Estimation of Neuromuscular Primitives from EEG Slow Cortical Potentials in Incomplete Spinal Cord Injury Individuals for a New Class of Brain-Machine Interfaces

Úbeda, Andrés; Azorín, José M.; Farina, Dario; Sartori, Massimo

doi:10.3389/fncom.2018.00003

Cited by 18 publications

(18 citation statements)

References 28 publications

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“…Overall, this does not enable continuous (event-free and task-independent) control of robotic exoskeletons. Alternative bioelectrical signals such as electroencephalograms [37–40] are currently limited in the context of robotic exoskeletons due to signal high sensitivity to movement artifacts [41].…”

Section: Introductionmentioning

confidence: 99%

Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling

Durandau

Farina

Asín-Prieto

et al. 2019

J NeuroEngineering Rehabil

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Background: Research efforts in neurorehabilitation technologies have been directed towards creating robotic exoskeletons to restore motor function in impaired individuals. However, despite advances in mechatronics and bioelectrical signal processing, current robotic exoskeletons have had only modest clinical impact. A major limitation is the inability to enable exoskeleton voluntary control in neurologically impaired individuals. This hinders the possibility of optimally inducing the activity-driven neuroplastic changes that are required for recovery. Methods: We have developed a patient-specific computational model of the human musculoskeletal system controlled via neural surrogates, i.e., electromyography-derived neural activations to muscles. The electromyography-driven musculoskeletal model was synthesized into a human-machine interface (HMI) that enabled poststroke and incomplete spinal cord injury patients to voluntarily control multiple joints in a multifunctional robotic exoskeleton in real time. Results: We demonstrated patients' control accuracy across a wide range of lower-extremity motor tasks. Remarkably, an increased level of exoskeleton assistance always resulted in a reduction in both amplitude and variability in muscle activations as well as in the mechanical moments required to perform a motor task. Since small discrepancies in onset time between human limb movement and that of the parallel exoskeleton would potentially increase human neuromuscular effort, these results demonstrate that the developed HMI precisely synchronizes the device actuation with residual voluntary muscle contraction capacity in neurologically impaired patients. Conclusions: Continuous voluntary control of robotic exoskeletons (i.e. event-free and task-independent) has never been demonstrated before in populations with paretic and spastic-like muscle activity, such as those investigated in this study. Our proposed methodology may open new avenues for harnessing residual neuromuscular function in neurologically impaired individuals via symbiotic wearable robots.

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Section: Introductionmentioning

confidence: 99%

Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling

Durandau

Farina

Asín-Prieto

et al. 2019

J NeuroEngineering Rehabil

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“…The distribution of papers in the categories is shown in a pie chart in Figure 4. Study of the cortico-muscular coupling (1) during motor tasks [37][38][39][40][41] and (2) with electrical stimulation [42][43][44][45][46] Investigation of the effects of exoskeleton on functional connectivity [47][48][49] Investigation of the effects of visual feedback [50,51] Detection of movement intention [52,53] Study of the interhemispheric interaction with TMS [54] Study of a neurophysiological marker of stress [55] Study of slow cortical potentials in stroke [56] Study of correlation between lower back pain and altered postural stabilization [57] Test new rehabilitation paradigm [34,[58][59][60][61][62] Investigation of the efficacy of BMI [63] and EEG feedback [64] Table 1. Type of study and aim.…”

Section: Type Of Studymentioning

confidence: 99%

Combined Use of EMG and EEG Techniques for Neuromotor Assessment in Rehabilitative Applications: A Systematic Review

Brambilla

Pirovano

Mira

et al. 2021

Sensors

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Electroencephalography (EEG) and electromyography (EMG) are widespread and well-known quantitative techniques used for gathering biological signals at cortical and muscular levels, respectively. Indeed, they provide relevant insights for increasing knowledge in different domains, such as physical and cognitive, and research fields, including neuromotor rehabilitation. So far, EEG and EMG techniques have been independently exploited to guide or assess the outcome of the rehabilitation, preferring one technique over the other according to the aim of the investigation. More recently, the combination of EEG and EMG started to be considered as a potential breakthrough approach to improve rehabilitation effectiveness. However, since it is a relatively recent research field, we observed that no comprehensive reviews available nor standard procedures and setups for simultaneous acquisitions and processing have been identified. Consequently, this paper presents a systematic review of EEG and EMG applications specifically aimed at evaluating and assessing neuromotor performance, focusing on cortico-muscular interactions in the rehabilitation field. A total of 213 articles were identified from scientific databases, and, following rigorous scrutiny, 55 were analyzed in detail in this review. Most of the applications are focused on the study of stroke patients, and the rehabilitation target is usually on the upper or lower limbs. Regarding the methodological approaches used to acquire and process data, our results show that a simultaneous EEG and EMG acquisition is quite common in the field, but it is mostly performed with EMG as a support technique for more specific EEG approaches. Non-specific processing methods such as EEG-EMG coherence are used to provide combined EEG/EMG signal analysis, but rarely both signals are analyzed using state-of-the-art techniques that are gold-standard in each of the two domains. Future directions may be oriented toward multi-domain approaches able to exploit the full potential of combined EEG and EMG, for example targeting a wider range of pathologies and implementing more structured clinical trials to confirm the results of the current pilot studies.

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“…A primitive but currently feasible solution would involve triggering the NMS model to perform a predetermined trajectory (e.g., cycling). Future approaches may explore BCI to extract basic spinal primitives that can be mapped to individual muscle to enable intuitive control of NMS models (Ubeda et al, 2018). This solution may be more advantageous compared to direct control of joint angles (Fitzsimmons et al, 2009) as it better reflects the current understanding of how the mammalian central nervous system organizes large groups of synergistic muscles during complex movement.…”

Section: Real-time Nms Modeling To Integrate Assistive Devicesmentioning

confidence: 99%

Neuromusculoskeletal Modeling-Based Prostheses for Recovery After Spinal Cord Injury

et al. 2019

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Concurrent stimulation and reinforcement of motor and sensory pathways has been proposed as an effective approach to restoring function after developmental or acquired neurotrauma. This can be achieved by applying multimodal rehabilitation regimens, such as thought-controlled exoskeletons or epidural electrical stimulation to recover motor pattern generation in individuals with spinal cord injury (SCI). However, the human neuromusculoskeletal (NMS) system has often been oversimplified in designing rehabilitative and assistive devices. As a result, the neuromechanics of the muscles is seldom considered when modeling the relationship between electrical stimulation, mechanical assistance from exoskeletons, and final joint movement. A powerful way to enhance current neurorehabilitation is to develop the next generation prostheses incorporating personalized NMS models of patients. This strategy will enable an individual voluntary interfacing with multiple electromechanical rehabilitation devices targeting key afferent and efferent systems for functional improvement. This narrative review discusses how real-time NMS models can be integrated with finite element (FE) of musculoskeletal tissues and interface multiple assistive and robotic devices with individuals with SCI to promote neural restoration. In particular, the utility of NMS models for optimizing muscle stimulation patterns, tracking functional improvement, monitoring safety, and providing augmented feedback during exercise-based rehabilitation are discussed.

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Estimation of Neuromuscular Primitives from EEG Slow Cortical Potentials in Incomplete Spinal Cord Injury Individuals for a New Class of Brain-Machine Interfaces

Cited by 18 publications

References 28 publications

Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling

Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling

Combined Use of EMG and EEG Techniques for Neuromotor Assessment in Rehabilitative Applications: A Systematic Review

Neuromusculoskeletal Modeling-Based Prostheses for Recovery After Spinal Cord Injury

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