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Journal articleGathmann 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- Author Web Link
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- Citations: 10
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Journal articleGiruzzi 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: 0741-3335JT-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.
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Journal articleDideriksen 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: 0022-3077The 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.
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Journal articleChen 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- Author Web Link
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- Citations: 44
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Conference paperRodrigues 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 -
Journal articleStachaczyk 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- Author Web Link
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- Citations: 7
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Conference paperMa 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- Author Web Link
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- Citations: 3
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Journal articleWilke MA, Hartmann C, Schimpf F, et al., 2020,
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- Author Web Link
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- Citations: 9
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Journal articleIbanez J, Fu L, Rocchi L, et al., 2020,
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- Author Web Link
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- Citations: 5
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Journal articleDel 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: 0022-3751KEY 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
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Journal articleWilke MA, Niethammer C, Meyer B, et al., 2019,
Psychometric characterization of incidental feedback sources during grasping with a hand prosthesis.
, J Neuroeng Rehabil, Vol: 16BACKGROUND: 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
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Journal articleDel 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: 1741-2552Objective. 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.
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Journal articlePuttaraksa 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: 0022-3077Pathological 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.
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Journal articleAliakbaryhosseinabadi 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: 3060-3071OBJECTIVE: 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.
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Journal articleSeminara L, Fares H, Franceschi M, et al., 2020,
Dual-Parameter Modulation Improves Stimulus Localization in Multichannel Electrotactile Stimulation
, IEEE TRANSACTIONS ON HAPTICS, Vol: 13, Pages: 393-403, ISSN: 1939-1412- Author Web Link
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- Citations: 12
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Journal articleThompson 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: 1034-1041The 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
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Journal articleBesomi 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: 128-144The 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.
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Journal articleRashid U, Niazi IK, Signal N, et al., 2019,
Optimal automatic detection of muscle activation intervals.
, J Electromyogr Kinesiol, Vol: 48, Pages: 103-111A 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.
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Journal articleXu 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 -
Journal articleVujaklija I, Shalchyan V, Kamavuako EN, et al., 2018,
Online mapping of EMG signals into kinematics by autoencoding
, Journal of NeuroEngineering and Rehabilitation, Vol: 15, ISSN: 1743-0003Background In this paper, we propose a nonlinear minimally supervised method based on auto-encoding (AEN) of EMG for myocontrol. The proposed method was tested against the state-of-the-art (SOA) control scheme using a Fitts’ law approach. MethodsSeven able-bodied subjects performed a series of target acquisition myoelectric control tasks using the AEN and SOA algorithms for controlling two degrees-of-freedom (radial/ulnar deviation and flexion/extension of the wrist), and their online performance was characterized by six metrics. Results Both methods allowed a completion rate close to 100%, however AEN outperformed SOA for all other performance metrics, e.g. it allowed to perform the tasks on average in half the time with respect to SOA. Moreover, the amount of information transferred by the proposed method in bit/s was nearly twice the throughput of SOA. ConclusionsThese results show that autoencoders can map EMG signals into kinematics with the potential of providing intuitive and dexterous control of artificial limbs for amputees.
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