Rationale and Evidence for Peripheral Nerve Stimulation for Treating Essential Tremor

Background:

There is growing recognition of peripheral stimulation techniques for controlling arm symptoms in essential tremor (ET). Recently, the FDA gave clearance to the Cala system, a device worn around the wrist to treat arm tremors. The Cala system stimulates the sensory afferents of the peripheral nerves with high-frequency pulses. These pulses are delivered to the median and radial nerves alternately at the tremor frequency of the individual patient.

Methods:

The PubMed database was searched using the terms (“Essential Tremor”[Mesh] OR “essential tremor” [Title/Abstract] OR “tremor” [Title/Abstract]) AND (“peripheral arm stimulation” [Title/Abstract] OR “Cala device” [Title/Abstract] OR “sensory afferent stimulation” [Title/Abstract] OR “afferent stimulation” [Title/Abstract] OR “arm stimulation” [Title/Abstract] OR “peripheral nerve stimulation” [Title/Abstract]).

Results:

The search yielded 54 articles. Many studies discussed the rationale and various strategies for peripheral modulation of tremor. While the Cala system was found to be safe and well-tolerated in ET, data on efficacy revealed mixed findings. In a large randomized, blinded trial (n = 77), the primary outcome evaluated with spiral drawing task did not improve but the secondary outcomes reflected by the arm tremor severity and the activities of the daily living score revealed 20–25% improvements. A subsequent trial (n = 323) found that the in-home use of the Cala device led to improvements of similar magnitude lasting for at least three months but the clinical assessments were open-labeled.

Discussion:

Peripheral stimulation techniques are promising therapeutic modalities for treating ET symptoms. Stimulation of sensory afferent nerve fibers at the wrist can potentially modulate the peripheral and central components of the tremor network. Although the Cala system is user-friendly, safe, and well-tolerated, the current clinical evidence on the efficacy is inconsistent and insufficient. Thus, more data is warranted for implementing peripheral nerve stimulation as a standard of care for ET.

Highlights

The current review discusses the rationale, background, and potential mechanisms for using peripheral arm stimulation devices for treating ET. The Cala system is a wrist-worn peripheral nerve stimulation device that received FDA clearance to treat arm tremors. The current review evaluates the evidence for the safety and efficacy of using the Cala system and similar devices in clinical practice.

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.

Genetic targeting of adult Renshaw cells using a Calbindin 1 destabilized Cre allele for intersection with Parvalbumin or Engrailed1

Renshaw cells (RCs) are one of the most studied spinal interneurons; however, their roles in motor control remain enigmatic in part due to the lack of experimental models to interfere with RC function, specifically in adults. To overcome this limitation, we leveraged the distinct temporal regulation of Calbindin (Calb1) expression in RCs to create genetic models for timed RC manipulation. We used a Calb1 allele expressing a destabilized Cre (dgCre) theoretically active only upon trimethoprim (TMP) administration. TMP timing and dose influenced RC targeting efficiency, which was highest within the first three postnatal weeks, but specificity was low with many other spinal neurons also targeted. In addition, dgCre showed TMP-independent activity resulting in spontaneous recombination events that accumulated with age. Combining Calb1-dgCre with Parvalbumin (Pvalb) or Engrailed1 (En1) Flpo alleles in dual conditional systems increased cellular and timing specificity. Under optimal conditions, Calb1-dgCre/Pvalb-Flpo mice targeted 90% of RCs and few dorsal horn neurons; Calb1-dgCre/En1-Flpo mice showed higher specificity, but only a maximum of 70% of RCs targeted. Both models targeted neurons throughout the brain. Restricted spinal expression was obtained by injecting intraspinally AAVs carrying dual conditional genes. These results describe the first models to genetically target RCs bypassing development.

Different effects of essential tremor and Parkinsonian tremor on multiscale dynamics of hand tremor

OBJECTIVE

Essential tremor (ET) and Parkinsonian tremor (PT) are often clinically misdiagnosed due to the overlapping characteristics of their hand tremor. We aim to examine if ET and PT influence the multiscale dynamics of hand tremor, as quantified using complexity, differently, and if such complexity metric is of promise to help identify ET from PT.

METHODS

Forty-eight participants with PT and 48 with ET performed two 30-second tests within each of the following conditions: sitting while resting arms or outstretching arms horizontally. The hand tremor was captured by accelerometers secured to the dorsum of each hand. The complexity was quantified using multiscale entropy.

RESULTS

Compared to PT group, ET group had lower complexity of both hands across conditions (F > 34.2, p < 0.001). Lower complexity was associated with longer disease duration (r² > 0.15, p < 0.009) in both PT and ET, and within PT, greater Unified Parkinson's Disease Rating Scale-III UPDRS-III scores (r² > 0.18, p < 0.009). Receiver-operating-characteristic curves revealed that the complexity metric can distinguish ET from PT (area-under-the-curve > 0.77, cut-off value = 48 (postural), 49 (resting)), which was confirmed in a separate dataset with ET and PT that were clearly diagnosed in prior work.

CONCLUSIONS

The PT and ET have different effects on hand tremor complexity, and this metric is promising to help the identification of ET and PT, which still needs to be confirmed in future studies.

SIGNIFICANCE

The characteristics of multiscale dynamics of the hand tremor, as quantified by complexity, provides novel insights into the different pathophysiology between ET and PT.

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.

COMPARISON OF THEORIES OF REST TREMOR MECHANISM IN PARKINSON’S DISEASE: CENTRAL OSCILLATOR (SOURCE-TRIGGERED OSCILLATIONS) AND FEEDBACK-INDUCED INSTABILITY IN THE SENSORIMOTOR LOOP (SELF-SUSTAINED OSCILLATIONS)

Rest tremor is one of the most common and disabling symptoms of Parkinson’s disease (PD). The exact neural origin of rest tremor is still not clearly understood. Understanding the origin of rest tremor is important as it may aid in optimizing existing treatment strategies such as Deep Brain Stimulation or in developing new treatment strategies for rest tremor reduction. There are broadly two theories that are gaining prominence for rest tremor generation in PD. The first theory is the central oscillator theory that states that the rest tremor is triggered by an oscillatory source in the brain. The second theory is the feedback-induced instability theory that states that the rest tremor arises out of a feedback-induced instability in the sensorimotor loop. This paper analyzes validity of the two theories based on established clinical observations of Parkinsonian rest tremor by using representative simulation examples. Finally, based on our analysis, we propose two test-worthy experiments for further validation.

Explaining Parkinsonian postural sway variabilities using intermittent control theory

Postural impairment due to neuro-degenerative disorders such as Parkinson's Disease (PD) leads to restricted gait patterns, fall-related injuries, decreased mobility, and loss of functional independence. Though several clinical and posturographic studies have attempted to reveal the complex pathophysiology involved in PD, the diversity of Parkinsonian population makes them unclear and sometimes even contradictory. For instance, studies related to the Center of Pressure (CoP) sway during quiet stance in PD patients highlight both increase and reduction of magnitude in contrast to age-matched healthy individuals. A possible explanation for this contradiction is presented in this article. While the presence of intermittent control has been observed in postural control in human quiet stance, we hypothesize that one of the factors that affects postural instability in PD might be the increase in intermittency in active feedback control. Using a simulation model representing the Anterior-Posterior dynamics of human quiet standing, the intermittent control strategy is first contrasted against continuous control strategy in terms of stability, energy efficiency and settling time, thus establishing the inherent advantages of an intermittent control strategy. Further, the ability of the intermittent control strategy to explain several clinical observations in PD is demonstrated. An experimental pilot study is also conducted to support the simulation study, and several body sway parameters derived from recordings of CoP are presented. The presented results are in close agreement with reported clinical observations and may also prove useful for the assessment of disease progression and future fall risk.

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

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.

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.

Modeling musculoskeletal kinematic and dynamic redundancy using null space projection

The coordination of the human musculoskeletal system is deeply influenced by its redundant structure, in both kinematic and dynamic terms. Noticing a lack of a relevant, thorough treatment in the literature, we formally address the issue in order to understand and quantify factors affecting the motor coordination. We employed well-established techniques from linear algebra and projection operators to extend the underlying kinematic and dynamic relations by modeling the redundancy effects in null space. We distinguish three types of operational spaces, namely task, joint and muscle space, which are directly associated with the physiological factors of the system. A method for consistently quantifying the redundancy on multiple levels in the entire space of feasible solutions is also presented. We evaluate the proposed muscle space projection on segmental level reflexes and the computation of the feasible muscle forces for arbitrary movements. The former proves to be a convenient representation for interfacing with segmental level models or implementing controllers for tendon driven robots, while the latter enables the identification of force variability and correlations between muscle groups, attributed to the system’s redundancy. Furthermore, the usefulness of the proposed framework is demonstrated in the context of estimating the bounds of the joint reaction loads, where we show that misinterpretation of the results is possible if the null space forces are ignored. This work presents a theoretical analysis of the redundancy problem, facilitating application in a broad range of fields related to motor coordination, as it provides the groundwork for null space characterization. The proposed framework rigorously accounts for the effects of kinematic and dynamic redundancy, incorporating it directly into the underlying equations using the notion of null space projection, leading to a complete description of the system.

A method for characterizing essential tremor from the shoulder to the wrist

BACKGROUND

Despite the pervasive and devastating effect of Essential Tremor (ET), the distribution of ET throughout the upper limb is unknown. We developed a method for characterizing the distribution of ET and performed a preliminary characterization in a small number of subjects with ET.

METHODS

Using orientation sensors and inverse kinematics, we measured tremor in each of the seven major degrees of freedom (DOF) from the shoulder to the wrist while ten patients with mild ET assumed 16 different postures. We described the tremor in each DOF in terms of power spectral density measures and investigated how tremor varied between DOF, postures, gravitational torques, and repetitions.

FINDINGS

Our method successfully resulted in tremor measures in each DOF, allowing one to compare tremor between DOF and determine the distribution of tremor throughout the upper limb, including how the distribution changes with posture. In our small number of subjects, we found that the amount of power in the frequency band associated with ET (4-12Hz) was lowest in the shoulder and greatest in the wrist. Similarly, the existence and amplitude of peaks in this band increased from proximal to distal. Although the amount of tremor differed significantly between postures, we did not find any clear patterns with changes in posture or gravitational torque.

INTERPRETATION

This method can be used to characterize the distribution of tremor throughout the upper limb. Our preliminary characterization suggests that the amount of tremor increases in a proximal-distal manner.

A Possible Explanation of How High-Frequency Deep Brain Stimulation Suppresses Low-Frequency Tremors in Parkinson's Disease

Parkinson's disease (PD) is a neurodegenerative disorder of the central nervous system and one of its key symptoms is rest tremor. Deep brain stimulation (DBS) effectively suppresses rest tremor in Parkinson's disease. Despite being a successful treatment option, its underlying principle and the mechanism by which it attenuates tremors is not yet fully understood. Since existing methods for tuning DBS parameters are largely trial and error, understanding how DBS works can help to reduce time and costs, and could also ultimately lead to better treatment strategies for PD. In this paper, we set out to analyze how a high-frequency stimulation applied through DBS can help reduce the low-frequency rest tremors observed in PD patients. We identify key elements in the sensorimotor loop (the feedback loop consisting of sensory feedbacks and motor responses) that play a role in the interaction of high-frequency DBS signal and the low-frequency tremor. Based on the analysis of these elements, we draw insights about the working of DBS and the role of frequency and the nature of stimulation. We verify these observations with numerical examples and a bench top experimental example.

AN ANGLE-EMG BIOMECHANICAL MODEL OF THE HUMAN ELBOW JOINT

The biomechanical model of the human elbow joint is extensively studied. In the model, the surface electromyography (sEMG) is used as the input signal, whereas the muscle force or muscle torque is commonly considered as the output signal. The estimation of the actual muscle force or torque is important to effectively modulate the tremor suppression. However, the measurement of the muscle force or torque in vivo is difficult. In this paper, a new angle-to-EMG biomechanical model of the elbow joint was developed and evaluated by comparing the measured sEMG with the calculated sEMG. Three sources of the sEMG signal, namely, the central nervous system (CNS), the Golgi tendon and the muscle spindle were considered in this model. Furthermore, a local PID algorithm was proposed to describe the impact of the CNS on the motor neuron and the Golgi tendon model was used to transform muscle forces to stimulus signals. The model was calibrated by an improved search procedure combining the Powell search and the direct search to determine optimal model parameters. In the experiment, an sEMG signal acquisition system was established to measure the sEMG signal and the elbow joint angle. The experimental results, the predicted sEMG signal well following the measured sEMG, demonstrated that the calibrated model could be used to estimate in vivo sEMG signals and is beneficial to explore the peripheral neural system and the pathogenesis of tremor.

Exploring the effect of electrical muscle stimulation as a novel treatment of intractable tremor in Parkinson's disease

BACKGROUND

As the pathophysiology of tremor in Parkinson disease (PD) involves a complex interaction between central and peripheral mechanisms, we propose that modulation of peripheral reflex mechanism by electrical muscle stimulation (EMS) may improve tremor temporarily.

OBJECTIVES

To determine the efficacy of EMS as a treatment for drug resistant tremor in PD patients.

METHODS

This study was a single-blinded, quasi-experimental study involving 34 PD patients with classic resting tremor as confirmed by tremor analysis. The EMS was given at 50Hz over the abductor pollicis brevis and interrosseus muscles for 10s with identified tremor parameters before and during stimulation as primary outcomes.

RESULTS

Compared to before stimulation, we observed a significant reduction in the root mean square (RMS) of the angular velocity (p<0.001) and peak magnitude (p<0.001) of resting tremor while tremor frequency (p=0.126) and dispersion (p=0.284) remained unchanged during stimulation. The UPDRS tremor score decreased from 10.59 (SD=1.74) before stimulation to 8.85 (SD=2.19) during stimulation (p<0.001). The average percentage of improvement of the peak magnitude and RMS angular velocity was 49.57% (SD=38.89) and 43.81% (SD=33.15) respectively. 70.6% and 61.8% of patients experienced at least 30% tremor attenuation as calculated from the peak magnitude and RMS angular velocity respectively.

CONCLUSIONS

Our study demonstrated the efficacy of EMS in temporarily improving resting tremor in medically intractable PD patients. Although tremor severity decreased, they were not completely eliminated and continued with a similar frequency, thus demonstrating the role of peripheral reflex mechanism in the modulation of tremor, but not as a generator. EMS should be further explored as a possible therapeutic intervention for tremor in PD.

Online tremor suppression using electromyography and low-level electrical stimulation

Tremor is one of the most prevalent movement disorders. There is a large proportion of patients (around 25%) in whom current treatments do not attain a significant tremor reduction. This paper proposes a tremor suppression strategy that detects tremor from the electromyographic signals of the muscles from which tremor originates and counteracts it by delivering electrical stimulation to the antagonist muscles in an out of phase manner. The detection was based on the iterative Hilbert transform and stimulation was delivered above the motor threshold (motor stimulation) and below the motor threshold (sensory stimulation). The system was tested on six patients with predominant wrist flexion/extension tremor (four with Parkinson disease and two with Essential tremor) and led to an average tremor reduction in the range of 46%-81% and 35%-48% across five patients when using the motor and sensory stimulation, respectively. In one patient, the system did not attenuate tremor. These results demonstrate that tremor attenuation might be achieved by delivering electrical stimulation below the motor threshold, preventing muscle fatigue and discomfort for the patients, which sets the basis for the development of an alternative treatment for tremor.

On the use of fixed-intensity functional electrical stimulation for attenuating essential tremor

A great proportion of essential tremor (ET) patients have not so far been able to receive functional benefits from traditional therapies. In this regard, the use of functional electrical stimulation (FES) has been proposed for reducing tremor amplitude by stimulating muscles in antiphase with respect to the trembling motion. Although some studies have reported success in terms of tremor attenuation, drawbacks still exist that prevent the method from being used in real-life applications. In this article, we explore an alternative approach: a strategy based on the hypothesis that FES-induced constant muscle contraction may provide functional benefit for tremor patients. To evaluate the proposed strategy, experiments were conducted in which stimulation was intermittently turned on and off while the subjects performed a static motor task. The results of the proposed experimental protocol indicate that tremor attenuation using this strategy is feasible, as consistent tremor attenuation levels were obtained in eight out of 10 ET patients. Nonetheless, tremor reduction was not instantaneous for all successful trials, indicating that prior training with FES may improve the overall response. Furthermore, although simpler assistive devices may potentially be designed based on this technique, some experimental difficulties still exist, which suggests that further studies are necessary.

RBF-based technique for statistical demodulation of pathological tremor

This paper presents an innovative technique based on the joint approximation capabilities of radial basis function (RBF) networks and the estimation capability of the multivariate iterated Hilbert transform (IHT) for the statistical demodulation of pathological tremor from electromyography (EMG) signals in patients with Parkinson's disease. We define a stochastic model of the multichannel high-density surface EMG by means of the RBF networks applied to the reconstruction of the stochastic process (characterizing the disease) modeled by the multivariate relationships generated by the Karhunen-Loéve transform in Hilbert spaces. Next, we perform a demodulation of the entire random field by means of the estimation capability of the multivariate IHT in a statistical setting. The proposed method is applied to both simulated signals and data recorded from three Parkinsonian patients and the results show that the amplitude modulation components of the tremor oscillation can be estimated with signal-to-noise ratio close to 30 dB with root-mean-square error for the estimates of the tremor instantaneous frequency. Additionally, the comparisons with a large number of techniques based on all the combinations of the RBF, extreme learning machine, backpropagation, support vector machine used in the first step of the algorithm; and IHT, empirical mode decomposition, multiband energy separation algorithm, periodic algebraic separation and energy demodulation used in the second step of the algorithm, clearly show the effectiveness of our technique. These results show that the proposed approach is a potential useful tool for advanced neurorehabilitation technologies that aim at tremor characterization and suppression.

The effects of isometric resistance training on stretch reflex induced tremor in the knee extensor muscles

This study examines the effect of 4 wk of high-intensity isometric resistance training on induced tremor in knee extensor muscles. Fourteen healthy volunteers were assigned to either the training group (n = 7) or the nontraining control group (n = 7). Induced tremor was assessed by measuring force fluctuations during anisometric contractions against spring loading, whose compliance was varied to allow for preferential activation of the short or long latency stretch reflex components. Effects of high-intensity isometric resistance training on induced tremor was assessed under two contraction conditions: relative force matching, where the relative level of activity was equal for both pre- and post-training sessions, set at 30% maximum voluntary contraction (MVC), and absolute force matching, where the level of activity was set to 30% pretrained MVC. The training group experienced a 26.5% increase in MVC in contrast to the 0.8% for the control group. For relative force-matching contractions, induced tremor amplitude and frequency did not change in either the training or control group. During absolute force-matching contractions, induced tremor amplitude was decreased by 37.5% and 31.6% for the short and long components, respectively, with no accompanying change in frequency, for the training group. No change in either measure was observed in the control group for absolute force-matching contractions. The results are consistent with high-intensity isometric resistance training induced neural changes leading to increased strength, coupled with realignment of stretch reflex automatic gain compensation to the new maximal force output. Also, previous reported reductions in anisometric tremor following strength training may partly be due to changed stretch reflex behavior.

Simulation of tremor on 3-dimentional musculoskeletal model of wrist joint and experimental verification?

A musculoskeletal model that allows to simulate the tremor of wrist joint with three degrees of freedom (DoFs) is developed. The model includes five muscles, extensor carpi radialis brevis, extensor carpi radialis longus, extensor carpi ulnaris, flexor carpi radialis and flexor carpi ulnaris. Simulation of tremor generation based on the 3-DoF model is performed. The tremor disorder can be generated in two directions: flexion-extension and radia-ulnar deviation. Accordingly, experiment is conducted on healthy subjects to verify the feasibility of artificial tremor generation via functional electrical stimulation (FES). Simulation results have shown qualitative agreement with the experimental results.

Inflammatory myopathy in a patient with postural and kinetik tremor

Essential tremor (ET) is a common neurological disease of unknown etiopathogenesis, possibly neurodegenerative, characterized by kinetic tremor at the arms. Here we reported the case of an HCV-positive patient with inflammatory myopathy, who did not develop typical neuromuscular signs or symptoms during at least 7 years of hyperCKemia, in whom kinetic tremor of the arms was the prominent clinical feature, suggesting a possible diagnosis of ET. After 3 months of treatment with corticosteroids/methotrexate, creatine kinase (CK) levels were nearly normal and the tremor was remarkably improved. To our knowledge, similar cases have not been previously reported. Postural tremor can be present in muscular diseases, but only very rarely tremor has been reported as a major clinical feature. Because inflammatory myopathies are potentially treatable conditions it is very important to consider this diagnosis. Our case suggests that in patients with isolated postural and kinetic tremor routine laboratory assays should include CK blood screening.

A model of the surface electromyogram in pathological tremor

The study developed a novel multi-scale model for simulating the surface electromyogram (EMG) of an antagonistic pair of muscles during pathological tremor. By combining and expanding mathematical descriptions from motor units to limb kinematics, the model constitutes the first attempt to simulate the surface EMG and the individual motor unit activity under the influence of descending voluntary command, oscillatory noise in the descending signal, and afferent feedback when controlling a freely moving limb to achieve a predefined angular trajectory. The oscillatory noise was adjusted to simulate various types of pathological tremor. The simulations replicated previously reported experimental results for the power spectral density of the surface EMG, the angular velocity of the limb, and single motor unit activity. The model provides a powerful tool for extracting information about how the surface EMG can be used to describe tremor in various conditions, including different tremor frequencies and intensities, that cannot be achieved solely with experimental approaches.

An integrative model of the surface EMG in pathological tremor

A novel integrative model for simulating the surface EMG signal during pathological tremor is presented. The model combines neuromuscular elements, biomechanical descriptions, and surface EMG generation. First single motor unit spike trains are generated based on the sum of the simulated descending drive, afferent input and an oscillatory noise causing tremor. Based on this activity pattern, the muscle force is estimated, from which the limb movement is derived. The surface EMG is simulated as the sum of the surface action potentials generated by the active motor units. The model was able to simulate several features of tremor that have been previously observed experimentally, including the spectral characteristics of the surface EMG during tremor and the pattern of activity of single motor units.