EMG remains fractionated in Parkinson's disease, despite practice-related improvements in performance

Impaired performance of rapid grip in people with Parkinson's disease and motor segmentation

Bradykinesia, or slow movement, is a defining symptom of Parkinson's disease (PD), but the underlying neuromechanical deficits that lead to this slowness remain unclear. People with PD often have impaired rates of motor output accompanied by disruptions in neuromuscular excitation, causing abnormal, segmented, force-time curves. Previous investigations using single-joint models indicate that agonist electromyogram (EMG) silent periods cause motor segmentation. It is unknown whether motor segmentation is evident in more anatomically complex and ecologically important tasks, such as handgrip tasks. Aim 1 was to determine how handgrip rates of force change compare between people with PD and healthy young and older adults. Aim 2 was to determine whether motor segmentation is present in handgrip force and EMG measures in people with PD. Subjects performed rapid isometric handgrip pulses to 20-60% of their maximal voluntary contraction force while EMG was collected from the grip flexors and extensors. Dependent variables included the time to 90% peak force, the peak rate of force development, the duration above 90% of peak force, the number of segments in the force-time curve, the number of EMG bursts, time to relaxation from 90% of peak force, and the peak rate of force relaxation. People with PD had longer durations and lower rates of force change than young and older adults. Six of 22 people with PD had motor segmentation. People with PD had more EMG bursts compared to healthy adults and the number of EMG bursts covaried with the number of segments. Thus, control of rapid movement in Parkinson's disease can be studied using isometric handgrip. People with PD have impaired rate control compared to healthy adults and motor segmentation can be studied in handgrip.

Changes in elbow flexion EMG morphology during adjustment of deep brain stimulator in advanced Parkinson’s disease

Objective

Deep brain stimulation (DBS) is an effective treatment for motor symptoms of advanced Parkinson’s disease (PD). Currently, DBS programming outcome is based on a clinical assessment. In an optimal situation, an objectively measurable feature would assist the operator to select the appropriate settings for DBS. Surface electromyographic (EMG) measurements have been used to characterise the motor symptoms of PD with good results; with proper methodology, these measurements could be used as an aid to program DBS.

Methods

Muscle activation measurements were performed for 13 patients who had advanced PD and were treated with DBS. The DBS pulse voltage, frequency, and width were changed during the measurements. The measured EMG signals were analysed with parameters that characterise the EMG signal morphology, and the results were compared to the clinical outcome of the adjustment.

Results

The EMG signal correlation dimension, recurrence rate, and kurtosis changed significantly when the DBS settings were changed. DBS adjustment affected the signal recurrence rate the most. Relative to the optimal settings, increased recurrence rates (median ± IQR) 1.1 ± 0.5 (−0.3 V), 1.3 ± 1.1 (+0.3 V), 1.7 ± 0.4 (−30 Hz), 1.7 ± 0.8 (+30 Hz), 2.0 ± 1.7 (+30 μs), and 1.5 ± 1.1 (DBS off) were observed. With optimal stimulation settings, the patients’ Unified Parkinson’s Disease Rating Scale motor part (UPDRS-III) score decreased by 35% on average compared to turning the device off. However, the changes in UPRDS-III arm tremor and rigidity scores did not differ significantly in any settings compared to the optimal stimulation settings.

Conclusion

Adjustment of DBS treatment alters the muscle activation patterns in PD patients. The changes in the muscle activation patterns can be observed with EMG, and the parameters calculated from the signals differ between optimal and non-optimal settings of DBS. This provides a possibility for using the EMG-based measurement to aid the clinicians to adjust the DBS.

A Statistical Method for Exploratory Data Analysis Based on 2D and 3D Area under Curve Diagrams: Parkinson's Disease Investigation

A statistical method for exploratory data analysis based on 2D and 3D area under curve (AUC) diagrams was developed. The method was designed to analyze electroencephalogram (EEG), electromyogram (EMG), and tremorogram data collected from patients with Parkinson's disease. The idea of the method of wave train electrical activity analysis is that we consider the biomedical signal as a combination of the wave trains. The wave train is the increase in the power spectral density of the signal localized in time, frequency, and space. We detect the wave trains as the local maxima in the wavelet spectrograms. We do not consider wave trains as a special kind of signal. The wave train analysis method is different from standard signal analysis methods such as Fourier analysis and wavelet analysis in the following way. Existing methods for analyzing EEG, EMG, and tremor signals, such as wavelet analysis, focus on local time-frequency changes in the signal and therefore do not reveal the generalized properties of the signal. Other methods such as standard Fourier analysis ignore the local time-frequency changes in the characteristics of the signal and, consequently, lose a large amount of information that existed in the signal. The method of wave train electrical activity analysis resolves the contradiction between these two approaches because it addresses the generalized characteristics of the biomedical signal based on local time-frequency changes in the signal. We investigate the following wave train parameters: wave train central frequency, wave train maximal power spectral density, wave train duration in periods, and wave train bandwidth. We have developed special graphical diagrams, named AUC diagrams, to determine what wave trains are characteristic of neurodegenerative diseases. In this paper, we consider the following types of AUC diagrams: 2D and 3D diagrams. The technique of working with AUC diagrams is illustrated by examples of analysis of EMG in patients with Parkinson's disease and healthy volunteers. It is demonstrated that new regularities useful for the high-accuracy diagnosis of Parkinson's disease can be revealed using the method of analyzing the wave train electrical activity and AUC diagrams.

Single-Joint Movements in Parkinson's Disease: A Pulse-Width and Pulse-Height Theory Review

The process by which the brain controls single-joint movements (SJM) is still not well understood. Some studies have defined rules describing the duration and magnitude of the agonist and antagonist muscles. Therefore, the purpose of this study was to analyze scientific publications about the electromyographic characteristics of SJM performed by patients with Parkinson's disease. A bibliographical review of the years 1989-2015 was performed using keywords such as electromyography, upper limb, and Parkinson's disease. After applying the inclusion criteria, 8 articles were included for analysis. The literature indicates that despite the lack of studies, it is possible to assume that considering the SJM, those with Parkinson's disease only control the magnitude of electromyography activation, being consistent only with the pulse-height theory control.

Motor Learning and Parkinson Disease: Refinement of Movement Velocity and Endpoint Excursion in a Limits of Stability Balance Task

Objective. To investigate the effects of practice on performance and retention of a balance task in persons with Parkinson disease (PD).

Methods. Ten persons with PD and 10 age and gender-matched healthy control subjects were tested on an anticipatory, static base of support, limits of stability (LOS) balance task on a force plate. The motor learning paradigm utilized for all subjects included an acquisition phase and retention tests at 24 h and 1 week after acquisition. A force plate was used for testing and to collect outcome measures including movement velocity (MVL), endpoint excursion (EPE), and directional control. Data were analyzed for differences between groups and change over time.

Results.Persons with PD demonstrated performance deficits relative to controls for MVL at all testing periods ( P < 0.05), and initially for EPE ( P < 0.05), but were able to maintain significant improvements through retention testing relative to baseline ( P < 0.05).

Conclusions. Persons with PD demonstrated unimpaired capacity for motor learning in a LOS balance task for MVL and EPE, although performance deficits remained for MVL. The results concur with previous motor learning research of upper extremity tasks by suggesting that individuals with mild to moderate PD exhibit a preserved ability to benefit from practice as a means of improving balance task performance.

A common optimization principle for motor execution in healthy subjects and parkinsonian patients

Recent research on Parkinson's disease (PD) has emphasized that parkinsonian movement, although bradykinetic, shares many attributes with healthy behavior. This observation led to the suggestion that bradykinesia in PD could be due to a reduction in motor motivation. This hypothesis can be tested in the framework of optimal control theory, which accounts for many characteristics of healthy human movement while providing a link between the motor behavior and a cost/benefit trade-off. This approach offers the opportunity to interpret movement deficits of PD patients in the light of a computational theory of normal motor control. We studied 14 PD patients with bilateral subthalamic nucleus (STN) stimulation and 16 age-matched healthy controls, and tested whether reaching movements were governed by similar rules in these two groups. A single optimal control model accounted for the reaching movements of healthy subjects and PD patients, whatever the condition of STN stimulation (on or off). The choice of movement speed was explained in all subjects by the existence of a preset dynamic range for the motor signals. This range was idiosyncratic and applied to all movements regardless of their amplitude. In PD patients this dynamic range was abnormally narrow and correlated with bradykinesia. STN stimulation reduced bradykinesia and widened this range in all patients, but did not restore it to a normal value. These results, consistent with the motor motivation hypothesis, suggest that constrained optimization of motor effort is the main determinant of movement planning (choice of speed) and movement production, in both healthy and PD subjects.

Analysis of dynamic EMG and acceleration measurements in Parkinson's disease

In this paper, we bring out modern methods that are potential in analysing differences in the dynamic surface electromyographic (EMG) and acceleration measurements between patients with Parkinson's disease (PD) and healthy persons. These methods are the correlation dimension of EMG, the recurrence rate of EMG, the power of acceleration and the sample entropy of acceleration. In this study, these methods were used to extract features from surface EMG and acceleration recordings measured during elbow flexion and extension movements. The extracted features were used to form high-dimensional feature vectors and the dimensionality of these vectors was then reduced by using the principal component approach. Finally, the feature vectors were discriminated between subjects by using the principal components. The discrimination power of the presented approach was tested with EMG and acceleration data measured from 46 patients with PD (on-medication) and 59 healthy controls. Discrimination results showed that the present method was able to discriminate dynamic EMG and acceleration recordings between patients with PD and healthy controls. Therefore, dynamic surface EMG and acceleration measurements may have potential in the objective and quantitative assessment and diagnosis of PD.

Surface EMG and acceleration signals in Parkinson's disease: feature extraction and cluster analysis

We present an advanced method for feature extraction and cluster analysis of surface electromyograms (EMG) and acceleration signals in Parkinson's disease (PD). In the method, 12 different EMG and acceleration signal features are extracted and used to form high-dimensional feature vectors. The dimensionality of these vectors is then reduced by using the principal component approach. Finally, the cluster analysis of feature vectors is performed in a low-dimensional eigenspace. The method was tested with EMG and acceleration data of 42 patients with PD and 59 healthy controls. The obtained discrimination between patients and controls was promising. According to clustering results, one cluster contained 90% of the healthy controls and two other clusters 76% of the patients. Seven patients with severe motor dysfunctions were distinguished in one of the patient clusters. In the future, the clinical value of the method should be further evaluated.

Control of aperture closure during reach-to-grasp movements in Parkinson's disease

This study examined whether the pattern of coordination between arm-reaching toward an object (hand transport) and the initiation of aperture closure for grasping is different between PD patients and healthy individuals, and whether that pattern is affected by the necessity to quickly adjust the reach-to-grasp movement in response to an unexpected shift of target location. Subjects reached for and grasped a vertical dowel, the location of which was indicated by illuminating one of the three dowels placed on a horizontal plane. In control conditions, target location was fixed during the trial. In perturbation conditions, target location was shifted instantaneously by switching the illumination to a different dowel during the reach. The hand distance from the target at which the subject initiated aperture closure (aperture closure distance) was similar for both the control and perturbation conditions within each group of subjects. However, that distance was significantly closer to the target in the PD group than in the control group. The timing of aperture closure initiation varied considerably across the trials in both groups of subjects. In contrast, aperture closure distance was relatively invariant, suggesting that aperture closure initiation was determined by spatial parameters of arm kinematics rather than temporal parameters. The linear regression analysis of aperture closure distance showed that the distance was highly predictable based on the following three parameters: the amplitude of maximum grip aperture, hand velocity, and hand acceleration. This result implies that a control law, the arguments of which include the above parameters, governs the initiation of aperture closure. Further analysis revealed that the control law was very similar between the subject groups under each condition as well as between the control and perturbation conditions for each group. Consequently, the shorter aperture closure distance observed in PD patients apparently is a result of the hypometria of their grip aperture and bradykinesia of hand transport movement, rather than a consequence of a deficit in transport-grasp coordination. It is also concluded that the perturbation of target location does not disrupt the transport-grasp coordination in either healthy individuals or PD patients.

Learning a high-precision locomotor task in patients with Parkinson's disease

We evaluated the acquisition and performance of a high-precision locomotor task in patients with Parkinson's disease (PD) and healthy subjects. All subjects walked on a treadmill and had to step repetitively as low as possible over an obstacle without touching it. During blocks 1 and 2, the subjects had full vision and received additional acoustic warning and feedback signals. During block 3, vision became restricted. Changes in foot clearance and the number of obstacle hits were evaluated. Initially, PD patients performed poorer and improved foot clearance slower. After task repetition, the groups performed similarly. Restricting vision deteriorated performance in both groups. The similar performance of PD patients after task repetition might indicate that adequate training could improve adaptive locomotor behavior in PD patients.