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Londral A. Assistive Technologies for Communication Empower Patients With ALS to Generate and Self-Report Health Data. Front Neurol 2022; 13:867567. [PMID: 35557618 PMCID: PMC9090469 DOI: 10.3389/fneur.2022.867567] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 03/25/2022] [Indexed: 11/25/2022] Open
Affiliation(s)
- Ana Londral
- Value for Health CoLAB, Lisbon, Portugal
- Comprehensive Health Research Center, Nova Medical School, Nova University of Lisbon, Lisbon, Portugal
- *Correspondence: Ana Londral
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Elcoro M, Backer A. Murray Sidman and Patient H. M.: The role of behavior analysis in the emergence of collaborative modern neuroscience. J Exp Anal Behav 2020; 115:242-254. [PMID: 33319374 DOI: 10.1002/jeab.656] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 11/12/2020] [Accepted: 11/15/2020] [Indexed: 11/09/2022]
Abstract
The intersection of the lives of 2 essential individuals in science, behavior analyst Murray Sidman (1923-2019), and Henry G. Molaison also known as Patient H.M. (1926-2008), warrants examination as it highlights the role of behavior analysis and other disciplines in the emergence of modern neuroscience and a collaborative approach to science. This paper describes the historical context and content of two publications by Sidman in which Molaison served as a research participant. The goal of the present paper is to emphasize this little-known facet of Sidman's rich career and to highlight the pioneering role of behavior analysis, and particularly the work of Murray Sidman, in the emergence of collaborative modern neuroscience.
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Pinto S, Quintarelli S, Silani V. New technologies and Amyotrophic Lateral Sclerosis - Which step forward rushed by the COVID-19 pandemic? J Neurol Sci 2020; 418:117081. [PMID: 32882437 PMCID: PMC7403097 DOI: 10.1016/j.jns.2020.117081] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 07/09/2020] [Accepted: 08/01/2020] [Indexed: 12/11/2022]
Abstract
Amyotrophic Lateral Sclerosis (ALS) is a fast-progressive neurodegenerative disease leading to progressive physical immobility with usually normal or mild cognitive and/or behavioural involvement. Many patients are relatively young, instructed, sensitive to new technologies, and professionally active when developing the first symptoms. Older patients usually require more time, encouragement, reinforcement and a closer support but, nevertheless, selecting user-friendly devices, provided earlier in the course of the disease, and engaging motivated carers may overcome many technological barriers. ALS may be considered a model for neurodegenerative diseases to further develop and test new technologies. From multidisciplinary teleconsults to telemonitoring of the respiratory function, telemedicine has the potentiality to embrace other fields, including nutrition, physical mobility, and the interaction with the environment. Brain-computer interfaces and eye tracking expanded the field of augmentative and alternative communication in ALS but their potentialities go beyond communication, to cognition and robotics. Virtual reality and different forms of artificial intelligence present further interesting possibilities that deserve to be investigated. COVID-19 pandemic is an unprecedented opportunity to speed up the development and implementation of new technologies in clinical practice, improving the daily living of both ALS patients and carers. The present work reviews the current technologies for ALS patients already in place or being under evaluation with published publications, prompted by the COVID-19 pandemic.
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Affiliation(s)
- Susana Pinto
- Translational and Clinical Physiology Unit, Instituto de Medicina Molecular, Lisbon, Portugal.
| | - Stefano Quintarelli
- AgID - Italian digital agency and Clusit - Italian Computer Security Association, Italy
| | - Vincenzo Silani
- Department of Neurology-Stroke Unit and Laboratory of Neuroscience, Istituto Auxologico Italiano IRCCS - Department of Pathophysiology and Transplantation, “Dino Ferrari” Center and Center for Neurotechnology and Brain Therapeutics, Università degli Studi di Milano, Milan, Italy
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Czyżewski A, Kurowski A, Odya P, Szczuko P. Multifactor consciousness level assessment of participants with acquired brain injuries employing human-computer interfaces. Biomed Eng Online 2020; 19:2. [PMID: 31924202 PMCID: PMC6954635 DOI: 10.1186/s12938-019-0746-y] [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: 01/31/2019] [Accepted: 12/31/2019] [Indexed: 11/27/2022] Open
Abstract
Background A lack of communication with people suffering from acquired brain injuries may lead to drawing erroneous conclusions regarding the diagnosis or therapy of patients. Information technology and neuroscience make it possible to enhance the diagnostic and rehabilitation process of patients with traumatic brain injury or post-hypoxia. In this paper, we present a new method for evaluation possibility of communication and the assessment of such patients’ state employing future generation computers extended with advanced human–machine interfaces. Methods First, the hearing abilities of 33 participants in the state of coma were evaluated using auditory brainstem response measurements (ABR). Next, a series of interactive computer-based exercise sessions were performed with the therapist’s assistance. Participants’ actions were monitored with an eye-gaze tracking (EGT) device and with an electroencephalogram EEG monitoring headset. The data gathered were processed with the use of data clustering techniques. Results Analysis showed that the data gathered and the computer-based methods developed for their processing are suitable for evaluating the participants’ responses to stimuli. Parameters obtained from EEG signals and eye-tracker data were correlated with Glasgow Coma Scale (GCS) scores and enabled separation between GCS-related classes. The results show that in the EEG and eye-tracker signals, there are specific consciousness-related states discoverable. We observe them as outliers in diagrams on the decision space generated by the autoencoder. For this reason, the numerical variable that separates particular groups of people with the same GCS is the variance of the distance of points from the cluster center that the autoencoder generates. The higher the GCS score, the greater the variance in most cases. The results proved to be statistically significant in this context. Conclusions The results indicate that the method proposed may help to assess the consciousness state of participants in an objective manner.
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Affiliation(s)
- Andrzej Czyżewski
- Multimedia Systems Department, Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, Gdańsk, Poland
| | - Adam Kurowski
- Multimedia Systems Department, Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, Gdańsk, Poland.
| | - Piotr Odya
- Multimedia Systems Department, Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, Gdańsk, Poland
| | - Piotr Szczuko
- Multimedia Systems Department, Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, Gdańsk, Poland
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Brain-Computer Interface for Clinical Purposes: Cognitive Assessment and Rehabilitation. BIOMED RESEARCH INTERNATIONAL 2017; 2017:1695290. [PMID: 28913349 PMCID: PMC5587953 DOI: 10.1155/2017/1695290] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 03/30/2017] [Revised: 06/13/2017] [Accepted: 07/03/2017] [Indexed: 12/11/2022]
Abstract
Alongside the best-known applications of brain-computer interface (BCI) technology for restoring communication abilities and controlling external devices, we present the state of the art of BCI use for cognitive assessment and training purposes. We first describe some preliminary attempts to develop verbal-motor free BCI-based tests for evaluating specific or multiple cognitive domains in patients with Amyotrophic Lateral Sclerosis, disorders of consciousness, and other neurological diseases. Then we present the more heterogeneous and advanced field of BCI-based cognitive training, which has its roots in the context of neurofeedback therapy and addresses patients with neurological developmental disorders (autism spectrum disorder and attention-deficit/hyperactivity disorder), stroke patients, and elderly subjects. We discuss some advantages of BCI for both assessment and training purposes, the former concerning the possibility of longitudinally and reliably evaluating cognitive functions in patients with severe motor disabilities, the latter regarding the possibility of enhancing patients' motivation and engagement for improving neural plasticity. Finally, we discuss some present and future challenges in the BCI use for the described purposes.
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The brain's silent messenger: using selective attention to decode human thought for brain-based communication. J Neurosci 2013; 33:9385-93. [PMID: 23719806 DOI: 10.1523/jneurosci.5577-12.2013] [Citation(s) in RCA: 58] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
Abstract
The interpretation of human thought from brain activity, without recourse to speech or action, is one of the most provoking and challenging frontiers of modern neuroscience. In particular, patients who are fully conscious and awake, yet, due to brain damage, are unable to show any behavioral responsivity, expose the limits of the neuromuscular system and the necessity for alternate forms of communication. Although it is well established that selective attention can significantly enhance the neural representation of attended sounds, it remains, thus far, untested as a response modality for brain-based communication. We asked whether its effect could be reliably used to decode answers to binary (yes/no) questions. Fifteen healthy volunteers answered questions (e.g., "Do you have brothers or sisters?") in the fMRI scanner, by selectively attending to the appropriate word ("yes" or "no"). Ninety percent of the answers were decoded correctly based on activity changes within the attention network. The majority of volunteers conveyed their answers with less than 3 min of scanning, suggesting that this technique is suited for communication in a reasonable amount of time. Formal comparison with the current best-established fMRI technique for binary communication revealed improved individual success rates and scanning times required to detect responses. This novel fMRI technique is intuitive, easy to use in untrained participants, and reliably robust within brief scanning times. Possible applications include communication with behaviorally nonresponsive patients.
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Ortiz-Rosario A, Adeli H. Brain-computer interface technologies: from signal to action. Rev Neurosci 2013; 24:537-52. [PMID: 24077619 DOI: 10.1515/revneuro-2013-0032] [Citation(s) in RCA: 144] [Impact Index Per Article: 13.1] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2013] [Accepted: 08/21/2013] [Indexed: 01/08/2023]
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Naci L, Monti MM, Cruse D, Kübler A, Sorger B, Goebel R, Kotchoubey B, Owen AM. Brain-computer interfaces for communication with nonresponsive patients. Ann Neurol 2012; 72:312-23. [DOI: 10.1002/ana.23656] [Citation(s) in RCA: 84] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Cipresso P, Carelli L, Solca F, Meazzi D, Meriggi P, Poletti B, Lulé D, Ludolph AC, Silani V, Riva G. The use of P300-based BCIs in amyotrophic lateral sclerosis: from augmentative and alternative communication to cognitive assessment. Brain Behav 2012; 2:479-98. [PMID: 22950051 PMCID: PMC3432970 DOI: 10.1002/brb3.57] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2011] [Revised: 03/06/2012] [Accepted: 03/13/2012] [Indexed: 12/11/2022] Open
Abstract
The use of augmentative and alternative communication (AAC) tools in patients with amyotrophic lateral sclerosis (ALS), as effective means to compensate for the progressive loss of verbal and gestural communication, has been deeply investigated in the recent literature. The development of advanced AAC systems, such as eye-tracking (ET) and brain-computer interface (BCI) devices, allowed to bypass the important motor difficulties present in ALS patients. In particular, BCIs could be used in moderate to severe stages of the disease, since they do not require preserved ocular-motor ability, which is necessary for ET applications. Furthermore, some studies have proved the reliability of BCIs, regardless of the severity of the disease and the level of physical decline. However, the use of BCI in ALS patients still shows some limitations, related to both technical and neuropsychological issues. In particular, a range of cognitive deficits in most ALS patients have been observed. At the moment, no effective verbal-motor free measures are available for the evaluation of ALS patients' cognitive integrity; BCIs could offer a new possibility to administer cognitive tasks without the need of verbal or motor responses, as highlighted by preliminary studies in this field. In this review, we outline the essential features of BCIs systems, considering advantages and challenges of these tools with regard to ALS patients and the main applications developed in this field. We then outline the main findings with regard to cognitive deficits observed in ALS and some preliminary attempts to evaluate them by means of BCIs. The definition of specific cognitive profiles could help to draw flexible approaches tailored on patients' needs. It could improve BCIs efficacy and reduce patients' efforts. Finally, we handle the open question, represented by the use of BCIs with totally locked in patients, who seem unable to reliably learn to use such tool.
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Affiliation(s)
- Pietro Cipresso
- Applied Technology for Neuro‐Psychology Lab, IRCCS Istituto Auxologico Italiano, Milan, Italy
| | - Laura Carelli
- Department of Neurology and Laboratory of Neuroscience ‐ “Dino Ferrari” Center ‐ Università degli Studi di Milano ‐ IRCCS Istituto Auxologico Italiano, Milano, Italy
| | - Federica Solca
- Department of Neurology and Laboratory of Neuroscience ‐ “Dino Ferrari” Center ‐ Università degli Studi di Milano ‐ IRCCS Istituto Auxologico Italiano, Milano, Italy
| | - Daniela Meazzi
- Applied Technology for Neuro‐Psychology Lab, IRCCS Istituto Auxologico Italiano, Milan, Italy
| | - Paolo Meriggi
- Polo Tecnologico–Biomedical Technology Department, Fondazione Don Carlo Gnocchi Onlus, Milano, Italy
| | - Barbara Poletti
- Department of Neurology and Laboratory of Neuroscience ‐ “Dino Ferrari” Center ‐ Università degli Studi di Milano ‐ IRCCS Istituto Auxologico Italiano, Milano, Italy
| | - Dorothée Lulé
- Department of Neurology ‐ University of Ulm, Ulm, Germany
| | | | - Vincenzo Silani
- Department of Neurology and Laboratory of Neuroscience ‐ “Dino Ferrari” Center ‐ Università degli Studi di Milano ‐ IRCCS Istituto Auxologico Italiano, Milano, Italy
| | - Giuseppe Riva
- Applied Technology for Neuro‐Psychology Lab, IRCCS Istituto Auxologico Italiano, Milan, Italy
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Pasqualotto E, Federici S, Belardinelli MO. Toward functioning and usable brain-computer interfaces (BCIs): a literature review. Disabil Rehabil Assist Technol 2011; 7:89-103. [PMID: 21967470 DOI: 10.3109/17483107.2011.589486] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
PURPOSE The aim of this paper is to provide an exhaustive review of the literature about brain-computer interfaces (BCIs) that could be used with these paralysed patients. The electroencephalography (EEG) is the best candidate for the continuous use in the environment of patients' houses, due to its portability and ease of use. For this reason, the present paper will focus on this kind of BCI. Moreover, it is our aim to focus more on the patients, regarding their active role in the modulation of the brain activity. This leads to a differentiation between studies that use an active regulation and studies that use a non-active regulation. METHOD Relevant articles in the BCIs field were selected using MEDLINE and PsycINFO. RESULTS Research through data banks produced 980 results, which were reduced to 127 after exclusion criteria selection. These references were divided in four categories, based on the use of active or non-active regulation, and on the event related potential used. CONCLUSIONS In most of the examined works, the focus was on the development of systems and algorithms able to recognise and classify brain events. Although this kind of research is fundamental, a user-centred point of view was rarely adopted. [Box: see text].
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Affiliation(s)
- Emanuele Pasqualotto
- Institute of Medical Psychology and Behavioral Neurobiology, Eberhard-Karls-University, Tübingen, Germany.
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Royer AS, Rose ML, He B. Goal selection versus process control while learning to use a brain-computer interface. J Neural Eng 2011; 8:036012. [PMID: 21508492 DOI: 10.1088/1741-2560/8/3/036012] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
A brain-computer interface (BCI) can be used to accomplish a task without requiring motor output. Two major control strategies used by BCIs during task completion are process control and goal selection. In process control, the user exerts continuous control and independently executes the given task. In goal selection, the user communicates their goal to the BCI and then receives assistance executing the task. A previous study has shown that goal selection is more accurate and faster in use. An unanswered question is, which control strategy is easier to learn? This study directly compares goal selection and process control while learning to use a sensorimotor rhythm-based BCI. Twenty young healthy human subjects were randomly assigned either to a goal selection or a process control-based paradigm for eight sessions. At the end of the study, the best user from each paradigm completed two additional sessions using all paradigms randomly mixed. The results of this study were that goal selection required a shorter training period for increased speed, accuracy, and information transfer over process control. These results held for the best subjects as well as in the general subject population. The demonstrated characteristics of goal selection make it a promising option to increase the utility of BCIs intended for both disabled and able-bodied users.
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Affiliation(s)
- Audrey S Royer
- Graduate Program in Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
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Min BK, Marzelli MJ, Yoo SS. Neuroimaging-based approaches in the brain–computer interface. Trends Biotechnol 2010; 28:552-60. [DOI: 10.1016/j.tibtech.2010.08.002] [Citation(s) in RCA: 56] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2010] [Revised: 07/26/2010] [Accepted: 08/02/2010] [Indexed: 01/15/2023]
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Bai O, Lin P, Huang D, Fei DY, Floeter MK. Towards a user-friendly brain-computer interface: initial tests in ALS and PLS patients. Clin Neurophysiol 2010; 121:1293-303. [PMID: 20347612 DOI: 10.1016/j.clinph.2010.02.157] [Citation(s) in RCA: 43] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2009] [Revised: 02/02/2010] [Accepted: 02/25/2010] [Indexed: 10/19/2022]
Abstract
OBJECTIVE Patients usually require long-term training for effective EEG-based brain-computer interface (BCI) control due to fatigue caused by the demands for focused attention during prolonged BCI operation. We intended to develop a user-friendly BCI requiring minimal training and less mental load. METHODS Testing of BCI performance was investigated in three patients with amyotrophic lateral sclerosis (ALS) and three patients with primary lateral sclerosis (PLS), who had no previous BCI experience. All patients performed binary control of cursor movement. One ALS patient and one PLS patient performed four-directional cursor control in a two-dimensional domain under a BCI paradigm associated with human natural motor behavior using motor execution and motor imagery. Subjects practiced for 5-10min and then participated in a multi-session study of either binary control or four-directional control including online BCI game over 1.5-2h in a single visit. RESULTS Event-related desynchronization and event-related synchronization in the beta band were observed in all patients during the production of voluntary movement either by motor execution or motor imagery. The online binary control of cursor movement was achieved with an average accuracy about 82.1+/-8.2% with motor execution and about 80% with motor imagery, whereas offline accuracy was achieved with 91.4+/-3.4% with motor execution and 83.3+/-8.9% with motor imagery after optimization. In addition, four-directional cursor control was achieved with an accuracy of 50-60% with motor execution and motor imagery. CONCLUSION Patients with ALS or PLS may achieve BCI control without extended training, and fatigue might be reduced during operation of a BCI associated with human natural motor behavior. SIGNIFICANCE The development of a user-friendly BCI will promote practical BCI applications in paralyzed patients.
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Affiliation(s)
- Ou Bai
- EEG & BCI Laboratory, Department of Biomedical Engineering, Virginia Commonwealth University, Richmond, VA 23284, USA.
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