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Farokh Atashzar S, Tavakoli M, Farina D, et al., 2020, Editorial: Autonomy and intelligence in neurorehabilitation robotic and prosthetic technologies, Journal of Medical Robotics Research, Vol: 5, ISSN: 2424-9068
Neurorehabilitation robotic technologies and powered assistive prosthetic devices have shown great potential for accelerating motor recovery or compensating for the lost motor functions of disabled users. The functioning of these technologies relies on a highly-interactive bidirectional flow of information and physical energy between a human user and a robotic system. Thus, key factors are integrity, intelligence and quality of the interaction loops. As a result, research in this field has focused on (a) enhancing the quality and safety of the physical interaction between disabled users and robotic systems while providing a high level of intelligence and adaptability for generating assistive and therapeutic force fields; (b) detecting the user's motor intention with high spatiotemporal resolution to provide bidirectional human-machine interfacing; (c) promoting mental engagement through designing multimodal interactive interfaces and various sensory manipulation strategies. This Special Issue has collected papers that contribute to these three research areas, highlighting the importance of different aspects in human-robot interaction loops for augmenting the performance of neurorehabilitation robotic systems and prosthetic devices.
Del Vecchio A, Negro F, Holobar A, et al., 2020, Direct translation of findings in isolated animal preparations to <i>in vivo</i> human motoneuron behaviour is challenging, JOURNAL OF PHYSIOLOGY-LONDON, Vol: 598, Pages: 1111-1112, ISSN: 0022-3751
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Germer CM, Del Vecchio A, Negro F, et al., 2020, Neurophysiological correlates of force control improvement induced by sinusoidal vibrotactile stimulation, Journal of Neural Engineering, Vol: 17, Pages: 1-14, ISSN: 1741-2552
Objective. An optimal level of vibrotactile stimulation has been shown to improve sensorimotor control in healthy and diseased individuals. However, the underlying neurophysiological mechanisms behind the enhanced motor performance caused by vibrotactile stimulation are yet to be fully understood. Therefore, here we aim to evaluate the effect of a cutaneous vibration on the firing behavior of motor units in a condition of improved force steadiness. Approach. Participants performed a visuomotor task, which consisted of low-intensity isometric contractions of the first dorsal interosseous (FDI) muscle, while sinusoidal (175 Hz) vibrotactile stimuli with different intensities were applied to the index finger. High-density surface electromyogram was recorded from the FDI muscle, and a decomposition algorithm was used to extract the motor unit spike trains. Additionally, computer simulations were performed using a multiscale neuromuscular model to provide a potential explanation for the experimental findings. Main results. Experimental outcomes showed that an optimal level of vibration significantly improved force steadiness (estimated as the coefficient of variation of force). The decreased force variability was accompanied by a reduction in the variability of the smoothed cumulative spike train (as an estimation of the neural drive to the muscle), and the proportion of common inputs to the FDI motor nucleus. However, the interspike interval variability did not change significantly with the vibration. A mathematical approach, together with computer simulation results suggested that vibrotactile stimulation would reduce the variance of the common synaptic input to the motor neuron pool, thereby decreasing the low frequency fluctuations of the neural drive to the muscle and force steadiness. Significance. Our results demonstrate that the decreased variability in common input accounts for the enhancement in force control induced by vibrotactile stimulation.
Yu T, Akhmadeev K, Le Carpentier E, et al., 2020, Recursive Decomposition of Electromyographic Signals With a Varying Number of Active Sources: Bayesian Modeling and Filtering, IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, Vol: 67, Pages: 428-440, ISSN: 0018-9294
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- Citations: 9
Aman M, Bergmeister KD, Festin C, et al., 2020, Experimental testing of bionic peripheral nerve and muscle interfaces: animal model considerations, Frontiers in Neuroscience, Vol: 13, Pages: 1-9, ISSN: 1662-453X
Introduction: Man-machine interfacing remains the main challenge for accurate and reliable control of bionic prostheses. Implantable electrodes in nerves and muscles may overcome some of the limitations by significantly increasing the interface's reliability and bandwidth. Before human application, experimental preclinical testing is essential to assess chronic in-vivo biocompatibility and functionality. Here, we analyze available animal models, their costs and ethical challenges in special regards to simulating a potentially life-long application in a short period of time and in non-biped animals.Methods: We performed a literature analysis following the PRISMA guidelines including all animal models used to record neural or muscular activity via implantable electrodes, evaluating animal models, group size, duration, origin of publication as well as type of interface. Furthermore, behavioral, ethical, and economic considerations of these models were analyzed. Additionally, we discuss experience and surgical approaches with rat, sheep, and primate models and an approach for international standardized testing.Results: Overall, 343 studies matched the search terms, dominantly originating from the US (55%) and Europe (34%), using mainly small animal models (rat: 40%). Electrode placement was dominantly neural (77%) compared to muscular (23%). Large animal models had a mean duration of 135 ± 87.2 days, with a mean of 5.3 ± 3.4 animals per trial. Small animal models had a mean duration of 85 ± 11.2 days, with a mean of 12.4 ± 1.7 animals.Discussion: Only 37% animal models were by definition chronic tests (>3 months) and thus potentially provide information on long-term performance. Costs for large animals were up to 45 times higher than small animals. However, costs are relatively small compared to complication costs in human long-term applications. Overall, we believe a combination of small animals for preliminary primary electrode testing a
Gathmann T, Atashzar SF, Alva PGS, et al., 2020, Wearable Dual-Frequency Vibrotactile System for Restoring Force and Stiffness Perception, IEEE TRANSACTIONS ON HAPTICS, Vol: 13, Pages: 191-196, ISSN: 1939-1412
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- Citations: 10
Giruzzi G, Yoshida M, Aiba N, et al., 2020, Advances in the physics studies for the JT-60SA tokamak exploitation and research plan, Plasma Physics and Controlled Fusion, Vol: 62, ISSN: 0741-3335
JT-60SA, the largest tokamak that will operate before ITER, has been designed and built jointly by Japan and Europe, and is due to start operation in 2020. Its main missions are to support ITER exploitation and to contribute to the demonstration fusion reactor machine and scenario design. Peculiar properties of JT-60SA are its capability to produce long-pulse, high-β, and highly shaped plasmas. The preparation of the JT-60SA Research Plan, plasma scenarios, and exploitation are producing physics results that are not only relevant to future JT-60SA experiments, but often constitute original contributions to plasma physics and fusion research. Results of this kind are presented in this paper, in particular in the areas of fast ion physics, high-beta plasma properties and control, and non-linear edge localised mode stability studies.
Dideriksen JL, Del Vecchio A, Farina D, 2020, Neural and muscular determinants of maximal rate of force development, Journal of Neurophysiology, Vol: 123, Pages: 149-157, ISSN: 0022-3077
The ability to produce rapid forces requires quick motor unit recruitment, high motor unit discharge rates, and fast motor unit force twitches. The relative importance of these parameters for maximum rate of force development (RFD), however, is poorly understood. In this study, we systematically investigated these relationships using a computational model of motor unit pool activity and force. Across simulations, neural and muscular properties were systematically varied in experimentally observed ranges. Motor units were recruited over an interval starting from contraction onset (range: 22–233 ms). Upon recruitment, discharge rates declined from an initial rate (range: 89–212 pulses per second), with varying likelihood of doublet (interspike interval of 3 ms; range: 0–50%). Finally, muscular adaptations were modeled by changing average twitch contraction time (range: 42–78 ms). Spectral analysis showed that the effective neural drive to the simulated muscle had smaller bandwidths than the average motor unit twitch, indicating that the bandwidth of the motor output, and thus the capacity for explosive force, was limited mainly by neural properties. The simulated RFD increased by 1,050 ± 281% maximal voluntary contraction force per second from the longest to the shortest recruitment interval. This effect was more than fourfold higher than the effect of increasing the initial discharge rate, more than fivefold higher than the effect of increasing the chance of doublets, and more than sixfold higher than the effect of decreasing twitch contraction times. The simulated results suggest that the physiological variation of the rate by which motor units are recruited during ballistic contractions is the main determinant for the variability in RFD across individuals.
Chen C, Yu Y, Ma S, et al., 2020, Hand gesture recognition based on motor unit spike trains decoded from high-density electromyography, BIOMEDICAL SIGNAL PROCESSING AND CONTROL, Vol: 55, ISSN: 1746-8094
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- Citations: 44
Rodrigues C, Fernandez M, Megia A, et al., 2020, Comparison of Intramuscular and Surface Electromyography Recordings Towards the Control of Wearable Robots for Incomplete Spinal Cord Injury Rehabilitation, 8th IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), Publisher: IEEE, Pages: 564-569, ISSN: 2155-1782
Stachaczyk M, Atashzar SF, Dupan S, et al., 2020, Toward Universal Neural Interfaces for Daily Use: Decoding the Neural Drive to Muscles Generalises Highly Accurate Finger Task Identification Across Humans, IEEE ACCESS, Vol: 8, Pages: 149025-149035, ISSN: 2169-3536
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- Citations: 7
Ma S, Chen C, Han D, et al., 2020, Subject-Specific EMG Modeling with Multiple Muscles: A Preliminary Study, 42nd Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), Publisher: IEEE, Pages: 740-743, ISSN: 1557-170X
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- Citations: 3
Wilke MA, Hartmann C, Schimpf F, et al., 2019, The Interaction Between Feedback Type and Learning in Routine Grasping With Myoelectric Prostheses, IEEE TRANSACTIONS ON HAPTICS, Vol: 13, Pages: 645-654, ISSN: 1939-1412
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- Citations: 9
Ibanez J, Fu L, Rocchi L, et al., 2019, Plasticity induced by pairing brain stimulation with motor-related states only targets a subset of cortical neurones, BRAIN STIMULATION, Vol: 13, Pages: 464-466, ISSN: 1935-861X
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- Citations: 5
Del Vecchio A, Germer CM, Elias LA, et al., 2019, The human central nervous system transmits common synaptic inputs to distinct motor neuron pools during non-synergistic digit actions, The Journal of Physiology, Vol: 597, Pages: 5935-5948, ISSN: 0022-3751
KEY POINTS: Neural connectivity between distinct motor neuronal modules in the spinal cord is classically studied through electrical stimulation or multi-muscle EMG recordings. We quantified the strength of correlation in the activity of two distinct populations of motor neurons innervating the thenar and first dorsal interosseous muscles during tasks that required the two hand muscles to exert matched or un-matched forces in different directions. We show that when the two hand muscles are concurrently activated, synaptic input to the two motor neuron pools is shared across all frequency bandwidths (representing cortical and spinal input) associated with force control. The observed connectivity indicates that motor neuron pools receive common input even when digit actions do not belong to a common behavioural repertoire. ABSTRACT: Neural connectivity between distinct motor neuronal modules in the spinal cord is classically studied through electrical stimulation or multi-muscle EMG recordings. Here we quantify the strength of correlation in the activity of two distinct populations of motor neurons innervating the thenar and first dorsal interosseous muscles in humans during voluntary contractions. To remove confounds associated with previous studies, we used a task that required the two hand muscles to exert matched or un-matched forces in different directions. Despite the force production task consisting of uncommon digit force coordination patterns, we found that synaptic input to motor neurons is shared across all frequency bands, reflecting cortical and spinal inputs associated with force control. The coherence between discharge timings of the two pools of motor neurons was significant at the delta (0-5 Hz), alpha (5-15 Hz) and beta (15-35 Hz) bands (P < 0.05). These results suggest that correlated input to motor neurons of two hand muscles can occur even during tasks not belonging to a common behavioural repertoire and despite lack of
Wilke MA, Niethammer C, Meyer B, et al., 2019, Psychometric characterization of incidental feedback sources during grasping with a hand prosthesis., J Neuroeng Rehabil, Vol: 16
BACKGROUND: A prosthetic system should ideally reinstate the bidirectional communication between the user's brain and its end effector by restoring both motor and sensory functions lost after an amputation. However, current commercial prostheses generally do not incorporate somatosensory feedback. Even without explicit feedback, grasping using a prosthesis partly relies on sensory information. Indeed, the prosthesis operation is characterized by visual and sound cues that could be exploited by the user to estimate the prosthesis state. However, the quality of this incidental feedback has not been objectively evaluated. METHODS: In this study, the psychometric properties of the auditory and visual feedback of prosthesis motion were assessed and compared to that of a vibro-tactile interface. Twelve able-bodied subjects passively observed prosthesis closing and grasping an object, and they were asked to discriminate (experiment I) or estimate (experiment II) the closing velocity of the prosthesis using visual (VIS), acoustic (SND), or combined (VIS + SND) feedback. In experiment II, the subjects performed the task also with a vibrotactile stimulus (VIB) delivered using a single tactor. The outcome measures for the discrimination and estimation experiments were just noticeable difference (JND) and median absolute estimation error (MAE), respectively. RESULTS: The results demonstrated that the incidental sources provided a remarkably good discrimination and estimation of the closing velocity, significantly outperforming the vibrotactile feedback. Using incidental sources, the subjects could discriminate almost the minimum possible increment/decrement in velocity that could be commanded to the prosthesis (median JND < 2% for SND and VIS + SND). Similarly, the median MAE in estimating the prosthesis velocity randomly commanded from the full working range was also low, i.e., approximately 5% in SND and VIS + SND. CO
Del Vecchio A, Farina D, 2019, Interfacing the neural output of the spinal cord: robust and reliable longitudinal identification of motor neurons in humans, Journal of Neural Engineering, Vol: 17, Pages: 1-11, ISSN: 1741-2552
Objective. Non-invasive electromyographic techniques can detect action potentials from muscle units with high spatial dimensionality. These technologies allow the decoding of large samples of motor units by using high-density grids of electrodes that are placed on the skin overlying contracting muscles and therefore provide a non-invasive representation of the human spinal cord output. Approach. From a sample of >1200 decoded motor neurons, we show that motor neuron activity can be identified in humans in the full muscle recruitment range with high accuracy. Main results. After showing the validity of decomposition with novel test parameters, we demonstrate that the same motor neurons can be tracked over a period of one-month, which allows for the longitudinal analysis of individual human neural cells. Significance. These results show the potential of an accurate and reliable assessment of large populations of motor neurons in physiological investigations. We discuss the potential of this non-invasive neural interfacing technology for the study of the neural determinants of movement and man-machine interfacing.
Puttaraksa G, Muceli S, Alvaro Gallego J, et al., 2019, Voluntary and tremorogenic inputs to motor neuron pools of agonist/antagonist muscles in essential tremor patients, Journal of Neurophysiology, Vol: 122, Pages: 2043-2053, ISSN: 0022-3077
Pathological tremor is an oscillation of body parts at 3–10 Hz, determined by the output of spinal motor neurons (MNs), which receive synaptic inputs from supraspinal centers and muscle afferents. The behavior of spinal MNs during tremor is not well understood, especially in relation to the activation of the multiple muscles involved. Recent studies on patients with essential tremor have shown that antagonist MN pools receive shared input at the tremor frequency. In this study, we investigated the synaptic inputs related to tremor and voluntary movement, and their coordination across antagonist muscles. We analyzed the spike trains of motor units (MUs) identified from high-density surface electromyography from the forearm extensor and flexor muscles in 15 patients with essential tremor during postural tremor. The shared synaptic input was quantified by coherence and phase difference analysis of the spike trains. All pairs of spike trains in each muscle showed coherence peaks at the voluntary drive frequency (1–3 Hz, 0.2 ± 0.2, mean ± SD) and tremor frequency (3–10 Hz, 0.6 ± 0.3) and were synchronized with small phase differences (3.3 ± 25.2° and 3.9 ± 22.0° for the voluntary drive and tremor frequencies, respectively). The coherence between MN spike trains of antagonist muscle groups at the tremor frequency was significantly smaller than intramuscular coherence. We predominantly observed in-phase activation of MUs between agonist/antagonist muscles at the voluntary frequency band (0.6 ± 48.8°) and out-of-phase activation at the tremor frequency band (126.9 ± 75.6°). Thus MNs innervating agonist/antagonist muscles concurrently receive synaptic inputs with different phase shifts in the voluntary and tremor frequency bands.
Aliakbaryhosseinabadi S, Kamavuako EN, Jiang N, et al., 2019, Classification of Movement Preparation Between Attended and Distracted Self-Paced Motor Tasks., IEEE Trans Biomed Eng, Vol: 66, Pages: 3060-3071
OBJECTIVE: Brain-computer interface (BCI) systems aim to control external devices by using brain signals. The performance of these systems is influenced by the user's mental state, such as attention. In this study, we classified two attention states to a target task (attended and distracted task level) while attention to the task is altered by one of three types of distractors. METHODS: A total of 27 participants were allocated into three experimental groups and exposed to one type of distractor. An attended condition that was the same across the three groups comprised only the main task execution (self-paced dorsiflexion) while the distracted condition was concurrent execution of the main task and an oddball task (dual-task condition). Electroencephalography signals were recorded from 28 electrodes to classify the two attention states of attended or distracted task conditions by extracting temporal and spectral features. RESULTS: The results showed that the ensemble classification accuracy using the combination of temporal and spectral features (spectro-temporal features, 82.3 ± 2.7%) was greater than using temporal (69 ± 2.2%) and spectral (80.3 ± 2.6%) features separately. The classification accuracy was computed using a combination of different channel locations, and it was demonstrated that a combination of parietal and centrally located channels was superior for classification of two attention states during movement preparation (parietal channels: 84.6 ± 1.3%, central and parietal channels: 87.2 ± 1.5%). CONCLUSION: It is possible to monitor the users' attention to the task for different types of distractors. SIGNIFICANCE: It has implications for online BCI systems where the requirement is for high accuracy of intention detection.
Seminara L, Fares H, Franceschi M, et al., 2019, Dual-Parameter Modulation Improves Stimulus Localization in Multichannel Electrotactile Stimulation, IEEE TRANSACTIONS ON HAPTICS, Vol: 13, Pages: 393-403, ISSN: 1939-1412
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- Citations: 12
Thompson CK, Johnson MD, Negro F, et al., 2019, Exogenous neuromodulation of spinal neurons induces beta-band coherence during self-sustained discharge of hind limb motor unit populations., J Appl Physiol (1985), Vol: 127, Pages: 1034-1041
The spontaneous or self-sustained discharge of spinal motoneurons can be observed in both animals and humans. Although the origins of this self-sustained discharge are not fully known, it can be generated by activation of persistent inward currents intrinsic to the motoneuron. If self-sustained discharge is generated exclusively through this intrinsic mechanism, the discharge of individual motor units will be relatively independent of one another. Alternatively, if increased activation of premotor circuits underlies this prolonged discharge of spinal motoneurons, we would expect correlated activity among motoneurons. Our aim is to assess potential synaptic drive by quantifying coherence during self-sustained discharge of spinal motoneurons. Electromyographic activity was collected from 20 decerebrate animals using a 64-channel electrode grid placed on the isolated soleus muscle before and following intrathecal administration of methoxamine, a selective α1-noradrenergic agonist. Sustained muscle activity was recorded and decomposed into the discharge times of ~10-30 concurrently active individual motor units. Consistent with previous reports, the self-sustained discharge of motor units occurred at low mean discharge rates with low-interspike variability. Before methoxamine administration, significant low-frequency coherence (<2 Hz) was observed, while minimal coherence was observed within higher frequency bands. Following intrathecal administration of methoxamine, increases in motor unit discharge rates and strong coherence in both the low-frequency and 15- to 30-Hz beta bands were observed. These data demonstrate beta-band coherence among motor units can be observed through noncortical mechanisms and that neuromodulation of spinal/brainstem neurons greatly influences coherent discharge within spinal motor pools.NEW & NOTEWORTHY The correlated discharge of spinal motoneurons is often used to describe the input to the motor pool. We demonstrate spinal/bra
Xu R, Dosen S, Jiang N, et al., 2019, Continuous 2D control via state-machine triggered by endogenous sensory discrimination and a fast brain switch, JOURNAL OF NEURAL ENGINEERING, Vol: 16, ISSN: 1741-2560
Rashid U, Niazi IK, Signal N, et al., 2019, Optimal automatic detection of muscle activation intervals., J Electromyogr Kinesiol, Vol: 48, Pages: 103-111
A significant challenge in surface electromyography (sEMG) is the accurate identification of onsets and offsets of muscle activations. Manual labelling and automatic detection are currently used with varying degrees of reliability, accuracy and time efficiency. Automatic methods still require significant manual input to set the optimal parameters for the detection algorithm. These parameters usually need to be adjusted for each individual, muscle and movement task. We propose a method to automatically identify optimal detection parameters in a minimally supervised way. The proposed method solves an optimisation problem that only requires as input the number of activation bursts in the sEMG in a given time interval. This approach was tested on an extended version of the widely adopted double thresholding algorithm, although the optimisation could be applied to any detection algorithm. sEMG data from 22 healthy participants performing a single (ankle dorsiflexion) and a multi-joint (step on/off) task were used for evaluation. Detection rate, concordance, F1 score as an average of sensitivity and precision, degree of over detection, and degree of under detection were used as performance metrices. The proposed method improved the performance of the double thresholding algorithm in multi-joint movement and had the same performance in single joint movement with respect to the performance of the double thresholding algorithm with task specific global parameters. Moreover, the proposed method was robust when an error of up to ±10% was introduced in the number of activation bursts in the optimisation phase regardless of the movement. In conclusion, our optimised method has improved the automation of a sEMG detection algorithm which may reduce the time burden associated with current sEMG processing.
Besomi M, Hodges PW, Van Dieën J, et al., 2019, Consensus for experimental design in electromyography (CEDE) project: Electrode selection matrix., J Electromyogr Kinesiol, Vol: 48, Pages: 128-144
The Consensus for Experimental Design in Electromyography (CEDE) project is an international initiative which aims to guide decision-making in recording, analysis, and interpretation of electromyographic (EMG) data. The quality of the EMG recording, and validity of its interpretation depend on many characteristics of the recording set-up and analysis procedures. Different electrode types (i.e., surface and intramuscular) will influence the recorded signal and its interpretation. This report presents a matrix to consider the best electrode type selection for recording EMG, and the process undertaken to achieve consensus. Four electrode types were considered: (1) conventional surface electrode, (2) surface matrix or array electrode, (3) fine-wire electrode, and (4) needle electrode. General features, pros, and cons of each electrode type are presented first. This information is followed by recommendations for specific types of muscles, the information that can be estimated, the typical representativeness of the recording and the types of contractions for which the electrode is best suited. This matrix is intended to help researchers when selecting and reporting the electrode type in EMG studies.
Felici F, Bazzucchi I, Casolo A, et al., 2019, The relative strength of common synaptic input to motor neurons is not a determinant of the maximal rate of force development in humans, Publisher: WILEY, Pages: 25-26, ISSN: 1748-1708
Sturma A, Hruby LA, Farina D, et al., 2019, Structured motor rehabilitation after selective nerve transfers, Jove-Journal of Visualized Experiments, Vol: 150, Pages: 1-11, ISSN: 1940-087X
Here, we present a protocol for the motor rehabilitation of patients with severe nerve injuries and selective nerve transfer surgery. It aims at restoring the motor function proposing several stages in patient education, early-stage therapy after surgery and interventions for rehabilitation after successful re-innervation of the nerve’s target.
Durandau G, Farina D, Asín-Prieto G, et al., 2019, Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling., Journal of NeuroEngineering and Rehabilitation, Vol: 16, Pages: 91-91, ISSN: 1743-0003
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 harnessin
Salminger S, Sturma A, Hofer C, et al., 2019, Long-term implant of intramuscular sensors and nerve transfers for wireless control of robotic arms in above-elbow amputees, Science Robotics, Vol: 4, Pages: 1-9, ISSN: 2470-9476
Targeted muscle reinnervation (TMR) amplifies the electrical activity of nerves at the stump of amputees by redirecting them in remnant muscles above the amputation. The electrical activity of the reinnervated muscles can be used to extract natural control signals. Nonetheless, current control systems, mainly based on noninvasive muscle recordings, fail to provide accurate and reliable control over time. This is one of the major reasons for prosthetic abandonment. This prospective interventional study includes three unilateral above-elbow amputees and reports the long-term (2.5 years) implant of wireless myoelectric sensors in the reinnervation sites after TMR and their use for control of robotic arms in daily life. It therefore demonstrates the clinical viability of chronically implanted myoelectric interfaces that amplify nerve activity through TMR. The patients showed substantial functional improvements using the implanted system compared with control based on surface electrodes. The combination of TMR and chronically implanted sensors may drastically improve robotic limb replacement in above-elbow amputees.
Del Vecchio A, Falla D, Felici F, et al., 2019, The relative strength of common synaptic input to motor neurons is not a determinant of the maximal rate of force development in humans, JOURNAL OF APPLIED PHYSIOLOGY, Vol: 127, Pages: 205-214, ISSN: 8750-7587
Yeung D, Farina D, Vujaklija I, 2019, Can Multi-DoF Training Improve Robustness of Muscle Synergy Inspired Myocontrollers?, Pages: 665-670
Non-negative Matrix Factorization (NMF) has been effective in extracting commands from surface electromyography (EMG) for the control of upper-limb prostheses. This approach enables Simultaneous and Proportional Control (SPC) over multiple degrees-of-freedom (DoFs) in a minimally supervised way. Here, like with other myoelectric approaches, robustness remains essential for clinical adoption, with device donning/doffing being a known cause for performance degradation. Previous research has demonstrated that NMF-based myocontrollers, trained on just single-DoF activations, permit a certain degree of user adaptation to a range of disturbances. In this study, we compare this traditional NMF controller with its sparsity constrained variation that allows initialization using both single and combined-DoF activations (NMF-C). The evaluation was done on 12 able bodied participants through a set of online target-reaching tests. Subjects were fitted with an 8-channel bipolar EMG setup, which was shifted by 1cm in both transversal directions throughout the experiments without system retraining. In the baseline condition NMF performed somewhat better than NMFC, but it did suffer more following the electrode repositioning, making the two perform on par. With no significant difference present across the conditions, results suggest that there is no immediate advantage from the naïve inclusion of more comprehensive training sets to the classic synergy-inspired implementation of SPC.
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