| 1. |
- Clarke, Alexander Kenneth, et al.
(author)
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Deep learning for robust decomposition of high-density surface EMG signals
- 2021
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In: IEEE Transactions on Biomedical Engineering. - 0018-9294 .- 1558-2531. ; 68:2, s. 526-534
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Journal article (peer-reviewed)abstract
- Blind source separation (BSS) algorithms, such as gradient convolution kernel compensation (gCKC), can efficiently and accurately decompose high-density surface electromyography (HD-sEMG) signals into constituent motor unit (MU) action potential trains. Once the separation matrix is blindly estimated on a signal interval, it is also possible to apply the same matrix to subsequent signal segments. Nonetheless, the trained separation matrices are sub-optimal in noisy conditions and require that incoming data undergo computationally expensive whitening. One unexplored alternative is to instead use the paired HD-sEMG signal and BSS output to train a model to predict MU activations within a supervised learning framework. A gated recurrent unit (GRU) network was trained to decompose both simulated and experimental unwhitened HD-sEMG signal using the output of the gCKC algorithm. The results on the experimental data were validated by comparison with the decomposition of concurrently recorded intramuscular EMG signals. The GRU network outperformed gCKC at low signal-to-noise ratios, proving superior performance in generalising to new data. Using 12 seconds of experimental data per recording, the GRU performed similarly to gCKC, at rates of agreement of 92.5% (84.5%-97.5%) and 94.9% (88.8%-100.0%) respectively for GRU and gCKC against matched intramuscular sources.
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| 2. |
- Mesquita, Ricardo, 1992, et al.
(author)
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Effects of jaw clenching and mental stress on persistent inward currents estimated by two different methods
- 2023
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In: European Journal of Neuroscience. - 1460-9568 .- 0953-816X. ; 58:9, s. 4011-4033
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Journal article (peer-reviewed)abstract
- Spinal motoneuron firing depends greatly on persistent inward currents (PICs), which in turn are facilitated by the neuromodulators serotonin and noradrenaline. The aim of this study was to determine whether jaw clenching (JC) and mental stress (MS), which may increase neuromodulator release, facilitate PICs in human motoneurons. The paired motor unit (MU) technique was used to estimate PIC contribution to motoneuron firing. Surface electromyograms were collected using a 32-channel matrix on gastrocnemius medialis (GM) during voluntary, ramp, plantar flexor contractions. MU discharges were identified, and delta frequency (ΔF), a measure of recruitment–derecruitment hysteresis, was calculated. Additionally, another technique was used (VibStim) that evokes involuntary contractions that persist after cessation of combined Achilles tendon vibration and triceps surae neuromuscular electrical stimulation. VibStim measures of plantar flexor torque and soleus activity may reflect PIC activation. ΔF was not significantly altered by JC (p =.679, n = 18, 9 females) or MS (p =.147, n = 14, 5 females). However, all VibStim variables quantifying involuntary torque and muscle activity during and after vibration cessation were significantly increased in JC (p <.011, n = 20, 10 females) and some, but not all, increased in MS (p =.017–.05, n = 19, 10 females). JC and MS significantly increased the magnitude of involuntary contractions (VibStim) but had no effect on GM ΔF during voluntary contractions. Effects of increased neuromodulator release on PIC contribution to motoneuron firing might differ between synergists or be context dependent. Based on these data, the background level of voluntary contraction and, hence, both neuromodulation and ionotropic inputs could influence neuromodulatory PIC enhancement.
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| 3. |
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| 4. |
- Muceli, Silvia, 1981, et al.
(author)
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Blind identification of the spinal cord output in humans with high-density electrode arrays implanted in muscles
- 2022
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In: Science advances. - : American Association for the Advancement of Science (AAAS). - 2375-2548. ; 8:46
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Journal article (peer-reviewed)abstract
- Invasive electromyography opened a new window to explore motoneuron behavior in vivo. However, the technique is limited by the small fraction of active motoneurons that can be concurrently detected, precluding a population analysis in natural tasks. Here, we developed a high-density intramuscular electrode for in vivo human recordings along with a fully automatic methodology that could detect the discharges of action potentials of up to 67 concurrently active motoneurons with 99% accuracy. These data revealed that motoneurons of the same pool receive common synaptic input at frequencies up to 75 Hz and that late-recruited motoneurons inhibit the discharges of those recruited earlier. These results constitute an important step in the population coding analysis of the human motor system in vivo.
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| 6. |
- Puttaraksa, Gonthicha, et al.
(author)
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Online tracking of the phase difference between neural drives to antagonist muscle pairs in essential tremor patients
- 2022
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In: IEEE Transactions on Neural Systems and Rehabilitation Engineering. - 1558-0210 .- 1534-4320. ; 30, s. 709-718
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Journal article (peer-reviewed)abstract
- Transcutaneous electrical stimulation has been applied in tremor suppression applications. Out-of-phase stimulation strategies applied above or below motor threshold result in a significant attenuation of pathological tremor. For stimulation to be properly timed, the varying phase relationship between agonist-antagonist muscle activity during tremor needs to be accurately estimated in real-time. Here we propose an online tremor phase and frequency tracking technique for the customized control of electrical stimulation, based on a phase-locked loop (PLL) system applied to the estimated neural drive to muscles. Surface electromyography signals were recorded from the wrist extensor and flexor muscle groups of 13 essential tremor patients during postural tremor. The EMG signals were pre-processed and decomposed online and offline via the convolution kernel compensation algorithm to discriminate motor unit spike trains. The summation of motor unit spike trains detected for each muscle was bandpass filtered between 3 to 10 Hz to isolate the tremor related components of the neural drive to muscles. The estimated tremorogenic neural drive was used as input to a PLL that tracked the phase differences between the two muscle groups. The online estimated phase difference was compared with the phase calculated offline using a Hilbert Transform as a ground truth. The results showed a rate of agreement of 0.88 ± 0.22 between offline and online EMG decomposition. The PLL tracked the phase difference of tremor signals in real-time with an average correlation of 0.86 ± 0.16 with the ground truth (average error of 6.40° ± 3.49°). Finally, the online decomposition and phase estimation components were integrated with an electrical stimulator and applied in closed-loop on one patient, to representatively demonstrate the working principle of the full tremor suppression system. The results of this study support the feasibility of real-time estimation of the phase of tremorogenic neural drive to muscles, providing a methodology for future tremor-suppression neuroprostheses.
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| 7. |
- Puttaraksa, Gonthicha, et al.
(author)
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Voluntary and tremorogenic inputs to motor neuron pools of agonist/antagonist muscles in essential tremor patients
- 2019
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In: Journal of Neurophysiology. - : American Physiological Society. - 1522-1598 .- 0022-3077. ; 122:5, s. 2043-2053
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Journal article (peer-reviewed)abstract
- 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 +/- SI)) and tremor frequency (3-10 Hz, 0.6 +/- 0.3) and were synchronized with small phase differences (3.3 +/- 25.2 degrees and 3.9 +/- 22.0 degrees 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 degrees) and out-of-phase activation at the tremor frequency band (126.9 +/- 75.6 degrees). Thus MNs innervating agonist/antagonist muscles concurrently receive synaptic inputs with different phase shifts in the voluntary and tremor frequency bands. NEW & NOTEWORTHY Although the mechanical characteristics of tremor have been widely studied, the activation of the affected muscles is still poorly understood. We analyzed the behavior of motor units of pairs of antagonistic wrist muscle groups in patients with essential tremor and studied their activity at voluntary movement- and tremor-related frequencies. We found that the phase relation between inputs to antagonistic muscles is different at the voluntary and tremor frequency bands.
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