Voluntary and tremorogenic inputs to motor neuron pools of agonist/antagonist muscles in essential tremor patients

Hand and distal joint tremor are most coherent with the activity of elbow flexors and wrist extensors in persons with essential tremor

Essential tremor (ET) affects millions of people. Although frontline treatment options (medication, deep brain stimulation, and focused ultrasound ablation) have provided significant relief, many patients are unsatisfied with the outcomes. Peripheral suppression techniques, such as injections of botulinum toxin or sensory electrical stimulation of muscles, are gaining popularity, but could be optimized if the muscles most responsible for a patient's tremor were identified. The purpose of this study was to quantify the relationship between the activity in various upper limb muscles and the resulting tremor in patients with ET. Surface electromyogram (sEMG) from the 15 major superficial muscles of the upper limb and displacement of the hand and upper limb joints were recorded from 22 persons with ET while they performed kinetic and postural tasks representative of activities of daily living. We calculated the peak coherence (frequency-dependent correlation) in the tremor band (4-8 Hz) between the sEMG of each muscle and the displacement in each major degree of freedom (DOF). Averaged across subjects with ET, the highest coherence was found between elbow flexors (particularly biceps brachii and brachioradialis) and the distal DOF (forearm, wrist, and hand motion), and between wrist extensors (extensor carpi radialis and ulnaris) and the same distal DOF. These coherence values represent the upper bound on the proportion of the tremor caused by each muscle. We conclude that, without further information, elbow flexors and wrist extensors should be among the first muscles considered for peripheral suppression techniques in persons with ET.NEW & NOTEWORTHY We characterized the relationships between activity in upper limb muscles and tremor in persons with essential tremor using coherence, which provides an upper bound on the proportion of the tremor due to each muscle. Averaged across subjects and various tasks, tremor in the hand and distal joints was most coherent with elbow flexors and wrist extensors. We conclude that, without further information, these muscle groups should be among the first considered for peripheral suppression techniques.

Decoding firings of a large population of human motor units from high-density surface electromyogram in response to transcranial magnetic stimulation

We describe a novel application of methodology for high-density surface electromyography (HDsEMG) decomposition to identify motor unit (MU) firings in response to transcranial magnetic stimulation (TMS). The method is based on the MU filter estimation from HDsEMG decomposition with convolution kernel compensation during voluntary isometric contractions and its application to contractions elicited by TMS. First, we simulated synthetic HDsEMG signals during voluntary contractions followed by simulated motor evoked potentials (MEPs) recruiting an increasing proportion of the motor pool. The estimation of MU filters from voluntary contractions and their application to elicited contractions resulted in high (>90%) precision and sensitivity of MU firings during MEPs. Subsequently, we conducted three experiments in humans. From HDsEMG recordings in first dorsal interosseous and tibialis anterior muscles, we demonstrated an increase in the number of identified MUs during MEPs evoked with increasing stimulation intensity, low variability in the MU firing latency and a proportion of MEP energy accounted for by decomposition similar to voluntary contractions. A negative relationship between the MU recruitment threshold and the number of identified MU firings was exhibited during the MEP recruitment curve, suggesting orderly MU recruitment. During isometric dorsiflexion we also showed a negative association between voluntary MU firing rate and the number of firings of the identified MUs during MEPs, suggesting a decrease in the probability of MU firing during MEPs with increased background MU firing rate. We demonstrate accurate identification of a large population of MU firings in a broad recruitment range in response to TMS via non-invasive HDsEMG recordings. KEY POINTS: Transcranial magnetic stimulation (TMS) of the scalp produces multiple descending volleys, exciting motor pools in a diffuse manner. The characteristics of a motor pool response to TMS have been previously investigated with intramuscular electromyography (EMG), but this is limited in its capacity to detect many motor units (MUs) that constitute a motor evoked potential (MEP) in response to TMS. By simulating synthetic signals with known MU firing patterns, and recording high-density EMG signals from two human muscles, we show the feasibility of identifying firings of many MUs that comprise a MEP. We demonstrate the identification of firings of a large population of MUs in the broad recruitment range, up to maximal MEP amplitude, with fewer required stimuli compared to intramuscular EMG recordings. The methodology demonstrates an emerging possibility to study responses to TMS on a level of individual MUs in a non-invasive manner.

Modulation of spinal circuits following phase-dependent electrical stimulation of afferent pathways

Objective.Peripheral electrical stimulation (PES) of afferent pathways is a tool commonly used to induce neural adaptations in some neural disorders such as pathological tremor or stroke. However, the neuromodulatory effects of stimulation interventions synchronized with physiological activity (closed-loop strategies) have been scarcely researched in the upper-limb. Here, the short-term spinal effects of a 20-minute stimulation protocol where afferent pathways were stimulated with a closed-loop strategy named selective and adaptive timely stimulation (SATS) were explored in 11 healthy subjects.Approach. SATS was applied to the radial nerve in-phase (INP) or out-of-phase (OOP) with respect to the muscle activity of the extensor carpi radialis (ECR). The neural adaptations at the spinal cord level were assessed for the flexor carpi radialis (FCR) by measuring disynaptic Group I inhibition, Ia presynaptic inhibition, Ib facilitation from the H-reflex and estimation of the neural drive before, immediately after, and 30 minutes after the intervention.Main results.SATS strategy delivered electrical stimulation synchronized with the real-time muscle activity measured, with an average delay of 17 ± 8 ms. SATS-INP induced increased disynaptic Group I inhibition (77 ± 23% of baseline conditioned FCR H-reflex), while SATS-OOP elicited the opposite effect (125 ± 46% of baseline conditioned FCR H-reflex). Some of the subjects maintained the changes after 30 minutes. No other significant changes were found for the rest of measurements.Significance.These results suggest that the short-term modulatory effects of phase-dependent PES occur at specific targeted spinal pathways for the wrist muscles in healthy individuals. Importantly, timely recruitment of afferent pathways synchronized with specific muscle activity is a fundamental principle that shall be considered when tailoring PES protocols to modulate specific neural circuits. (NCT number 04501133).

Essential Tremor accentuates the pattern of tremor-band coherence between upper-limb muscles

Although Essential Tremor is one of the most common movement disorders, current treatment options are relatively limited. Peripheral tremor suppression methods have shown potential, but we do not currently know which muscles are most responsible for patients' tremor, making it difficult to optimize suppression methods. The purpose of this study was to quantify the relationships between the tremorogenic activity in muscles throughout the upper limb. Muscle activity was recorded from the 15 major superficial upper-limb muscles in 24 subjects with Essential Tremor while they held various postures or made upper-limb movements. We calculated the coherence in the tremor band (4-12 Hz) between the activity of all muscle pairs and the time-varying phase difference between sufficiently coherent muscle pairs. Overall, the observed pattern somewhat mirrored functional relationships: agonistic muscle pairs were most coherent and in phase, whereas antagonist and unrelated muscle pairs exhibited less coherence and were either consistently in phase, consistently antiphase, consistently out of phase (unrelated pairs only), or else inconsistent. Patients exhibited significantly more coherence than control subjects (p<0.001) in the vast majority of muscle pairs (95 out of 105). Furthermore, differences between patients and controls were most pronounced among agonists; thus, the coherence pattern existing in control subjects was accentuated in patients with ET. We conclude that tremor-band activity is broadly distributed among the muscles of the upper limb, challenging efforts to determine which muscles are most responsible for a patient's tremor.

Classification of Kinematic and Electromyographic Signals Associated with Pathological Tremor Using Machine and Deep Learning

Peripheral Electrical Stimulation (PES) of afferent pathways has received increased interest as a solution to reduce pathological tremors with minimal side effects. Closed-loop PES systems might present some advantages in reducing tremors, but further developments are required in order to reliably detect pathological tremors to accurately enable the stimulation only if a tremor is present. This study explores different machine learning (K-Nearest Neighbors, Random Forest and Support Vector Machines) and deep learning (Long Short-Term Memory neural networks) models in order to provide a binary (Tremor; No Tremor) classification of kinematic (angle displacement) and electromyography (EMG) signals recorded from patients diagnosed with essential tremors and healthy subjects. Three types of signal sequences without any feature extraction were used as inputs for the classifiers: kinematics (wrist flexion-extension angle), raw EMG and EMG envelopes from wrist flexor and extensor muscles. All the models showed high classification scores (Tremor vs. No Tremor) for the different input data modalities, ranging from 0.8 to 0.99 for the f₁ score. The LSTM models achieved 0.98 f₁ scores for the classification of raw EMG signals, showing high potential to detect tremors without any processed features or preliminary information. These models may be explored in real-time closed-loop PES strategies to detect tremors and enable stimulation with minimal signal processing steps.

Distribution of tremorogenic activity among the major superficial muscles of the upper limb in persons with Essential tremor

OBJECTIVE

Peripheral tremor suppression has the potential to reduce tremor, but we do not currently know where best to intervene. The purpose of this study was to characterize the distribution of tremorogenic activity among upper-limb muscles.

METHODS

Surface electromyography was recorded from the 15 major superficial muscles of the upper limb while 25 patients with Essential Tremor performed postural and kinetic tasks. We defined tremorogenic activity as power in the tremor band (4-8 Hz) and determined the distribution of this power among muscles.

RESULTS

The distribution varied considerably between patients (mean r = 0.58), but on average, the greatest power was found in the anterior deltoid and extensor carpi ulnaris muscles. Other muscles with high power included the extensor carpi radialis, pectoralis major, lateral deltoid, and brachialis muscles. This distribution was similar (mean r ≥ 0.88) for postural and kinetic tremor, various limb configurations, repetitions, and patient characteristics (sex, tremor severity, age of onset, and duration).

CONCLUSIONS

We identified a rough pattern in which muscles opposing gravity appeared to have the highest tremor-band power; we hypothesize that the distribution of tremorogenic muscle activity depends in part on the distribution of voluntary activity required by the task.

SIGNIFICANCE

Understanding which muscles exhibit the most tremorogenic activity is one of the steps in the pursuit of optimizing peripheral tremor suppression.

Segment-Wise Decomposition of Surface Electromyography to Identify Discharges Across Motor Neuron Populations

OBJECTIVE

The surface electromyography (EMG) decomposition techniques have shown promising results in neurophysiologic investigations, clinical diagnosis, and human-machine interfacing. However, current decomposition methods could only decode a limited number of motor units (MUs) because of the local convergence. The number of identified MUs remains similar even though more muscles or movements are involved, where multiple motor neuron populations are activated. The objective of this study was to develop a segment-wise decomposition strategy to increase the number of MU decoded from multiple motor neuron populations.

METHODS

The EMG signals were divided into several segments depending on the number of involved movements. The motor neurons, activated during each movement, were regarded as a population. The convolution kernel compensation (CKC) method was applied individually for each segment to decode the motor unit discharges from each motor neuron population. The MU filters were obtained in each segment and filtrated to estimate the MU spike trains (MUSTs) from the global EMG signals. The decomposition performance was validated on synthetic and experimental EMG signals.

MAIN RESULTS

From synthetic EMG signals generated by two motor neuron populations, the proposed segment-wise CKC (swCKC) decoded significantly more MUs during low and medium excitation levels, with an increased rate of 16.3% to 75.4% compared with the conventional CKC. From experimental signals recorded during ten motor tasks, 133±24 MUs with the pulse-to-noise ratio of 36.6±6.5 dB were identified for each subject by swCKC, whereas the conventional CKC identified only 43±12 MUs.

CONCLUSION AND SIGNIFICANCE

These results indicate the feasibility and superiority of the proposed swCKC to decode MU activities across motor neuron populations, extending the potential applications of EMG decomposition for neural decoding during multiple motor tasks.

The Effects of Deep Brain Stimulation on Motor Unit Activities in Parkinson's Disease based on High-Density Surface EMG Analysis

Tremor in Parkinson's disease (PD) is caused by synchronized activation bursts in limb muscles. Deep Brain Stimulation (DBS) is an effective clinical therapy for inhibiting tremor and improving movement disorders in PD patients. However, the neural mechanism of how tremor symptom is suppressed by DBS at motor unit (MU) level remains unclear. This paper developed a data acquisition platform for collecting physiological data in PD patients. Both high-density surface Electromyography (HD-sEMG) and kinematics data were collected concurrently before and after DBS surgery. The MU behaviors were obtained via HD-sEMG decomposition algorithm to reveal the effect of DBS on PD tremor. A data set of one tremor dominant PD patient acquired in pre-operation and post-operation (DBS-on) phases was analyzed. Preliminary results showed significant changes in MU firing rate and MU synchronization. The analysis approach introduced in this paper provides a novel perspective for studying the neural mechanism of DBS as revealed by MU activities. Clinical Relevance- This study presented an approach to investigate the effect of DBS therapy on improving tremor disorder of PD patients.

Online tracking of the phase difference between neural drives to antagonist muscle pairs in essential tremor patients

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.

Non-invasive electrical stimulation of peripheral nerves for the management of tremor

Pathological tremor in patients with essential tremor and Parkinsons disease is typically treated using medication or neurosurgical interventions. There is a widely recognized need for new treatments that avoid the side effects of current medications and do not carry the risks of surgical interventions. Building on decades of research and engineering development, non-invasive electrical stimulation of peripheral nerves has emerged as a safe and effective strategy for reducing pathologic tremor in essential tremor. This review surveys the peripheral electrical stimulation (PES) literature and summarizes effectiveness, safety, clinical translatability, and hypothesized tremor-reduction mechanisms of various PES approaches. The review also proposes guidelines for assessing tremor in the context of evaluating new therapies that combine the strengths of clinician assessments, patient evaluations, and novel motion sensing technology. The review concludes with a summary of future directions for PES, including expanding clinical access for patients with Parkinson's disease and leveraging large, at-home datasets to learn more about tremor physiology and treatment effect that will better characterize the state of tremor management and accelerate discovery of new therapies. Growing evidence suggests that non-invasive electrical stimulation of afferent neural pathways provides a viable new option for management of pathological tremor, with one specific PES therapy cleared for prescription and home use, suggesting that PES be considered along with medication and neurosurgical interventions for treatment of tremor. This article is part of the Special Issue "Tremor" edited by Daniel D. Truong, Mark Hallett, and Aasef Shaikh.

Wearable Peripheral Electrical Stimulation Devices for the Reduction of Essential Tremor: A Review

Essential tremor is the most common pathological tremor, with a prevalence of 6.3% in people over 65 years of age. This disorder interferes with a patient's ability to carry out activities of daily living independently, and treatment with medical and surgical interventions is often insufficient or contraindicated. Mechanical orthoses have not been widely adopted by patients due to discomfort and lack of discretion. Over the past 30 years, peripheral electrical stimulation has been investigated as a possible treatment for patients who have not found other treatment options to be satisfactory, with wearable devices revolutionizing this emerging approach in recent years. In this paper, an overview of essential tremor and its current medical and surgical treatment options are presented. Following this, tremor detection, measurement and characterization methods are explored with a focus on the measurement options that can be incorporated into wearable devices. Then, novel interventions for essential tremor are described, with a detailed review of open and closed-loop peripheral electrical stimulation methods. Finally, discussion of the need for wearable closed-loop peripheral electrical stimulation devices for essential tremor, approaches in their implementation, and gaps in the literature for further research are presented.

Intramuscular Stimulation of Muscle Afferents Attains Prolonged Tremor Reduction in Essential Tremor Patients

This study proposes and clinically tests intramuscular electrical stimulation below motor threshold to achieve prolonged reduction of wrist flexion/extension tremor in Essential Tremor (ET) patients. The developed system consisted of an intramuscular thin-film electrode structure that included both stimulation and electromyography (EMG) recording electrodes, and a control algorithm for the timing of intramuscular stimulation based on EMG (closed-loop stimulation). Data were recorded from nine ET patients with wrist flexion/extension tremor recruited from the Gregorio Marañón Hospital (Madrid, Spain). Patients participated in two experimental sessions comprising: 1) sensory stimulation of wrist flexors/extensors via thin-film multichannel intramuscular electrodes; and 2) surface stimulation of the nerves innervating the same target muscles. For each session, four of these patients underwent random 60-s trials of two stimulation strategies for each target muscle: 1) selective and adaptive timely stimulation (SATS) - based on EMG of the antagonist muscle; and 2) continuous stimulation (CON) of target muscles. Two patients underwent SATS stimulation trials alone while the other three underwent CON stimulation trials alone in each session. Kinematics of wrist, elbow, and shoulder, together with clinical scales, were used to assess tremor before, right after, and 24 h after each session. Intramuscular SATS achieved, on average, 32% acute (during stimulation) tremor reduction on each trial, while continuous stimulation augmented tremorgenic activity. Furthermore, tremor reduction was significantly higher using intramuscular than surface stimulation. Prolonged reduction of tremor amplitude (24 h after the experiment) was observed in four patients. These results showed acute and prolonged (24 h) tremor reduction using a minimally invasive neurostimulation technology based on SATS of primary sensory afferents of wrist muscles. This strategy might open the possibility of an alternative therapeutic approach for ET patients.

Peripheral electrical stimulation to reduce pathological tremor: a review

Interventions to reduce tremor in essential tremor (ET) and Parkinson’s disease (PD) clinical populations often utilize pharmacological or surgical therapies. However, there can be significant side effects, decline in effectiveness over time, or clinical contraindications for these interventions. Therefore, alternative approaches must be considered and developed. Some non-pharmacological strategies include assistive devices, orthoses and mechanical loading of the tremorgenic limb, while others propose peripheral electrical stimulation. Specifically, peripheral electrical stimulation encompasses strategies that activate motor and sensory pathways to evoke muscle contractions and impact sensorimotor function. Numerous studies report the efficacy of peripheral electrical stimulation to alter tremor generation, thereby opening new perspectives for both short- and long-term tremor reduction. Therefore, it is timely to explore this promising modality in a comprehensive review. In this review, we analyzed 27 studies that reported the use of peripheral electrical stimulation to reduce tremor and discuss various considerations regarding peripheral electrical stimulation: the stimulation strategies and parameters, electrodes, experimental designs, results, and mechanisms hypothesized to reduce tremor. From our review, we identified a high degree of disparity across studies with regard to stimulation patterns, experimental designs and methods of assessing tremor. Having standardized experimental methodology is a critical step in the field and is needed in order to accurately compare results across studies. With this review, we explore peripheral electrical stimulation as an intervention for tremor reduction, identify the limitations and benefits of the current state-of-the-art studies, and provide ideas to guide the development of novel approaches based on the neural circuitries and mechanical properties implied in tremor generation.