Training

Deep Neural Network-based Empirical Mode Decomposition for Motor Imagery EEG Classification
Deep Neural Network-based Empirical Mode Decomposition for Motor Imagery EEG Classification 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Motor imagery refers to the brain’s response during the mental simulation of physical activities, which can be detected through electroencephalogram (EEG) signals. However, EEG signals exhibit a low signal-to-noise ratio… read more

AMBER: A Device for Hand Motor and Cognitive Rehabilitation—Development and Proof of Concept
AMBER: A Device for Hand Motor and Cognitive Rehabilitation—Development and Proof of Concept 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Stroke survivors usually exhibit concurrent motor and cognitive impairment. Historically, rehabilitation strategies post-stroke occur separately in terms of motor and cognitive functions. However, recent studies show that hand motor interventions… read more

MovePort: Multimodal Dataset of EMG, IMU, MoCap, and Insole Pressure for Analyzing Abnormal Movements and Postures in Rehabilitation Training
MovePort: Multimodal Dataset of EMG, IMU, MoCap, and Insole Pressure for Analyzing Abnormal Movements and Postures in Rehabilitation Training 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
In most real world rehabilitation training, patients are trained to regain motion capabilities with the aid of functional/epidural electrical stimulation (FES/EES), under the support of gravity-assist systems to prevent falls.… read more

Feasibility of Augmenting Ankle Exoskeleton Walking Performance With Step Length Biofeedback in Individuals With Cerebral Palsy
Author(s)3: Ying Fang, Zachary F. Lerner
Feasibility of Augmenting Ankle Exoskeleton Walking Performance With Step Length Biofeedback in Individuals With Cerebral Palsy 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

Most people with cerebral palsy (CP) suffer from impaired walking ability and pathological gait patterns. Seeking to improve the effectiveness of gait training in this patient population, this study developed…

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Deep Learning for Accelerometric Data Assessment and Ataxic Gait Monitoring
Author(s)3: Aleš Procházka, Ondřej Dostál, Pavel Cejnar, Hagar Ibrahim Mohamed, Zbyšek Pavelek, Martin Vališ, Oldřich Vyšata
Deep Learning for Accelerometric Data Assessment and Ataxic Gait Monitoring 526 336 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

Ataxic gait monitoring and assessment of neurological disorders belong to important multidisciplinary areas that are supported by digital signal processing methods and machine learning tools. This paper presents the possibility…

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Deep Learning for Electromyographic Hand Gesture Signal Classification Using Transfer Learning

Deep Learning for Electromyographic Hand Gesture Signal Classification Using Transfer Learning
Author(s)3: Ulysse Côté-Allard, Cheikh Latyr Fall, Alexandre Drouin, Alexandre Campeau-Lecours, Clément Gosselin, Kyrre Glette, François Laviolette, Benoit Gosselin
Deep Learning for Electromyographic Hand Gesture Signal Classification Using Transfer Learning 780 435 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

        In recent years, deep learning algorithms have become increasingly more prominent for their unparalleled ability to automatically learn discriminant features from large amounts of data. However, within the field…

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Synergy-Based FES for Post-Stroke Rehabilitation of Upper-Limb Motor Functions

Synergy-Based FES for Post-Stroke Rehabilitation of Upper-Limb Motor Functions
Author(s)3: Chuanxin M. Niu, Yong Bao, Cheng Zhuang, Si Li, Tong Wang, Lijun Cui, Qing Xie, Ning Lan
Synergy-Based FES for Post-Stroke Rehabilitation of Upper-Limb Motor Functions 780 435 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

        Functional electrical stimulation (FES) is capable of activating muscles that are under-recruited in neurological diseases, such as stroke. Therefore, FES provides a promising technology for assisting upper-limb motor functions…

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Unimanual Versus Bimanual Motor Imagery

Unimanual vs Bimanual Motor Imagery Classifiers for Assistive and Rehabilitative Brain Computer Interfaces
Author(s)3: Vuckovic Aleksandra, Pangaro Sara, Putri Finda
Unimanual vs Bimanual Motor Imagery Classifiers for Assistive and Rehabilitative Brain Computer Interfaces 780 435 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

   Bimanual movements are an integral part of everyday activities and are often included in rehabilitation therapies. Yet electroencephalography (EEG) based assistive and rehabilitative brain computer interface (BCI) systems typically…

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Biomedical Serious Game System for Balance Rehabilitation of Hemiparetic Stroke Patients
Author(s)3: F. Noveletto, A.V. Soares, B.A. Mello, C.N. Sevegnani, F.L.F. Eichinger, marcelodashounsell, P. Bertemes-Filho
Biomedical Serious Game System for Balance Rehabilitation of Hemiparetic Stroke Patients 345 229 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

Hemiparetic stroke patients can have several muscular and postural disorders which compromise their balance. Serious Games (SG) emerged as a new approach to enhance conventional treatment by making it a…

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Can Wii Balance? Evaluating a Stepping Game for Older Adults
Author(s)3: Mark Deacon, John Parsons, Sean Mathieson, T. Claire Davies
Can Wii Balance? Evaluating a Stepping Game for Older Adults 300 541 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

    Decline in balance control is an issue for older adults as it leads to an increased risk of falling which may result in serious injury. Mitigating this risk may…

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