex techniques have been proposed, which may lead to more accurate gait parameters. The review process has shown that presently the best-performing methods for gait parameter estimation make use of inertial sensors combined with auxiliary sensors such as ultrasonic sensors, proximity sensors and cameras. However, the experimental evaluation protocol was much more thorough, when single inertial sensors were used. Finally, it has been highlighted that the accuracy of setups using auxiliary sensors may further be improved by collecting measurements during the whole foot movement and not only partially as is currently the practice. This review has identified the need for research and development of methods and setups that allow for the robust estimation of kinematic gait parameters in unconstrained environments and under various gait profiles.
    Language English
    Publishing date 2020-06-25
    Publishing country Germany
    Document type Journal Article ; Review
    ZDB-ID 120817-2
    ISSN 1862-278X ; 0013-5585
    ISSN (online) 1862-278X
    ISSN 0013-5585
    DOI 10.1515/bmt-2019-0163
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: A multi-segment modelling approach for foot trajectory estimation using inertial sensors.

    Okkalidis, Nikiforos / Marinakis, George / Gatt, Alfred / Bugeja, Marvin K / Camilleri, Kenneth P / Falzon, Owen

    Gait & posture

    2019  Volume 75, Page(s) 22–27

    Abstract: Background: Kinematic gait analysis employing multi-segment foot models has been mainly conducted in laboratories by means of optical motion capture systems. This type of process requires considerable setup time and is constrained by a limited capture ... ...

    Abstract Background: Kinematic gait analysis employing multi-segment foot models has been mainly conducted in laboratories by means of optical motion capture systems. This type of process requires considerable setup time and is constrained by a limited capture space. A procedure involving the use of multiple inertial measurement units (IMUs) is proposed to overcome these limitations.
    Research question: This study presents a new approach for the estimation of the trajectories of a multi-segment foot model by means of multiple IMUs.
    Methods: To test the proposed method, a system consisting of four IMUs attached to the shank, heel, dorsum and toes segments of the foot, was considered. The performance of the proposed method was compared to that of a conventional method using IMUs adopted from the literature. In addition, an optical motion capture system was used as a reference to assess the performance of the implemented methods.
    Results: Employing the suggested method, all trajectory directions of the shank, heel and dorsum segments, as well as the Z (yaw) direction of the toes segment, have exhibited an error reduction varying between 8% and 55%. However, X (roll) and Y (pitch) direction of the toes segment presented an error increase of 17% and 26%, respectively. The estimation of the vertical displacement, corresponding to the foot clearance, was improved for all segments, resulting in a final mean accuracy and precision of 3.5 ± 2.8 cm, 2.7 ± 2.1 cm, 0.8 ± 0.7 cm and 1.1 ± 0.9 cm for the shank, heel, dorsum and toes segments, respectively.
    Significance: It has been demonstrated that as an alternative to tracking each foot segment separately, the fusion of multiple IMU measurements using kinematic equations, considerably improves the estimated trajectories, especially when considering vertical foot displacements. The proposed method could complement the use of smaller and cheaper sensors, while still matching the same performance of other published methods, making the suggested approach very attractive for real life applications.
    MeSH term(s) Accelerometry/instrumentation ; Adult ; Algorithms ; Biomechanical Phenomena ; Equipment Design ; Foot/physiology ; Gait/physiology ; Healthy Volunteers ; Humans ; Reproducibility of Results
    Language English
    Publishing date 2019-09-22
    Publishing country England
    Document type Journal Article
    ZDB-ID 1162323-8
    ISSN 1879-2219 ; 0966-6362
    ISSN (online) 1879-2219
    ISSN 0966-6362
    DOI 10.1016/j.gaitpost.2019.09.022
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 3804: Show issues Location:
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    Jg. 1995 - 2021: Lesesall (2.OG)
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  5. Article ; Online: Dual adaptive dynamic control of mobile robots using neural networks.

    Bugeja, Marvin K / Fabri, Simon G / Camilleri, Liberato

    IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society

    2009  Volume 39, Issue 1, Page(s) 129–141

    Abstract: This paper proposes two novel dual adaptive neural control schemes for the dynamic control of nonholonomic mobile robots. The two schemes are developed in discrete time, and the robot's nonlinear dynamic functions are assumed to be unknown. Gaussian ... ...

    Abstract This paper proposes two novel dual adaptive neural control schemes for the dynamic control of nonholonomic mobile robots. The two schemes are developed in discrete time, and the robot's nonlinear dynamic functions are assumed to be unknown. Gaussian radial basis function and sigmoidal multilayer perceptron neural networks are used for function approximation. In each scheme, the unknown network parameters are estimated stochastically in real time, and no preliminary offline neural network training is used. In contrast to other adaptive techniques hitherto proposed in the literature on mobile robots, the dual control laws presented in this paper do not rely on the heuristic certainty equivalence property but account for the uncertainty in the estimates. This results in a major improvement in tracking performance, despite the plant uncertainty and unmodeled dynamics. Monte Carlo simulation and statistical hypothesis testing are used to illustrate the effectiveness of the two proposed stochastic controllers as applied to the trajectory-tracking problem of a differentially driven wheeled mobile robot.
    MeSH term(s) Algorithms ; Analysis of Variance ; Artificial Intelligence ; Biomechanical Phenomena ; Computer Simulation ; Monte Carlo Method ; Neural Networks (Computer) ; Nonlinear Dynamics ; Normal Distribution ; Robotics/methods ; Statistics, Nonparametric ; Stochastic Processes
    Language English
    Publishing date 2009-02
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 1941-0492
    ISSN (online) 1941-0492
    DOI 10.1109/TSMCB.2008.2002851
    Database MEDical Literature Analysis and Retrieval System OnLINE

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