The aging process is a multifaceted phenomenon that affects cognitive-affective and physical functioning as well as interactions with the environment. Although subjective cognitive decline may be part of normal aging, negative changes objectified as cognitive impairment are present in neurocognitive disorders and functional abilities are most impaired in patients with dementia. Electroencephalography-based brain-machine interfaces (BMI) are being used to assist older people in their daily activities and to improve their quality of life with neuro-rehabilitative applications. This paper provides an overview of BMI used to assist older adults. Both technical issues (detection of signals, extraction of features, classification) and application-related aspects with respect to the users' needs are considered.
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Electroencephalography-Based Brain-Machine Interfaces in Older Adults: A Literature Review.
Bioengineering (Basel)
March 2023
Department of Psychology, Universitá di Torino, 10124 Turin, Italy.
The aging process is a multifaceted phenomenon that affects cognitive-affective and physical functioning as well as interactions with the environment. Although subjective cognitive decline may be part of normal aging, negative changes objectified as cognitive impairment are present in neurocognitive disorders and functional abilities are most impaired in patients with dementia. Electroencephalography-based brain-machine interfaces (BMI) are being used to assist older people in their daily activities and to improve their quality of life with neuro-rehabilitative applications.
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Keio J Med
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Professor, Department of Biosciences and Informatics, Faculty of Science and Technology, Keio University, Yokohama, Japan.
Because recovery from upper limb paralysis after stroke is challenging, compensatory approaches have been the main focus of upper limb rehabilitation. However, based on fundamental and clinical research indicating that the brain has a far greater potential for plastic change than previously thought, functional restorative approaches have become increasingly common. Among such interventions, constraint-induced movement therapy, task-specific training, robotic therapy, neuromuscular electrical stimulation (NMES), mental practice, mirror therapy, and bilateral arm training are recommended in recently published stroke guidelines.
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Am J Phys Med Rehabil
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From the Noninvasive Brain-Machine Interface Systems Laboratory, Department of Electrical and Computer Engineering, University of Houston, Houston, Texas (JLC-V, MB, FZ, KN, AV); Neural Rehabilitation Group, Cajal Institute, Spanish Research Council, Madrid, Spain (MB, JLP); TIRR Memorial Hermann and Department of PM&R, University of Texas Health Sciences Center, Houston, Texas (GEF); Palo Alto Research Center, Inc. (PARC, a Xerox Company), Palo Alto, California (AV); and School of Engineering, Tecnologico de Monterrey, Monterrey, Mexico (JLC-V, GEF, RS, JLP).
Objective: Advancements in robot-assisted gait rehabilitation and brain-machine interfaces may enhance stroke physiotherapy by engaging patients while providing information about robot-induced cortical adaptations. We investigate the feasibility of decoding walking from brain activity in stroke survivors during therapy using a powered exoskeleton integrated with an electroencephalography-based brain-machine interface.
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Int J Neural Syst
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2 Instituto de Investigación de Ingeniería de Aragón (I3A), Departamento de Informática e Ingeniería de Sistemas, University of Zaragoza, María de Luna 1, 50015, Zaragoza, Spain.
Motor rehabilitation based on the association of electroencephalographic (EEG) activity and proprioceptive feedback has been demonstrated as a feasible therapy for patients with paralysis. To promote long-lasting motor recovery, these interventions have to be carried out across several weeks or even months. The success of these therapies partly relies on the performance of the system decoding movement intentions, which normally has to be recalibrated to deal with the nonstationarities of the cortical activity.
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The co-registration of eye tracking and electroencephalography provides a holistic measure of ongoing cognitive processes. Recently, fixation-related potentials have been introduced to quantify the neural activity in such bi-modal recordings. Fixation-related potentials are time-locked to fixation onsets, just like event-related potentials are locked to stimulus onsets.
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