Clinical Aspects for the Application of Robotics in Locomotor Neurorehabilitation

Dietz, Volker

doi:10.1007/978-3-319-28603-7_11

Cited by 5 publications

(3 citation statements)

References 101 publications

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“…However, for rehabilitation purposes, and when no residual EMG is present, a synchronous HCI based on the tasks employed in this study may be the most appropriate solution. This is partly due to ITR being less important in rehabilitation applications, and that movement-related activity is necessary to drive the Hebbian-mechanisms needed for rehabilitation [7], [49].…”

Section: B Limitationsmentioning

confidence: 99%

Investigating the feasibility of combining EEG and EMG for controlling a hybrid human computer interface in patients with spinal cord injury

Leerskov

Rehman

Niazi

et al. 2020

2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE)

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Objective. Human-computer interfaces (HCI) are potential tools for assisting (movement replacement) and rehabilitating (movement restoration) individuals with spinal cord injury (SCI). HCIs based on electroencephalography (EEG) have limited accuracy and hence control options; this could be improved by exploiting potential residual muscle activity (electromyography, EMG). The study objectives were to determine if combined EEG and EMG improves offline singletrial movement classification. Furthermore, the effect of number of classes and detection latency on the accuracies was investigated. Methods. Ten able-bodied and eight SCI subjects performed elbow flexion/extension at three force levels while EEG and EMG were recorded. Temporal and spectral features were extracted from the EEG and Hudgins time domain features were extracted from the EMG in 1-second time windows. The time window was shifted (200-ms shift) over 5second epochs around the movement onset. Each segment was classified in three scenarios (2, 3 or 7 classes) using linear discriminant analysis. Results. The accuracies obtained with EEG (51.2%) was outperformed by EMG (95.5%) and combined EMG and EEG (96.2%). Immediately after the EMG onset, the accuracies increased and rapidly reached a plateau. High accuracies were obtained for the different number of classes. Conclusion and Significance. EMG was crucial for obtaining high accuracies, and potential residual EMG should be exploited in HCIs to improve the performance. Force proved to be a viable option for SCI subjects with residual EMG to increase the number of classes for HCI control. These findings could assist design considerations of HCIs for SCI individuals.

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Section: B Limitationsmentioning

confidence: 99%

Investigating the feasibility of combining EEG and EMG for controlling a hybrid human computer interface in patients with spinal cord injury

Leerskov

Rehman

Niazi

et al. 2020

2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE)

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“…Robotassisted treadmill training has been shown to produce some beneficial effects, especially in patients with severe SCI-induced deficits. 50 Yet, evidence from randomized controlled studies comparing robotic and manual treadmill assistance demonstrate that manual treadmill training outperforms robotic-assisted training. 51,52 This implies that active participation is a crucial element for adaptive neurorehabilitation, and robotic-assisted treadmill training alone may be too passive to induce lasting training effects on adaptive spinal cord plasticity and locomotor recovery.…”

Section: 44mentioning

confidence: 99%

What Is Being Trained? How Divergent Forms of Plasticity Compete To Shape Locomotor Recovery after Spinal Cord Injury

Huie

Morioka

Haefeli

et al. 2017

Journal of Neurotrauma

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Spinal cord injury (SCI) is a devastating syndrome that produces dysfunction in motor and sensory systems, manifesting as chronic paralysis, sensory changes, and pain disorders. The multi-faceted and heterogeneous nature of SCI has made effective rehabilitative strategies challenging. Work over the last 40 years has aimed to overcome these obstacles by harnessing the intrinsic plasticity of the spinal cord to improve functional locomotor recovery. Intensive training after SCI facilitates lower extremity function and has shown promise as a tool for retraining the spinal cord by engaging innate locomotor circuitry in the lumbar cord. As new training paradigms evolve, the importance of appropriate afferent input has emerged as a requirement for adaptive plasticity. The integration of kinematic, sensory, and loading force information must be closely monitored and carefully manipulated to optimize training outcomes. Inappropriate peripheral input may produce lasting maladaptive sensory and motor effects, such as central pain and spasticity. Thus, it is important to closely consider the type of afferent input the injured spinal cord receives. Here we review preclinical and clinical input parameters fostering adaptive plasticity, as well as those producing maladaptive plasticity that may undermine neurorehabilitative efforts. We differentiate between passive (hindlimb unloading [HU], limb immobilization) and active ( peripheral nociception) forms of aberrant input. Furthermore, we discuss the timing of initiating exposure to afferent input after SCI for promoting functional locomotor recovery. We conclude by presenting a candidate rapid synaptic mechanism for maladaptive plasticity after SCI, offering a pharmacological target for restoring the capacity for adaptive spinal plasticity in real time.

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“…La limitación de la marcha es uno de los mayores problemas sufridos por niños con Parálisis Cerebral (PC) [1]. Ello es consecuencia de un daño producido en el sistema nervioso central (SNC) del paciente, y por tanto, se requiere un entrenamiento funcional óptimo para maximizar las mejoras debidas a la terapia [2], lo que por ende, provocará efectos positivos en la calidad de vida de los pacientes y sus familias [3].…”

Section: Introductionunclassified

Entrenamiento robótico de la marcha en pacientes con Parálisis Cerebral: definición de objetivos, propuesta de tratamiento e implementación clínica preliminar

Bayón¹,

Ramírez²,

Rocón³

et al. 2020

XXXVIII Jornadas De Automática: Gijón, 6, 7, Y 8 De Septiembre De 2017

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Todos los derechos reservados. De conformidad con lo dispuesto en la legislación vigente, podrán ser cas�gados con penas de multa y privación de libertad quienes reproduzcan o plagien, en todo o en parte, una obra literaria, ar�s�ca o cien�fica, fijada en cualquier �po y soporte, sin la precep�va autorización. JA2017 Prefacio PrefacioLas Jornadas de Automática se celebran desde hace 40 años en una universidad nacional facilitando el encuentro entre expertos en estaárea en un foro que permite la puesta en común de las nuevas ideas y proyectos en desarrollo. Al mismo tiempo, propician la siempre necesaria colaboración entre investigadores delámbito de la Ingeniería de Control y Automática, así como de campos afines, a la hora de abordar complejos proyectos de investigación multidisciplinares.En esta ocasión, las Jornadas estarán organizadas por la Universidad de Oviedo y se han celebrado del 6 al 8 de septiembre de

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Clinical Aspects for the Application of Robotics in Locomotor Neurorehabilitation

Cited by 5 publications

References 101 publications

Investigating the feasibility of combining EEG and EMG for controlling a hybrid human computer interface in patients with spinal cord injury

Investigating the feasibility of combining EEG and EMG for controlling a hybrid human computer interface in patients with spinal cord injury

What Is Being Trained? How Divergent Forms of Plasticity Compete To Shape Locomotor Recovery after Spinal Cord Injury

Entrenamiento robótico de la marcha en pacientes con Parálisis Cerebral: definición de objetivos, propuesta de tratamiento e implementación clínica preliminar

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