Pathological Tremor Research Articles

Tremor

Tremor, defined as a rhythmic and involuntary movement of any body part, is the most prevalent movement disorder, affecting millions of people in the United States. All adults have varying degrees of physiological tremor so it is imperative to distinguish physiological tremor from pathological tremor types. Tremor is not inherently dangerous, but it can cause significant disability at home and in the workplace. Common tremors like essential tremor and Parkinson disease tremor can be recognized by most clinicians at the early stages for the initiation of disease-specific medical therapies. Less common tremors, such as those induced by drugs or brain lesions, are also important to recognize because they may be more refractory to medical therapies and may require earlier referral to a neurological specialist. In patients with the most progressive and severe tremors that are resistant to medical therapies, surgical interventions are available and typically target deep brain regions with stimulation or lesioning. This Grand Rounds review describes the evaluation and evidence-based management of the most common tremors, essential tremor and Parkinson disease tremor.

Robust Controller for Tremor Suppression at Musculoskeletal Level in Human Wrist

Tremor is a rhythmical and involuntary oscillatory movement of a body part and it is one of the most common movement disorders. Orthotic devices have been under investigation as a noninvasive tremor suppression alternative to medication or surgery. The challenge in musculoskeletal tremor suppression is estimating and attenuating the tremor motion without impeding the patient's intentional motion. In this research a robust tremor suppression algorithm was derived for patients with pathological tremor in the upper limbs. First the motion in the tremor frequency range is estimated using a high-pass filter. Then, by applying the backstepping method the appropriate amount of torque is calculated to drive the output of the estimator toward zero. This is equivalent to an estimation of the tremor torque. It is shown that the arm/orthotic device control system is stable and the algorithm is robust despite inherent uncertainties in the open-loop human arm joint model. A human arm joint simulator, capable of emulating tremorous motion of a human arm joint was used to evaluate the proposed suppression algorithm experimentally for two types of tremor, Parkinson and essential. Experimental results show 30-42 dB (97.5-99.2%) suppression of tremor with minimal effect on the intentional motion.

Medical treatment of essential tremor.

Essential tremor (ET) is the most common pathological tremor characterized by upper limb action—postural tremor (PT)/kinetic tremor (KT). There are no specific neuropathological or biochemical abnormalities in ET. The disability is consequent to amplitude of KT, which may remain mild without handicap or may become disabling. The most effective drugs for sustained tremor control are propranolol and primidone. Symptomatic drug treatment must be individualized depending on the circumstances that provoke the tremor-related disability. Broad guidelines for treatment are discussed in this review. Patients may be treated intermittently only on stressful occasions with propranolol, clonazepam, or primidone monotherapy, or an alcoholic drink. Those with persistently disabling tremor need continued treatment.

Adaptive sliding bandlimited multiple fourier linear combiner for estimation of pathological tremor

Pathological tremor is a roughly sinusoidal movement and impacts individuals’ daily living activities. Biomechanical loading is employed as a potential method for tremor suppression with the accurate estimation of amplitude and frequency of tremor signals. In this paper, a study on tremor is conducted and the characteristics of tremor signals are analyzed. An adaptive sliding Bandlimited multiple Fourier linear combiner (ASBMFLC) algorithm is proposed to estimate the different desired signals with sliding frequency band and zero-phase lag. This method incorporates digital filter, Weighted-Frequency Fourier Linear Combiner (WFLC) and Bandlimited Multiple Fourier Linear Combiner (BMFLC) with modification of fundamental frequency and limitation of frequency range. Based on the experimental tremor signals, WFLC, BMFLC and the proposed algorithm are evaluated, respectively. The experimental results show that the developed algorithm could adapt to the unknown dominant frequency for determining the interesting frequency band without prior information. Furthermore, the improved method could provide higher accurate estimation of tremor and extract the voluntary components from measured signals, compared with WFLC and BMFLC, respectively.

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.

A neural network approach for feature extraction and discrimination between Parkinsonian tremor and essential tremor

Essential tremor (ET) and the tremor in Parkinson's disease (PD) are the two most common pathological tremor with a certain overlap in the clinical presentation. The main purpose of this work is to use an artificial neural network to select the best features and to discriminate between the two types of tremors using spectral analysis of tremor time-series recorded by accelerometry and surface EMG signals. The Soft-Decision wavelet-based technique is to be used in this work in order to obtain a 16 bands approximate spectral representation of both accelerometer and two EMG signals of two sets of data (training and test). The training set consists of 21 ET subjects and 19 PD subjects while the test set consists of 20 ET and 20 PD subjects. The data has been recorded for diagnostic purposes in the Department of Neurology of the University of Kiel, Germany. A neural network of the type feed forward back propagation has been used to find the frequency bands associated with the different signals that yield better discrimination efficiency on training data. The same designed network is used to discriminate the test set. Efficiency result of 87.5% was obtained using two different bands from each of the three signals under test. The artificial neural network has been used successfully in both feature extraction and in pattern matching tasks in a complete classification system.

Pathological tremor prediction using surface electromyogram and acceleration: potential use in ‘ON–OFF’ demand driven deep brain stimulator design

Objective. We present a proof of concept for a novel method of predicting the onset of pathological tremor using non-invasively measured surface electromyogram (sEMG) and acceleration from tremor-affected extremities of patients with Parkinson’s disease (PD) and essential tremor (ET). Approach. The tremor prediction algorithm uses a set of spectral (Fourier and wavelet) and nonlinear time series (entropy and recurrence rate) parameters extracted from the non-invasively recorded sEMG and acceleration signals. Main results. The resulting algorithm is shown to successfully predict tremor onset for all 91 trials recorded in 4 PD patients and for all 91 trials recorded in 4 ET patients. The predictor achieves a 100% sensitivity for all trials considered, along with an overall accuracy of 85.7% for all ET trials and 80.2% for all PD trials. By using a Pearson’s chi-square test, the prediction results are shown to significantly differ from a random prediction outcome. Significance. The tremor prediction algorithm can be potentially used for designing the next generation of non-invasive closed-loop predictive ON–OFF controllers for deep brain stimulation (DBS), used for suppressing pathological tremor in such patients. Such a system is based on alternating ON and OFF DBS periods, an incoming tremor being predicted during the time intervals when DBS is OFF, so as to turn DBS back ON. The prediction should be a few seconds before tremor re-appears so that the patient is tremor-free for the entire DBS ON–OFF cycle and the tremor-free DBS OFF interval should be maximized in order to minimize the current injected in the brain and battery usage.

Multiphysics modeling of magnetorheological dampers

The dynamics of a small scale magnetorheological damper were modeled and analyzed using multiphysics commercial finite element software to couple the electromagnetic field distribution with the non-Newtonian fluid flow. The magnetic flux lines and field intensity generated within the damper and cyclic fluid flow in the damper under harmonic motion were simulated with the AC/DC and CFD physics modules of COMSOL Multiphysics, respectively. Coupling of the physics is achieved through a modified Bingham plastic definition, relating the fluid’s dynamic viscosity to the intensity of the induced magnetic field. Good agreement is confirmed between simulation results and experimentally observed resistance forces in the damper. This study was conducted to determine the feasibility of utilizing magnetorheological dampers in a medical orthosis for pathological tremor attenuation. The implemented models are thus dimensioned on a relatively small scale. The method used, however, is not specific to the damper’s size or geometry and can be extended to larger-scale devices with little or no complication.

Power spectral density analysis of physiological, rest and action tremor in Parkinson’s disease patients treated with deep brain stimulation

BackgroundObservation of the signals recorded from the extremities of Parkinson’s disease patients showing rest and/or action tremor reveal a distinct high power resonance peak in the frequency band corresponding to tremor. The aim of the study was to investigate, using quantitative measures, how clinically effective and less effective deep brain stimulation protocols redistribute movement power over the frequency bands associated with movement, pathological and physiological tremor, and whether normal physiological tremor may reappear during those periods that tremor is absent.MethodsThe power spectral density patterns of rest and action tremor were studied in 7 Parkinson’s disease patients treated with (bilateral) deep brain stimulation of the subthalamic nucleus. Two tests were carried out: 1) the patient was sitting at rest; 2) the patient performed a hand or foot tapping movement. Each test was repeated four times for each extremity with different stimulation settings applied during each repetition. Tremor intermittency was taken into account by classifying each 3-second window of the recorded angular velocity signals as a tremor or non-tremor window.ResultsThe distribution of power over the low frequency band (<3.5 Hz – voluntary movement), tremor band (3.5-7.5 Hz) and high frequency band (>7.5 Hz – normal physiological tremor) revealed that rest and action tremor show a similar power-frequency shift related to tremor absence and presence: when tremor is present most power is contained in the tremor frequency band; when tremor is absent lower frequencies dominate. Even under resting conditions a relatively large low frequency component became prominent, which seemed to compensate for tremor. Tremor absence did not result in the reappearance of normal physiological tremor.ConclusionParkinson’s disease patients continuously balance between tremor and tremor suppression or compensation expressed by power shifts between the low frequency band and the tremor frequency band during rest and voluntary motor actions. This balance shows that the pathological tremor is either on or off, with the latter state not resembling that of a healthy subject. Deep brain stimulation can reverse the balance thereby either switching tremor on or off.

On-Off Tremor Suppression Orthosis with Electromagnetic Brake

Pathological tremor is a common neurological movement disorder characterized by involuntary rhythmic oscillation of body parts. Available treatments are often insufficiently effective or are accompanied by severe side effects. This work proposes a lightweight, portable elbow tremor suppression orthosis using an electromagnetic brake (EB) with on-off actuation scheme. The device reduces tremor amplitude and could potentially be donned under clothes. At this stage of the project, the focus is on action tremor (postural) such as essential tremor. The elbow joint is commonly affected by tremor; it can be modelled as a single Degree Of Freedom (DOF) joint and was selected to test our hypothesis and prototype. The orthosis is actuated by an (EB). The algorithm alternates between full suppression and no suppression, and relies on the high frequency nature of tremor relative to the frequency of Activities of Daily Living (ADL). A MEMS gyro signal is processed to assess the tremor component. The system successfully reduces tremor amplitude with over 88% of tremor signal power reduction.

Using a Smart Phone as a Standalone Platform for Detection and Monitoring of Pathological Tremors

Introduction: Smart phones are becoming ubiquitous and their computing capabilities are ever increasing. Consequently, more attention is geared toward their potential use in research and medical settings. For instance, their built-in hardware can provide quantitative data for different movements. Therefore, the goal of the current study was to evaluate the capabilities of a standalone smart phone platform to characterize tremor. Results: Algorithms for tremor recording and online analysis can be implemented within a smart phone. The smart phone provides reliable time- and frequency-domain tremor characteristics. The smart phone can also provide medically relevant tremor assessments. Discussion: Smart phones have the potential to provide researchers and clinicians with quantitative short- and long-term tremor assessments that are currently not easily available. Methods: A smart phone application for tremor quantification and online analysis was developed. Then, smart phone results were compared to those obtained simultaneously with a laboratory accelerometer. Finally, results from the smart phone were compared to clinical tremor assessments.

The potential roles of T-type Ca2+ channels in motor coordination.

Specific behavioral patterns are expressed by complex combinations of muscle coordination. Tremors are simple behavioral patterns and are the focus of studies investigating motor coordination mechanisms in the brain. T-type Ca2+ channels mediate intrinsic neuronal oscillations and rhythmic burst spiking, and facilitate the generation of tremor rhythms in motor circuits. Despite substantial evidence that T-type Ca2+ channels mediate pathological tremors, their roles in physiological motor coordination and behavior remain unknown. Here, we review recent progress in understanding the roles that T-type Ca2+ channels play under pathological conditions, and discuss the potential relevance of these channels in mediating physiological motor coordination.

Variability, regularity and coupling measures distinguish PD tremor from voluntary 5 Hz tremor

A characteristic of Parkinson's disease (PD) is the development of tremor within the 4–6Hz range. One method used to better understand pathological tremor is to compare the responses to tremor-type actions generated intentionally in healthy adults. This study was designed to investigate the similarities and differences between voluntarily generated 4–6Hz tremor and PD tremor in regards to their amplitude, frequency and coupling characteristics. Tremor responses for 8 PD individuals (on- and off-medication) and 12 healthy adults were assessed under postural and resting conditions. Results showed that the voluntary and PD tremor were essentially identical with regards to the amplitude and peak frequency. However, differences between the groups were found for the variability (SD of peak frequency, proportional power) and regularity (Approximate Entropy, ApEn) of the tremor signal. Additionally, coherence analysis revealed strong inter-limb coupling during voluntary conditions while no bilateral coupling was seen for the PD persons. Overall, healthy participants were able to produce a 5Hz tremulous motion indistinguishable to that of PD patients in terms of peak frequency and amplitude. However, differences in the structure of variability and level of inter-limb coupling were found for the tremor responses of the PD and healthy adults. These differences were preserved irrespective of the medication state of the PD persons. The results illustrate the importance of assessing the pattern of signal structure/variability to discriminate between different tremor forms, especially where no differences emerge in standard measures of mean amplitude as traditionally defined.

Biomechanical loading as an alternative treatment for tremor: a review of two approaches.

Tremor is the most common movement disorder and strongly increases in incidence and prevalence with aging. Although not life threatening, upper-limb tremors hamper the independence of 65% of people suffering from them affected persons, greatly impacting their quality of life. Current treatments include pharmacotherapy and surgery (thalamotomy and deep brain stimulation). However, these options are not sufficient for approximately 25% of patients. Therefore, further research and new therapeutic options are required to effectively manage pathological tremor. This paper presents findings of two research projects in which two different wearable robots for tremor management were developed based on force loading and validated. The first consisted of a robotic exoskeleton that applied forces to tremulous limbs and consistently attenuated mild and severe tremors. The second was a neuroprosthesis based on transcutaneous neurostimulation. A total of 22 patients suffering from parkinsonian or essential tremor (ET) of different severities were recruited for experimental validation, and both systems were evaluated using standard tasks employed for neurological examination. The inclusion criterion was a postural and/or kinetic pathological upper-limb tremor resistant to medication. The results demonstrate that both approaches effectively suppressed tremor in most patients, although further research is required. The work presented here is based on clinical evidence from a small number of patients (n = 10 for robotic exoskeleton and n = 12 for the neuroprosthesis), but most had a positive response to the approaches. In summary, biomechanical loading is non-invasive and painless. It may be effective in patients who are insufficiently responsive (or have adverse reactions) to drugs or in whom surgery is contraindicated. This paper identifies and evaluates biomechanical loading approaches to tremor management and discusses their potential.

Non-invasive characterization of motor unit behaviour in pathological tremor

This paper presents the fully automatic identification of motor unit spike trains from high-density surface electromyograms (EMG) in pathological tremor. First, a mathematical derivation is provided to theoretically prove the possibility of decomposing noise-free high-density surface EMG signals into motor unit spike trains with high correlation, which are typical of tremor contractions. Further, the proposed decomposition method is tested on simulated signals with different levels of noise and on experimental signals from 14 tremor-affected patients. In the case of simulated tremor with central frequency ranging from 5 Hz to 11 Hz and signal-to-noise ratio of 20 dB, the method identified ∼8 motor units per contraction with sensitivity in spike timing identification ≥95% and false alarm and miss rates ≤5%. In experimental signals, the number of identified motor units varied substantially (range 0–21) across patients and contraction types, as expected. The behaviour of the identified motor units was consistent with previous data obtained by intramuscular EMG decomposition. These results demonstrate for the first time the possibility of a fully non-invasive investigation of motor unit behaviour in tremor-affected patients. The method provides a new means for physiological investigations of pathological tremor.

Tremor: clinical phenomenology and assessment techniques.

Tremors are among the most common movement disorders. As there can be considerable variability in the manner in which clinicians assess tremor, objective quantitative tools such as electromyography, accelerometry, and computerized, spiral analysis can be very useful in establishing a clinical diagnosis and in research settings. In this review, we discuss the various methods of quantitative tremor analysis and the classification and pathogenesis of tremor. The most common pathologic tremors and an approach to the diagnosis of tremor etiology are described. Pathologic tremors are common, and the diagnosis of underlying etiology is not always straightforward. Computerized quantitative tremor analysis is a valuable adjunct to careful clinical evaluation in distinguishing tremulous diseases from physiologic tremors, and can also help shed light on their pathogenesis.

Oscillating central motor networks in pathological tremors and voluntary movements. What makes the difference?

Parkinsonian tremor (PD), essential tremor (ET) and voluntarily mimicked tremor represent fundamentally different motor phenomena, yet, magnetoencephalographic and imaging data suggest their origin in the same motor centers of the brain. Using EEG-EMG coherence and coherent source analysis we found a different pattern of corticomuscular delays, time courses and central representations for the basic and double tremor frequencies typical for PD suggesting a wider range defective oscillatory activity. For the basic tremor frequency similar central representations in primary sensorimotor, prefrontal/premotor and diencephalic (e.g. thalamic) areas were reproduced for all three tremors. But renormalized partial directed coherence of the spatially filtered (source) signals revealed a mainly unidirectional flow of information from the diencephalon to cortex in voluntary tremor, e.g. a thalamocortical relay, as opposed to a bidirectional subcortico-cortical flow in PD and ET promoting uncontrollable, e.g. thalamocortical, loop oscillations. Our results help to understand why pathological tremors although originating from the physiological motor network are not under voluntary control and they may contribute to the solution of the puzzle why high frequency thalamic stimulation has a selective effect on pathological tremor leaving voluntary movement performance almost unaltered.

The usefulness of accelerometric registration with assessment of tremor parameters and their symmetry in differential diagnosis of parkinsonian, essential and cerebellar tremor

Background and purposeThe aim of the study was to perform an analysis of the recorded tremor using accelerometry and select those parameters that are the most useful in differentiation of tremor types. Material and methodsWe examined 45 patients with parkinsonian tremor (PT), 39 patients with essential tremor (ET) and 35 patients with cerebellar tremor (CT). The control group consisted of 52 healthy persons. The analysis included tremor intensity, frequency of spectral peaks, centre frequency, standard deviation of the centre frequency, and harmonic index. Parameters of tremor were compared between particular groups of patients with pathological tremor and with the control group. The side-to-side symmetry of these parameters was also analysed. ResultsTremor intensity was significantly higher in patients than in controls. There was a significant side-to-side asymmetry of intensity in all patient groups. Significantly lower peak frequency, centre frequency and standard deviation of centre frequency were found in patients compared to the control group. The frequency was symmetric in ET and in controls, but asymmetric in other subjects. The differences between hands regarding the standard deviation of centre frequency were significantly greater in all patient groups than in controls, who revealed no difference of this parameter between sides. Harmonic index was significantly greater and asymmetric in all groups of patients when compared to the control group. ConclusionsStandard deviation of centre frequency and harmonic index are the most valuable variables in differentiation of tremor. The assessment of symmetry of tremor parameters is useful in discrimination of various types of pathological tremor.

Diagnosis and treatment of hand tremor

Hand tremor is one of the most frequent movement disorders and embarrassing symptoms of a wide spectrum of diseases. Hand tremor can be classified by form in which the hand tremor occurs, the main distinction being whether the hand tremor occurs at rest or is produced by voluntary muscle contractions. Essential tremor is the most common pathologic tremor in humans. The clinical features of essential tremor are heterogeneous across patients. Parkinson’s disease is a common disease in the elderly with increasing prevalence over the last decade. Rest tremor is one of the cardinal motor features of Parkinson’s disease. Drug-induced hand tremor is also common and should be diagnosed accurately. Hand tremor in Wilson’s disease is very important to identify because the disease can be treatable. Here, the diagnosis and treatment of hand tremor were reviewed to provide a practical guide for managing patients with hand tremor.

SENSING OF PATHOLOGICAL TREMOR USING SURFACE ELECTROMYOGRAPHY AND ACCELEROMETER FOR REAL-TIME ATTENUATION

Tremor is the most common movement disorder and it is affecting more and more people as the world is aging. The cost involved is big considering the financial and social impact. This paper explores an assistive technology solution for upper limb pathological tremor compensation. Using both surface electromyography (SEMG) and accelerometer (ACC), a real-time pathological tremor compensation with functional electrical stimulation (FES) is proposed. One advantage of using SEMG is the electromechanical delay (SEMG data precedes the ACC data by 20–100 ms). Hence by detecting the tremor in advance, there is enough time window to do the necessary computation and to actuate the antagonist muscle by FES. This is also possible because the time taken for FES to actuate the muscle is significantly less than that of the neural signal, as detected by SEMG. For estimation of tremor parameters and separation between voluntary motion and tremor, an algorithm based on extended Kalman filter (EKF) is proposed. Experimental result from one essential tremor patient has shown 57% reduction in tremor power as measured by the ACC.