Analysis of amplitude and frequency variations of essential and Parkinsonian tremors

An OpenSim-Based Closed-Loop Biomechanical Wrist Model for Subject-Specific Pathological Tremor Simulation

OBJECTIVE

A pathological tremor (PT) is an involuntary rhythmic movement of varying frequency and amplitude that affects voluntary motion, thus compromising individuals' independence. A comprehensive model incorporating PT's physiological and biomechanical aspects can enhance our understanding of the disorder and provide valuable insights for therapeutic approaches. This study aims to build a biomechanical model of pathological tremors using OpenSim's realistic musculoskeletal representation of the human wrist with two degrees of freedom.

METHODS

We implemented a Matlab/OpenSim interface for a forward dynamics simulation, which allows for the modeling, simulation, and design of a physiological H∞ closed-loop control. This system replicates pathological tremors similar to those observed in patients when their arm is extended forward, the wrist is pronated, and the hand is subject to gravity forces. The model was individually tuned to five subjects (four Parkinson's disease patients and one diagnosed with essential tremor), each exhibiting distinct tremor characteristics measured by an inertial sensor and surface EMG electrodes. Simulation agreement with the experiments for EMGs, central frequency, joint angles, and angular velocities were evaluated by Jensen-Shannon divergence, histogram centroid error, and histogram intersection.

RESULTS

The model emulated individual tremor statistical characteristics, including muscle activations, frequency, variability, and wrist kinematics, with greater accuracy for the four Parkinson's patients than the essential tremor.

CONCLUSION

The proposed model replicated the main statistical features of subject-specific wrist tremor kinematics.

SIGNIFICANCE

Our methodology may facilitate the design of patient-specific rehabilitation devices for tremor suppression, such as neural prostheses and electromechanical orthoses.

Discontinuous phase transition switching induced by a power-law function between dynamical parameters in coupled oscillators

In biological or physical systems, the intrinsic properties of oscillators are heterogeneous and correlated. These two characteristics have been empirically validated and have garnered attention in theoretical studies. In this paper, we propose a power-law function existed between the dynamical parameters of the coupled oscillators, which can control discontinuous phase transition switching. Unlike the special designs for the coupling terms, this generalized function within the dynamical term reveals another path for generating the first-order phase transitions. The power-law relationship between dynamic characteristics is reasonable, as observed in empirical studies, such as long-term tremor activity during volcanic eruptions and ion channel characteristics of the Xenopus expression system. Our work expands the conditions that used to be strict for the occurrence of the first-order phase transitions and deepens our understanding of the impact of correlation between intrinsic parameters on phase transitions. We explain the reason why the continuous phase transition switches to the discontinuous phase transition when the control parameter is at a critical value.

Therapeutic maps for a sensor-based evaluation of deep brain stimulation programming

Programming in deep brain stimulation (DBS) is a labour-intensive process for treating advanced motor symptoms. Specifically for patients with medication-refractory tremor in multiple sclerosis (MS). Wearable sensors are able to detect some manifestations of pathological signs, such as intention tremor in MS. However, methods are needed to visualise the response of tremor to DBS parameter changes in a clinical setting while patients perform the motor task finger-to-nose. To this end, we attended DBS programming sessions of a MS patient and intention tremor was effectively quantified by acceleration amplitude and frequency. A new method is introduced which results in the generation of therapeutic maps for a systematic review of the programming procedure in DBS. The maps visualise the combination of tremor acceleration power, clinical rating scores, total electrical energy delivered to the brain and possible side effects. Therapeutic maps have not yet been employed and could lead to a certain degree of standardisation for more objective decisions about DBS settings. The maps provide a base for future research on visualisation tools to assist physicians who frequently encounter patients for DBS therapy.

Artifact Mimicking Ictal Epileptiform Activity in EEG

Although the EEG is designed to record cerebral activity, it also frequently records activity from extracerebral sources, leading to artifact. Differentiating rhythmical artifact from true electrographic ictal activity remains a substantial challenge to even experienced electroencephalographers because the sources of artifact able to mimic ictal activity on EEG have continued to increase with the advent of technology. Knowledge of the characteristics of the polarity and physiologic electrical fields of the brain, as opposed to those generated by the eyes, heart, and muscles, allows the electroencephalographer to intuitively recognize noncerebrally generated waveforms. In this review, we provide practical guidelines for the EEG interpreter to correctly identify physiologic and nonphysiologic artifacts capable of mimicking electrographic seizures. In addition, we further elucidate the common pitfalls in artifact interpretation and the costly impact of epilepsy misdiagnosis due to artifact.

A Power Spectral Density-Based Method to Detect Tremor and Tremor Intermittency in Movement Disorders

There is no objective gold standard to detect tremors. This concerns not only the choice of the algorithm and sensors, but methods are often designed to detect tremors in one specific group of patients during the performance of a specific task. Therefore, the aim of this study is twofold. First, an objective quantitative method to detect tremor windows (TWs) in accelerometer and electromyography recordings is introduced. Second, the tremor stability index (TSI) is determined to indicate the advantage of detecting TWs prior to analysis. Ten Parkinson's disease (PD) patients, ten essential tremor (ET) patients, and ten healthy controls (HC) performed a resting, postural and movement task. Data was split into 3-s windows, and the power spectral density was calculated for each window. The relative power around the peak frequency with respect to the power in the tremor band was used to classify the windows as either tremor or non-tremor. The method yielded a specificity of 96.45%, sensitivity of 84.84%, and accuracy of 90.80% of tremor detection. During tremors, significant differences were found between groups in all three parameters. The results suggest that the introduced method could be used to determine under which conditions and to which extent undiagnosed patients exhibit tremors.

Controlling a motorized orthosis to follow elbow volitional movement: tests with individuals with pathological tremor

BACKGROUND

There is a need for alternative treatment options for tremor patients who do not respond well to medications or surgery, either due to side effects or poor efficacy, or that are excluded from surgery. The study aims to evaluate feasibility of a voluntary-driven, speed-controlled tremor rejection approach with individuals with pathological tremor. The suppression approach was investigated using a robotic orthosis for suppression of elbow tremor. Importantly, the study emphasizes the performance in relation to the voluntary motion.

METHODS

Nine participants with either Essential Tremor (ET) or Parkinson's disease (PD) were recruited and tested off medication. The participants performed computerized pursuit tracking tasks following a sinusoid and a random target, both with and without the suppressive orthosis. The impact of the Tremor Suppression Orthosis (TSO) at the tremor and voluntary frequencies was determined by the relative power change calculated from the Power Spectral Density (PSD). Voluntary motion was, in addition, assessed by position and velocity tracking errors.

RESULTS

The suppressive orthosis resulted in a 94.4% mean power reduction of the tremor (p < 0.001) - a substantial improvement over reports in the literature. As for the impact to the voluntary motion, paired difference tests revealed no statistical effect of the TSO on the relative power change (p = 0.346) and velocity tracking error (p = 0.283). A marginal effect was observed for the position tracking error (p = 0.05). The interaction torque with the robotic orthosis was small (0.62 Nm) when compared to the maximum voluntary torque that can be exerted by adult individuals at the elbow joint.

CONCLUSIONS

Two key contributions of this work are first, a recently proposed approach is evaluated with individuals with tremor demonstrating high levels of tremor suppression; second, the impact of the approach to the voluntary motion is analyzed comprehensively, showing limited inhibition. This study also seeks to address a gap in studies with individuals with tremor where the impact of engineering solutions on voluntary motion is unreported. This study demonstrates feasibility of the wearable technology as an effective treatment that removes tremor with limited impediment to intentional motion. The goal for such wearable technology is to help individuals with pathological tremor regain independence in activities affected by the tremor condition. Further investigations are needed to validate the technology.

Neural computational modeling reveals a major role of corticospinal gating of central oscillations in the generation of essential tremor

Essential tremor, also referred to as familial tremor, is an autosomal dominant genetic disease and the most common movement disorder. It typically involves a postural and motor tremor of the hands, head or other part of the body. Essential tremor is driven by a central oscillation signal in the brain. However, the corticospinal mechanisms involved in the generation of essential tremor are unclear. Therefore, in this study, we used a neural computational model that includes both monosynaptic and multisynaptic corticospinal pathways interacting with a propriospinal neuronal network. A virtual arm model is driven by the central oscillation signal to simulate tremor activity behavior. Cortical descending commands are classified as alpha or gamma through monosynaptic or multisynaptic corticospinal pathways, which converge respectively on alpha or gamma motoneurons in the spinal cord. Several scenarios are evaluated based on the central oscillation signal passing down to the spinal motoneurons via each descending pathway. The simulated behaviors are compared with clinical essential tremor characteristics to identify the corticospinal pathways responsible for transmitting the central oscillation signal. A propriospinal neuron with strong cortical inhibition performs a gating function in the generation of essential tremor. Our results indicate that the propriospinal neuronal network is essential for relaying the central oscillation signal and the production of essential tremor.

The Cerebral Network of Parkinson's Tremor: An Effective Connectivity fMRI Study

Parkinson's resting tremor has been linked to pathophysiological changes both in the basal ganglia and in a cerebello-thalamo-cortical motor loop, but the role of those circuits in initiating and maintaining tremor remains unclear. Here, we test whether and how the cerebello-thalamo-cortical loop is driven into a tremor-related state by virtue of its connectivity with the basal ganglia. An internal replication design on two independent cohorts of tremor-dominant Parkinson patients sampled brain activity and tremor with concurrent EMG-fMRI. Using dynamic causal modeling, we tested: (1) whether activity at the onset of tremor episodes drives tremulous network activity through the basal ganglia or the cerebello-thalamo-cortical loop and (2) whether the basal ganglia influence the cerebello-thalamo-cortical loop through connectivity with the cerebellum or motor cortex. We compared five physiologically plausible circuits, model families in which transient activity at the onset of tremor episodes (assessed using EMG) drove network activity through the internal globus pallidus (GPi), external globus pallidus, motor cortex, thalamus, or cerebellum. In each family, we compared two models in which the basal ganglia and cerebello-thalamo-cortical loop were connected through the cerebellum or motor cortex. In both cohorts, cerebral activity associated with changes in tremor amplitude (using peripheral EMG measures as a proxy for tremor-related neuronal activity) drove network activity through the GPi, which effectively influenced the cerebello-thalamo-cortical loop through the motor cortex. We conclude that cerebral activity related to Parkinson's tremor first arises in the GPi and is then propagated to the cerebello-thalamo-cortical circuit.

SIGNIFICANCE STATEMENT

Parkinson's resting tremor has been linked to pathophysiological changes both in the basal ganglia and in a cerebello-thalamo-cortical motor loop, but the role of those circuits in initiating and maintaining tremor remains unclear. Using dynamic causal modeling of concurrently collected EMG-fMRI data in two cohorts of Parkinson's patients, we showed that cerebral activity associated with changes in tremor amplitude drives network activity through the basal ganglia. Furthermore, the basal ganglia effectively influenced the cerebello-thalamo-cortical circuit through the motor cortex (but not the cerebellum). Out findings suggest that Parkinson's tremor-related activity first arises in the basal ganglia and is then propagated to the cerebello-thalamo-cortical circuit.

Cognitive Stress Reduces the Effect of Levodopa on Parkinson's Resting Tremor

Aims

Resting tremor in Parkinson′s disease (PD) increases markedly during cognitive stress. Dopamine depletion in the basal ganglia is involved in the pathophysiology of resting tremor, but it is unclear whether this contribution is altered under cognitive stress. We test the hypothesis that cognitive stress modulates the levodopa effect on resting tremor.

Methods

Tremulous PD patients (n = 69) were measured in two treatment conditions (OFF vs. ON levodopa) and in two behavioral contexts (rest vs. cognitive co‐activation). Using accelerometry, we tested the effect of both interventions on tremor intensity and tremor variability.

Results

Levodopa significantly reduced tremor intensity (across behavioral contexts), while cognitive co‐activation increased it (across treatment conditions). Crucially, the levodopa effect was significantly smaller during cognitive co‐activation than during rest. Resting tremor variability increased after levodopa and decreased during cognitive co‐activation.

Conclusion

Cognitive stress reduces the levodopa effect on Parkinson's tremor. This effect may be explained by a stress‐related depletion of dopamine in the basal ganglia motor circuit, by stress‐related involvement of nondopaminergic mechanisms in tremor (e.g., noradrenaline), or both. Targeting these mechanisms may open new windows for treatment. Clinical tremor assessments under evoked cognitive stress (e.g., counting tasks) may avoid overestimation of treatment effects in real life.

Development of method for quantifying essential tremor using a small optical device

BACKGROUND

Clinical assessment scales are the most common means used by physicians to assess tremor severity. Some scientific tools that may be able to replace these scales to objectively assess the severity, such as accelerometers, digital tablets, electromyography (EMG) measurement devices, and motion capture cameras, are currently available. However, most of the operational modes of these tools are relatively complex or are only able to capture part of the clinical information; furthermore, using these tools is sometimes time consuming. Currently, there is no tool available for automatically quantifying tremor severity in clinical environments.

NEW METHOD

We aimed to develop a rapid, objective, and quantitative system for measuring the severity of finger tremor using a small portable optical device (Leap Motion).

RESULTS

A single test took 15s to conduct, and three algorithms were proposed to quantify the severity of finger tremor. The system was tested with four patients diagnosed with essential tremor.

COMPARISON WITH EXISTING METHOD

The proposed algorithms were able to quantify different characteristics of tremor in clinical environments, and could be used as references for future clinical assessments.

CONCLUSIONS

A portable, easy-to-use, small-sized, and noncontact device (Leap Motion) was used to clinically detect and record finger movement, and three algorithms were proposed to describe tremor amplitudes.

Distinguishing the central drive to tremor in Parkinson's disease and essential tremor

Parkinson's disease (PD) and essential tremor (ET) are the two most common movement disorders. Both have been associated with similar patterns of network activation leading to the suggestion that they may result from similar network dysfunction, specifically involving the cerebellum. Here, we demonstrate that parkinsonian tremors and ETs result from distinct patterns of interactions between neural oscillators. These patterns are reflected in the tremors' derived frequency tolerance, a novel measure readily attainable from bedside accelerometry. Frequency tolerance characterizes the temporal evolution of tremor by quantifying the range of frequencies over which the tremor may be considered stable. We found that patients with PD (N = 24) and ET (N = 21) were separable based on their frequency tolerance, with PD associated with a broad range of stable frequencies whereas ET displayed characteristics consistent with a more finely tuned oscillatory drive. Furthermore, tremor was selectively entrained by transcranial alternating current stimulation applied over cerebellum. Narrow frequency tolerances predicted stronger entrainment of tremor by stimulation, providing good evidence that the cerebellum plays an important role in pacing those tremors. The different patterns of frequency tolerance could be captured with a simple model based on a broadly coupled set of neural oscillators for PD, but a more finely tuned set of oscillators in ET. Together, these results reveal a potential organizational principle of the human motor system, whose disruption in PD and ET dictates how patients respond to empirical, and potentially therapeutic, interventions that interact with their underlying pathophysiology.

The nature of tremor circuits in parkinsonian and essential tremor

See Arkadir et al. (doi:10.1093/brain/awu285) for a scientific commentary on this article. The mechanisms underlying tremor generation remain unclear. Cagnan et al. use deep brain stimulation of the thalamus or subthalamic nucleus at/near a patient's own tremor frequency to investigate the networks responsible for parkinsonian and essential tremor. The results reveal differences in the circuitry underlying these two tremor types.

Tremor is a cardinal feature of Parkinson’s disease and essential tremor, the two most common movement disorders. Yet, the mechanisms underlying tremor generation remain largely unknown. We hypothesized that driving deep brain stimulation electrodes at a frequency closely matching the patient’s own tremor frequency should interact with neural activity responsible for tremor, and that the effect of stimulation on tremor should reveal the role of different deep brain stimulation targets in tremor generation. Moreover, tremor responses to stimulation might reveal pathophysiological differences between parkinsonian and essential tremor circuits. Accordingly, we stimulated 15 patients with Parkinson’s disease with either thalamic or subthalamic electrodes (13 male and two female patients, age: 50–77 years) and 10 patients with essential tremor with thalamic electrodes (nine male and one female patients, age: 34–74 years). Stimulation at near-to tremor frequency entrained tremor in all three patient groups (ventrolateral thalamic stimulation in Parkinson’s disease, P = 0.0078, subthalamic stimulation in Parkinson’s disease, P = 0.0312; ventrolateral thalamic stimulation in essential tremor, P = 0.0137; two-tailed paired Wilcoxon signed-rank tests). However, only ventrolateral thalamic stimulation in essential tremor modulated postural tremor amplitude according to the timing of stimulation pulses with respect to the tremor cycle (e.g. P = 0.0002 for tremor amplification, two-tailed Wilcoxon rank sum test). Parkinsonian rest and essential postural tremor severity (i.e. tremor amplitude) differed in their relative tolerance to spontaneous changes in tremor frequency when stimulation was not applied. Specifically, the amplitude of parkinsonian rest tremor remained unchanged despite spontaneous changes in tremor frequency, whereas that of essential postural tremor reduced when tremor frequency departed from median values. Based on these results we conclude that parkinsonian rest tremor is driven by a neural network, which includes the subthalamic nucleus and ventrolateral thalamus and has broad frequency-amplitude tolerance. We propose that it is this tolerance to changes in tremor frequency that dictates that parkinsonian rest tremor may be significantly entrained by low frequency stimulation without stimulation timing-dependent amplitude modulation. In contrast, the circuit influenced by low frequency thalamic stimulation in essential tremor has a narrower frequency-amplitude tolerance so that tremor entrainment through extrinsic driving is necessarily accompanied by amplitude modulation. Such differences in parkinsonian rest and essential tremor will be important in selecting future strategies for closed loop deep brain stimulation for tremor control.

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.

Cerebral causes and consequences of parkinsonian resting tremor: a tale of two circuits?

Tremor in Parkinson's disease has several mysterious features. Clinically, tremor is seen in only three out of four patients with Parkinson's disease, and tremor-dominant patients generally follow a more benign disease course than non-tremor patients. Pathophysiologically, tremor is linked to altered activity in not one, but two distinct circuits: the basal ganglia, which are primarily affected by dopamine depletion in Parkinson's disease, and the cerebello-thalamo-cortical circuit, which is also involved in many other tremors. The purpose of this review is to integrate these clinical and pathophysiological features of tremor in Parkinson's disease. We first describe clinical and pathological differences between tremor-dominant and non-tremor Parkinson's disease subtypes, and then summarize recent studies on the pathophysiology of tremor. We also discuss a newly proposed ‘dimmer-switch model’ that explains tremor as resulting from the combined actions of two circuits: the basal ganglia that trigger tremor episodes and the cerebello-thalamo-cortical circuit that produces the tremor. Finally, we address several important open questions: why resting tremor stops during voluntary movements, why it has a variable response to dopaminergic treatment, why it indicates a benign Parkinson's disease subtype and why its expression decreases with disease progression.

A telemedicine instrument for remote evaluation of tremor: design and initial applications in fatigue and patients with Parkinson's disease

INTRODUCTION

A novel system that combines a compact mobile instrument and Internet communications is presented in this paper for remote evaluation of tremors. The system presents a high potential application in Parkinson's disease and connects to the Internet through a TCP/IP protocol. Tremor transduction is carried out by accelerometers, and the data processing, presentation and storage were obtained by a virtual instrument. The system supplies the peak frequency (fp), the amplitude (Afp) and power in this frequency (Pfp), the total power (Ptot), and the power in low (1-4 Hz) and high (4-7 Hz) frequencies (Plf and Phf, respectively).

METHODS

The ability of the proposed system to detect abnormal tremors was initially demonstrated by a fatigue study in normal subjects. In close agreement with physiological fundamentals, the presence of fatigue increased fp, Afp, Pfp and Pt (p < 0.05), while the removal of fatigue reduced all the mentioned parameters (p < 0.05). The system was also evaluated in a preliminary in vivo test in parkinsonian patients. Afp, Pfp, Ptot, Plf and Phf were the most accurate parameters in the detection of the adverse effects of this disease (Se = 100%, Sp = 100%), followed by fp (Se = 100%, Sp = 80%). Tests for Internet transmission that realistically simulated clinical conditions revealed adequate acquisition and analysis of tremor signals and also revealed that the user could adequately receive medical recommendations.

CONCLUSIONS

The proposed system can be used in a wide spectrum of telemedicine scenarios, enabling the home evaluation of tremor occurrence under specific medical treatments and contributing to reduce the costs of the assistance offered to these patients.

Distinguishing chaos from noise by scale-dependent Lyapunov exponent

Time series from complex systems with interacting nonlinear and stochastic subsystems and hierarchical regulations are often multiscaled. In devising measures characterizing such complex time series, it is most desirable to incorporate explicitly the concept of scale in the measures. While excellent scale-dependent measures such as epsilon entropy and the finite size Lyapunov exponent (FSLE) have been proposed, simple algorithms have not been developed to reliably compute them from short noisy time series. To promote widespread application of these concepts, we propose an efficient algorithm to compute a variant of the FSLE, the scale-dependent Lyapunov exponent (SDLE). We show that with our algorithm, the SDLE can be accurately computed from short noisy time series and readily classify various types of motions, including truly low-dimensional chaos, noisy chaos, noise-induced chaos, random 1/f alpha and alpha-stable Levy processes, stochastic oscillations, and complex motions with chaotic behavior on small scales but diffusive behavior on large scales. To our knowledge, no other measures are able to accurately characterize all these different types of motions. Based on the distinctive behaviors of the SDLE for different types of motions, we propose a scheme to distinguish chaos from noise.

Point process model of 1/f noise vs a sum of Lorentzians

We present a simple point process model of 1/f(beta) noise, covering different values of the exponent beta . The signal of the model consists of pulses or events. The interpulse, interevent, interarrival, recurrence, or waiting times of the signal are described by the general Langevin equation with the multiplicative noise and stochastically diffuse in some interval resulting in a power-law distribution. Our model is free from the requirement of a wide distribution of relaxation times and from the power-law forms of the pulses. It contains only one relaxation rate and yields 1/f(beta) spectra in a wide range of frequencies. We obtain explicit expressions for the power spectra and present numerical illustrations of the model. Further we analyze the relation of the point process model of 1/f noise with the Bernamont-Surdin-McWhorter model, representing the signals as a sum of the uncorrelated components. We show that the point process model is complementary to the model based on the sum of signals with a wide-range distribution of the relaxation times. In contrast to the Gaussian distribution of the signal intensity of the sum of the uncorrelated components, the point process exhibits asymptotically a power-law distribution of the signal intensity. The developed multiplicative point process model of 1/f(beta)noise may be used for modeling and analysis of stochastic processes in different systems with the power-law distribution of the intensity of pulsing signals.