The dynamics of resting and postural tremor in Parkinson's disease

Continuous and Unconstrained Tremor Monitoring in Parkinson's Disease Using Supervised Machine Learning and Wearable Sensors

Background

Accurately assessing the severity and frequency of fluctuating motor symptoms is important at all stages of Parkinson's disease management. Contrarily to time-consuming clinical testing or patient self-reporting with uncertain reliability, recordings with wearable sensors show promise as a tool for continuously and objectively assessing PD symptoms. While wearables-based clinical assessments during standardised and scripted tasks have been successfully implemented, assessments during unconstrained activity remain a challenge.

Methods

We developed and implemented a supervised machine learning algorithm, trained and tested on tremor scores. We evaluated the algorithm on a 67-hour database comprising sensor data and clinical tremor scores for 24 Parkinson patients at four extremities for periods of about 3 hours. A random 25% subset of the labelled samples was used as test data, the remainder as training data. Based on features extracted from the sensor data, a Support Vector Machine was trained to predict tremor severity. Due to the inherent imbalance in tremor scores, we applied dataset rebalancing techniques.

Results

Our classifier demonstrated robust performance in detecting tremor events with a sensitivity of 0.90 on the test-portion of the resampled dataset. The overall classification accuracy was high at 0.88.

Conclusion

We implemented an accurate classifier for tremor monitoring in free-living environments that can be trained even with modestly sized and imbalanced datasets. This advancement offers significant clinical value in continuously monitoring Parkinson's disease symptoms beyond the hospital setting, paving the way for personalized management of PD, timely therapeutic adjustments, and improved patient quality of life.

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

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

The Relevance of Intraoperative Clinical and Accelerometric Measurements for Thalamotomy Outcome

Thalamotomy alleviates medication-refractory tremors in patients with movement disorders such as Parkinson's Disease (PD), Essential tremor (ET), and Holmes tremor (HT). However, limited data are available on tremor intensity during different thalamotomy stages. Also, the predictive value of the intraoperative tremor status for treatment outcomes remains unclear. Therefore, we aimed to quantify tremor status during thalamotomy and postoperatively. Data were gathered between January 2020 and June 2023 during consecutive unilateral thalamotomy procedures in patients with PD (n = 13), ET (n = 8), and HT (n = 3). MDS-UPDRS scores and tri-axial accelerometry data were obtained during rest, postural, and intention tremor tests. Measurements were performed intraoperatively (1) before lesioning-probe insertion, (2) directly after lesioning-probe insertion, (3) during coagulation, (4) directly after coagulation, and (5) 4-6 months post-surgery. Accelerometric data were recorded continuously during the coagulation process. Outcome measures included MDS-UPDRS tremor scores and accelerometric parameters (peak frequency, tremor amplitude, and area under the curve of power (AUCP)). Tremor intensity was assessed for the insertion effect (1-2), during coagulation (3), post-coagulation effect (1-4), and postoperative effect (1-5). Following insertion and coagulation, tremor intensity improved significantly compared to baseline (p < 0.001). The insertion effect clearly correlated with the postoperative effect (ρ = 0.863, p < 0.001). Both tremor amplitude and AUCP declined gradually during coagulation. Peak frequency did not change significantly intraoperatively. In conclusion, the study data show that both the intraoperative insertion effect and the post-coagulation effect are good predictors for thalamotomy outcomes.

Distinct cortical and subcortical predictors of Purdue Pegboard decline in Parkinson's disease and atypical parkinsonism

Objective measures of disease progression are critically needed in research on Parkinson's disease (PD) and atypical Parkinsonism but may be hindered by both practicality and cost. The Purdue Pegboard Test (PPT) is objective, has high test-retest reliability, and has a low cost. The goals of this study were to determine: (1) longitudinal changes in PPT in a multisite cohort of patients with PD, atypical Parkinsonism, and healthy controls; (2) whether PPT performance reflects brain pathology revealed by neuroimaging; (3) quantify kinematic deficits shown by PD patients during PPT. Parkinsonian patients showed a decline in PPT performance that correlated with motor symptom progression, which was not seen in controls. Neuroimaging measures from basal ganglia were significant predictors of PPT performance in PD, whereas cortical, basal ganglia, and cerebellar regions were predictors for atypical Parkinsonism. Accelerometry in a subset of PD patients showed a diminished range of acceleration and irregular patterns of acceleration, which correlated with PPT scores.

Torque complexity of maximal knee extensor isometric contraction in individuals following anterior cruciate ligament reconstruction

BACKGROUND

Current rehabilitation goals following anterior cruciate ligament reconstruction are structured around the maximal force generating capabilities of the muscle. Force fluctuations, an index of force control, have been observed to alter post- anterior cruciate ligament reconstruction. The temporal structure, or "complexity" of force fluctuations may provide important insight into the post-operative muscular recovery. The aims of this study were 1) to compare quadriceps torque complexity in anterior cruciate ligament reconstructed patients to the contralateral limb and to healthy, controls and 2) to assess the relationships between torque complexity to patient outcomes.

METHODS

Data from 120 anterior cruciate ligament reconstructed participants (65 Females, 21.0 ± 8.3 years, 5.96 ± 0.48-months post-surgery) and 95 healthy controls (50 Females, 21.5 ± 2.9 years) were collected. A 30-s knee extensor maximal isometric contraction was completed to calculate approximate entropy, a measure of torque complexity.

FINDINGS

Approximate entropy was found to decrease throughout the 30-s trial (P < .001, Cohen's d = 1.87 [1.64,2.10]). The anterior cruciate ligament reconstructed limb demonstrated greater approximate entropy compared to the contralateral limb or to healthy controls (P < .001, Cohen's d = 0.64 [0.38,0.90]). approximate entropy at the end of the trial demonstrated weak, negatively relationships with peak torque, patient reported outcome measures, and knee extensor fatigue (r = -0.21 to -0.32, P < .05).

INTERPRETATION

A greater torque complexity in individuals following anterior cruciate ligament reconstruction was weakly related to lower quadriceps strength, lower subjective function, and quadriceps fatigue resistance. The complexity of force fluctuations during a sustained maximal task may draw clinical insight into the recovery of motor function following anterior cruciate ligament reconstruction.

Detection of intermuscular coordination based on the causality of empirical mode decomposition

Considering the stochastic nature of electromyographic (EMG) signals, nonlinear methods may be a more accurate approach to study intermuscular coordination than the linear approach. The aims of this study were to assess the coordination between two ankle plantar flexors using EMG by applying the causal decomposition approach and assessing whether the intermuscular coordination is affected by the slope of the treadmill. The medial gastrocnemius (MG) and soleus muscles (SOL) were analyzed during the treadmill walking at inclinations of 0°, 5°, and 10°. The coordination was evaluated using ensemble empirical mode decomposition, and the causal interaction was encoded by the instantaneous phase dependence of time series bi-directional causality. To estimate the mutual predictability between MG and SOL, the cross-approximate entropy (XApEn) was assessed. The maximal causal interaction was observed between 40 and 75 Hz independent of inclination. XApEn showed a significant decrease between 0° and 5° (p = 0.028), between 5° and 10° (p = 0.038), and between 0° and 10° (p = 0.014), indicating an increase in coordination. Thus, causal decomposition is an appropriate methodology to study intermuscular coordination. These results indicate that the variation of loading through the change in treadmill inclination increases the interaction of the shared input between MG and SOL, suggesting increased intermuscular coordination.

Non-Contact Hand Movement Analysis for Optimal Configuration of Smart Sensors to Capture Parkinson's Disease Hand Tremor

Parkinson’s disease affects millions worldwide with a large rise in expected burden over the coming decades. More easily accessible tools and techniques to diagnose and monitor Parkinson’s disease can improve the quality of life of patients. With the advent of new wearable technologies such as smart rings and watches, this is within reach. However, it is unclear what method for these new technologies may provide the best opportunity to capture the patient-specific severity. This study investigates which locations on the hand can be used to capture and monitor maximal movement/tremor severity. Using a Leap Motion device and custom-made software the volume, velocity, acceleration, and frequency of Parkinson’s (n = 55, all right-handed, majority right-sided onset) patients’ hand locations (25 joints inclusive of all fingers/thumb and the wrist) were captured simultaneously. Distal locations of the right hand, i.e., the ends of fingers and the wrist showed significant trends (p < 0.05) towards having the largest movement velocities and accelerations. The right hand, compared with the left hand, showed significantly greater volumes, velocities, and accelerations (p < 0.01). Supplementary analysis showed that the volumes, acceleration, and velocities had significant correlations (p < 0.001) with clinical MDS-UPDRS scores, indicating the potential suitability of using these metrics for monitoring disease progression. Maximal movements at the distal hand and wrist area indicate that these locations are best suited to capture hand tremor movements and monitor Parkinson’s disease.

Intraoperative Quantification of MDS-UPDRS Tremor Measurements Using 3D Accelerometry: A Pilot Study

The most frequently used method for evaluating tremor in Parkinson’s disease (PD) is currently the internationally standardized Movement Disorder Society—Unified PD Rating Scale (MDS-UPDRS). However, the MDS-UPDRS is associated with limitations, such as its inherent subjectivity and reliance on experienced raters. Objective motor measurements using accelerometry may overcome the shortcomings of visually scored scales. Therefore, the current study focuses on translating the MDS-UPDRS tremor tests into an objective scoring method using 3D accelerometry. An algorithm to measure and classify tremor according to MDS-UPDRS criteria is proposed. For this study, 28 PD patients undergoing neurosurgical treatment and 26 healthy control subjects were included. Both groups underwent MDS-UPDRS tests to rate tremor severity, while accelerometric measurements were performed at the index fingers. All measurements were performed in an off-medication state. Quantitative measures were calculated from the 3D acceleration data, such as tremor amplitude and area-under-the-curve of power in the 4−6 Hz range. Agreement between MDS-UPDRS tremor scores and objective accelerometric scores was investigated. The trends were consistent with the logarithmic relationship between tremor amplitude and MDS-UPDRS score reported in previous studies. The accelerometric scores showed a substantial concordance (>69.6%) with the MDS-UPDRS ratings. However, accelerometric kinetic tremor measures poorly associated with the given MDS-UPDRS scores (R2 < 0.3), mainly due to the noise between 4 and 6 Hz found in the healthy controls. This study shows that MDS-UDPRS tremor tests can be translated to objective accelerometric measurements. However, discrepancies were found between accelerometric kinetic tremor measures and MDS-UDPRS ratings. This technology has the potential to reduce rater dependency of MDS-UPDRS measurements and allow more objective intraoperative monitoring of tremor.

Motion characteristics of subclinical tremors in Parkinson's disease and normal subjects

The characteristics of the Parkinson’s disease tremor reported previously are not applicable to the full spectrum of severity. The characteristics of high- and low-amplitude tremors differ in signal regularity and frequency dispersion, a phenomenon that indicates characterisation should be studied separately based on the severity. The subclinical tremor of Parkinson’s disease is close to physiological tremor in terms of amplitude and frequency, and their distinctive features are still undetermined. We aimed to determine joint motion characteristics that are unique to subclinical Parkinson’s disease tremors. The tremors were characterised by four hand–arm motions based on displacement and peak frequencies. The rest and postural tremors of 63 patients with Parkinson’s disease and 62 normal subjects were measured with inertial sensors. The baseline was established from normal tremors, and the joint motions were compared within and between the two subject groups. Displacement analysis showed that pronation–supination and wrist abduction–adduction are the most and least predominant tremor motions for both Parkinson’s disease and normal tremors, respectively. However, the subclinical Parkinson’s disease tremor has significant greater amplitude and peak frequency in specific predominant motions compared with the normal tremor. The flexion–extension of normal postural tremor increases in frequency from the proximal to distal segment, a phenomenon that is explainable by mechanical oscillation. This characteristic is also observed in patients with Parkinson’s disease but with amplification in wrist and elbow joints. The contributed distinctive characteristics of subclinical tremors provide clues on the physiological manifestation that is a result of the neuromuscular mechanism of Parkinson’s disease.

Analysis of Movement Entropy during Community Dance Programs for People with Parkinson's Disease and Older Adults: A Cohort Study

Dance therapy can improve motor skills, balance, posture, and gait in people diagnosed with Parkinson’s disease (PD) and healthy older adults (OA). It is not clear how specific movement patterns during dance promote these benefits. The purpose of this cohort study was to identify differences and complexity in dance movement patterns among different dance styles for PD and OA participants in community dance programs using approximate entropy (ApEn) analysis. The hypothesis was that PD participants will show greater ApEn during dance than OA participants and that the unique dance style of tango with more pronounced foot technique and sharp direction changes will show greater ApEn than smoother dance types such as foxtrot and waltz characterized by gradual changes in direction and gliding movement with rise and fall. Individuals participated in one-hour community dance classes. Movement data were captured using porTable 3D motion capture sensors attached to the arms, torso and legs. Classes were also video recorded to assist in analyzing the dance steps. Movement patterns were captured and ApEn was calculated to quantify the complexity of movements. Participants with PD had greater ApEn in right knee flexion during dance movements than left knee flexion (p = 0.02), greater ApEn of right than left hip flexion (p = 0.05), and greater left hip rotation than right (p = 0.03). There was no significant difference in ApEn of body movements (p > 0.4) or mean body movements (p > 0.3) at any body-segment in OA. ApEn analysis is valuable for quantifying the degree of control and predictability of dance movements and could be used as another tool to assess the movement control of dancers and aid in the development of dance therapies.

Physiological complexity: influence of ageing, disease and neuromuscular fatigue on muscle force and torque fluctuations

NEW FINDINGS

What is the topic of this review? Physiological complexity in muscle force and torque fluctuations, specifically the quantification of complexity, how neuromuscular complexityis altered by perturbations and the potential mechanism underlying changes in neuromuscular complexity. What advances does it highlight? The necessity to calculate both magnitude- and complexity-based measures for the thorough evaluation of force/torque fluctuations. Also the need for further research on neuromuscular complexity, particularly how it relates to the performance of functional activities (e.g. manual dexterity, balance, locomotion).

ABSTRACT

Physiological time series produce inherently complex fluctuations. In the last 30 years, methods have been developed to characterise these fluctuations, and have revealed that they contain information about the function of the system producing them. Two broad classes of metrics are used: (1) those which quantify the regularity of the signal (e.g. entropy metrics); and (2) those which quantify the fractal properties of the signal (e.g. detrended fluctuation analysis). Using these techniques, it has been demonstrated that ageing results in a loss of complexity in the time series of a multitude of signals, including heart rate, respiration, gait and, crucially, muscle force or torque output. This suggests that as the body ages, physiological systems become less adaptable (i.e. the systems' ability to respond rapidly to a changing external environment is diminished). More recently, it has been shown that neuromuscular fatigue causes a substantial loss of muscle torque complexity, a process that can be observed in a few minutes, rather than the decades it requires for the same system to degrade with ageing. The loss of torque complexity with neuromuscular fatigue appears to occur exclusively above the critical torque (at least for tasks lasting up to 30 min). The loss of torque complexity can be exacerbated with previous exercise of the same limb, and reduced by the administration of caffeine, suggesting both peripheral and central mechanisms contribute to this loss. The mechanisms underpinning the loss of complexity are not known but may be related to altered motor unit behaviour as the muscle fatigues.

The Thermodynamic Consequences of Parkinson's Disease

Several lines of evidence point to a pervasive disturbance of energy balance in Parkinson's disease (PD). Weight loss, common and multifactorial, is the most observable sign of this. Bradykinesia may be best understood as an underinvestment of energy in voluntary movement. This accords with rodent experiments that emphasise the importance of dopamine in allocating motor energy expenditure. Oxygen consumption studies in PD suggest that, when activities are standardised for work performed, these inappropriate energy thrift settings are actually wasteful. That the dopaminergic deficit of PD creates a problem with energy efficiency highlights the role played by the basal ganglia, and by dopamine, in thermodynamic governance. This involves more than balancing energy, since living things maintain their internal order by controlling transformations of energy, resisting probabilistic trends to more random states. This review will also look at recent research in PD on the analysis of entropy-an information theory metric of predictability in a message-in recordings from the basal ganglia. Close relationships between energy and information converge around the concept of entropy. This is especially relevant to the motor system, which regulates energy exchange with the outside world through its flow of information. The malignant syndrome in PD, a counterpart of neuroleptic malignant syndrome, demonstrates how much thermodynamic disruption can result from breakdown of motor signalling in an extreme hypodopaminergic state. The macroenergetic disturbances of PD are consistent with a unifying hypothesis of dopamine's neurotransmitter actions-to adapt energy expenditure to prevailing economic circumstances.

Gait Variability in Spinocerebellar Ataxia Assessed Using Wearable Inertial Sensors

BACKGROUND

Quantitative assessment of severity of ataxia-specific gait impairments from wearable technology could provide sensitive performance outcome measures with high face validity to power clinical trials.

OBJECTIVES

The aim of this study was to identify a set of gait measures from body-worn inertial sensors that best discriminate between people with prodromal or manifest spinocerebellar ataxia (SCA) and age-matched, healthy control subjects (HC) and determine how these measures relate to disease severity.

METHODS

One hundred and sixty-three people with SCA (subtypes 1, 2, 3, and 6), 42 people with prodromal SCA, and 96 HC wore 6 inertial sensors while performing a natural pace, 2-minute walk. Areas under the receiver operating characteristic curves (AUC) were compared for 25 gait measures, including standard deviations as variability, to discriminate between ataxic and normal gait. Pearson's correlation coefficient assessed the relationships between the gait measures and severity of ataxia.

RESULTS

Increased gait variability was the most discriminative gait feature of SCA; toe-out angle variability (AUC = 0.936; sensitivity = 0.871; specificity = 0.896) and double-support time variability (AUC = 0.932; sensitivity = 0.834; specificity = 0.865) were the most sensitive and specific measures. These variability measures were also significantly correlated with the scale for the assessment and rating of ataxia (SARA) and disease duration. The same gait measures discriminated gait of people with prodromal SCA from the gait of HC (AUC = 0.610, and 0.670, respectively).

CONCLUSIONS

Wearable inertial sensors provide sensitive and specific measures of excessive gait variability in both manifest and prodromal SCAs that are reliable and related to the severity of the disease, suggesting they may be useful as clinical trial performance outcome measures. © 2021 International Parkinson and Movement Disorder Society.

Smartphone-Based Prediction Model for Postoperative Cardiac Surgery Outcomes Using Preoperative Gait and Posture Measures

Gait speed assessment increases the predictive value of mortality and morbidity following older adults' cardiac surgery. The purpose of this study was to improve clinical assessment and prediction of mortality and morbidity among older patients undergoing cardiac surgery through the identification of the relationships between preoperative gait and postural stability characteristics utilizing a noninvasive-wearable mobile phone device and postoperative cardiac surgical outcomes. This research was a prospective study of ambulatory patients aged over 70 years undergoing non-emergent cardiac surgery. Sixteen older adults with cardiovascular disease (Age 76.1 ± 3.6 years) scheduled for cardiac surgery within the next 24 h were recruited for this study. As per the Society of Thoracic Surgeons (STS) recommendation guidelines, eight of the cardiovascular disease (CVD) patients were classified as frail (prone to adverse outcomes with gait speed ≤0.833 m/s) and the remaining eight patients as non-frail (gait speed >0.833 m/s). Treating physicians and patients were blinded to gait and posture assessment results not to influence the decision to proceed with surgery or postoperative management. Follow-ups regarding patient outcomes were continued until patients were discharged or transferred from the hospital, at which time data regarding outcomes were extracted from the records. In the preoperative setting, patients performed the 5-m walk and stand still for 30 s in the clinic while wearing a mobile phone with a customized app "Lockhart Monitor" available at iOS App Store. Systematic evaluations of different gait and posture measures identified a subset of smartphone measures most sensitive to differences in two groups (frail versus non-frail) with adverse postoperative outcomes (morbidity/mortality). A regression model based on these smartphone measures tested positive on five CVD patients. Thus, clinical settings can readily utilize mobile technology, and the proposed regression model can predict adverse postoperative outcomes such as morbidity or mortality events.

Building a Machine-Learning Framework to Remotely Assess Parkinson's Disease Using Smartphones

OBJECTIVE

Parkinson's disease (PD) is a neurodegenerative disorder that affects multiple neurological systems. Traditional PD assessment is conducted by a physician during infrequent clinic visits. Using smartphones, remote patient monitoring has the potential to obtain objective behavioral data semi-continuously, track disease fluctuations, and avoid rater dependency.

METHODS

Smartphones collect sensor data during various active tests and passive monitoring, including balance (postural instability), dexterity (skill in performing tasks using hands), gait (the pattern of walking), tremor (involuntary muscle contraction and relaxation), and voice. Some of the features extracted from smartphone data are potentially associated with specific PD symptoms identified by physicians. To leverage large-scale cross-modality smartphone features, we propose a machine-learning framework for performing automated disease assessment. The framework consists of a two-step feature selection procedure and a generic model based on the elastic-net regularization.

RESULTS

Using this framework, we map the PD-specific architecture of behaviors using data obtained from both PD participants and healthy controls (HCs). Utilizing these atlases of features, the framework shows promises to (a) discriminate PD participants from HCs, and (b) estimate the disease severity of individuals with PD.

SIGNIFICANCE

Data analysis results from 437 behavioral features obtained from 72 subjects (37 PD and 35 HC) sampled from 17 separate days during a period of up to six months suggest that this framework is potentially useful for the analysis of remotely collected smartphone sensor data in individuals with PD.

Electromyography Biomarkers for Quantifying the Intraoperative Efficacy of Deep Brain Stimulation in Parkinson's Patients With Resting Tremor

Introduction: Deep brain stimulation (DBS) is an effective therapy for resting tremor in Parkinson's disease (PD). However, quick and objective biomarkers for quantifying the efficacy of DBS intraoperatively are lacking. Therefore, we aimed to study how DBS modulates the intraoperative neuromuscular pattern of resting tremor in PD patients and to find predictive surface electromyography (sEMG) biomarkers for quantifying the intraoperative efficacy of DBS. Methods: Intraoperative sEMG of 39 PD patients with resting tremor was measured with the DBS on and off, respectively, during the intraoperative DBS testing stage. Twelve signal features (time and frequency domains) were extracted from the intraoperative sEMG data. These sEMG features were associated with the clinical outcome to evaluate the efficacy of intraoperative DBS. Also, an sEMG-based prediction model was established to predict the clinical improvement rate (IR) of resting tremor with DBS therapy. Results: A typical resting tremor with a peak frequency of 4.93 ± 0.98 Hz (mean ± SD) was measured. Compared to the baseline, DBS modulated significant neuromuscular pattern changes in most features except for the peak frequency, by decreasing the motor unit firing rate, amplitude, or power and by changing the regularity pattern. Three sEMG features were detected with significant associations with the clinical improvement rate (IR) of the tremor scale: peak frequency power (R = 0.37, p = 0.03), weighted root mean square (R = 0.42, p = 0.01), and modified mean amplitude power (R = 0.48, p = 0.003). These were adopted to train a Gaussian process regression model with a leave-one-out cross-validation procedure. The prediction values from the trained sEMG prediction model (1,000 permutations, p = 0.003) showed a good correlation (r = 0.47, p = 0.0043) with the true IR of the tremor scale. Conclusion: DBS acutely modulated the intraoperative resting tremor, mainly by suppressing the amplitude and motor unit firing rate and by changing the regularity pattern, but not by modifying the frequency pattern. Three features showed strong robustness and could be used as quick intraoperative biomarkers to quantify and predict the efficacy of DBS in PD patients with resting tremor.

Gender differences in nonlinear motor performance following concussion

PURPOSE

To quantify differences in nonlinear aspects of performance on a seated visual-motor tracking task between clinically asymptomatic males and females with and without a self-reported mild traumatic brain injury history.

METHODS

Seventy-three individuals with a self-reported concussion history (age: 21.40 ± 2.25 years, mean ± SD) and 75 without completed the visual-motor tracking task (age: 21.50 ± 2.00 years). Participants pressed an index finger against a force sensor, tracing a line across a computer screen (visual-motor tracking). The produced signal's root-mean-square error (RMSE), sample entropy (SampEn, a measure of regularity), and average power (AvP) between 0 and 12 Hz were calculated.

RESULTS

Males with a history of 0 or 1 concussion had greater RMSE (worse performance) than females with 0 (p < 0.0001) and 1 concussion (p = 0.052). Additionally, females with 2+ concussions exhibited lower SampEn than females with no history (p = 0.001) or a history of 1 concussion (p = 0.026). Finally, females with 2+ concussions had lower 8-12 Hz AvP than males with 2+ concussions (p = 0.031). Few differences were observed in the male participants.

CONCLUSION

Females with a self-reported history of multiple concussions exhibited lower SampEn in the visual-motor tracking-task force output structure as compared to those with no reported history of concussion and their male counterparts. Lower SampEn and lower power between 8 and 12 Hz indicated persistent impairment in visual processing and feed-forward or predictive motor control systems.

Experimental knee-related pain enhances attentional interference on postural control

PURPOSE

To quantify how postural stability is modified during experimental pain while performing different cognitively demanding tasks.

METHODS

Sixteen healthy young adults participated in the experiment. Pain was induced by intramuscular injection of hypertonic saline solution (1 mL, 6%) in both vastus medialis and vastus lateralis muscles (0.9% isotonic saline was used as control). The participants stood barefoot in tandem position for 1 min on a force plate. Center of pressure (CoP) was recorded before and immediately after injections, while performing two cognitive tasks: (i) counting forwards by adding one; (ii) counting backwards by subtracting three. CoP variables-total area of displacement, velocity in anterior-posterior (AP-velocity) and medial-lateral (ML-velocity) directions, and CoP sample entropy in anterior-posterior and medial-lateral directions were displayed as the difference between the values obtained after and before each injection and compared between tasks and injections.

RESULTS

CoP total area ( - 84.5 ± 145.5 vs. 28.9 ± 78.5 cm²) and ML-velocity ( - 1.71 ± 2.61 vs. 0.98 ± 1.93 cm/s) decreased after the painful injection vs. Control injection while counting forward (P < 0.05). CoP total area (12.8 ± 53.9 vs. - 84.5 ± 145.5 cm²), ML-velocity ( - 0.34 ± 1.92 vs. - 1.71 ± 2.61 cm/s) and AP-velocity (1.07 ± 2.35 vs. - 0.39 ± 1.82 cm/s) increased while counting backwards vs. forwards after the painful injection (P < 0.05).

CONCLUSION

Pain interfered with postural stability according to the type of cognitive task performed, suggesting that pain may occupy cognitive resources, potentially resulting in poorer balance performance.

A widespread visually-sensitive functional network relates to symptoms in essential tremor

Essential tremor is a neurological syndrome of heterogeneous pathology and aetiology that is characterized by tremor primarily in the upper extremities. This tremor is commonly hypothesized to be driven by a single or multiple neural oscillator(s) within the cerebello-thalamo-cortical pathway. Several studies have found an association of blood-oxygen level-dependent (BOLD) signal in the cerebello-thalamo-cortical pathway with essential tremor, but there is behavioural evidence that also points to the possibility that the severity of tremor could be influenced by visual feedback. Here, we directly manipulated visual feedback during a functional MRI grip force task in patients with essential tremor and control participants, and hypothesized that an increase in visual feedback would exacerbate tremor in the 4-12 Hz range in essential tremor patients. Further, we hypothesized that this exacerbation of tremor would be associated with dysfunctional changes in BOLD signal and entropy within, and beyond, the cerebello-thalamo-cortical pathway. We found that increases in visual feedback increased tremor in the 4-12 Hz range in essential tremor patients, and this increase in tremor was associated with abnormal changes in BOLD amplitude and entropy in regions within the cerebello-thalamo-motor cortical pathway, and extended to visual and parietal areas. To determine if the tremor severity was associated with single or multiple brain region(s), we conducted a birectional stepwise multiple regression analysis, and found that a widespread functional network extending beyond the cerebello-thalamo-motor cortical pathway was associated with changes in tremor severity measured during the imaging protocol. Further, this same network was associated with clinical tremor severity measured with the Fahn, Tolosa, Marin Tremor Rating Scale, suggesting this network is clinically relevant. Since increased visual feedback also reduced force error, this network was evaluated in relation to force error but the model was not significant, indicating it is associated with force tremor but not force error. This study therefore provides new evidence that a widespread functional network is associated with the severity of tremor in patients with essential tremor measured simultaneously at the hand during functional imaging, and is also associated with the clinical severity of tremor. These findings support the idea that the severity of tremor is exacerbated by increased visual feedback, suggesting that designers of new computing technologies should consider using lower visual feedback levels to reduce tremor in essential tremor.

Evaluation of tremor interference with control of voluntary reaching movements in patients with Parkinson's disease

BACKGROUND

A large population of patients with Parkinson's disease (PD) displays the symptom of resting tremor. However, the extent that resting tremor may affect the performance of movement control has not been evaluated specifically. This study aims at establishing methods to quantitatively evaluate motor performance in PD patients with tremor, and at analyzing the interfering effects of tremor on control of reaching movements.

METHODS

Ten PD patients with tremor and Ten healthy control subjects were recruited to participate in this study. All patients and healthy control subjects performed point-to-point reaching movements with their tremor affected arm or preferred arm. We verified that a smoothing model of minimum-jerk trajectory (MJT) can be used to extract voluntary movement trajectory from tremor-corrupted movement trajectory in the reaching tasks by the patients. Performance indices of reaction time (RT) and movement time (MT) of reaching movements by the PD subjects with tremor were evaluated using MJT trajectories. Differences of RT and MT between the recorded trajectories and MJT in PD and control subjects were calculated to investigate the extent that tremor may affect their motor performance. Linear mixed-effects model was used to identify the contributions of tremor, bradykinesia and rigidity to the performance indices of RT and MT based on UPDRS scores. The power spectrum densities (PSD) of tremor were also evaluated using hand velocities to represent tremor intensity and to analyze their correlations with RT and MT.

RESULTS

The MJT model demonstrated good fit to recorded trajectory with a more consistent estimation of motor performance for both PD and control subjects. The RT and MT of patients were found to be 43.4 and 79.5% longer respectively than those of healthy control subjects. Analysis of the linear mixed-effects model was not able to reveal that tremor, bradykinesia and rigidity each had a significant contribution to RT or MT in PD patients with tremor. However, the PSD of tremor was found to correlate significantly to RT, but not to MT, in both linear regression and linear mixed-effects model.

CONCLUSIONS

The minimum-jerk trajectory and power spectrum densities are effective quantitative tools for evaluating motor performance for PD patients with tremor. Resting tremor is one of the factors prolonging the initiation of voluntary reaching movement in these patients.

Entropy Analysis for the Evaluation of Respiratory Changes Due to Asbestos Exposure and Associated Smoking

Breathing is a complex rhythmic motor act, which is created by integrating different inputs to the respiratory centres. Analysing nonlinear fluctuations in breathing may provide clinically relevant information in patients with complex illnesses, such as asbestosis. We evaluated the effect of exposition to asbestos on the complexity of the respiratory system by investigating the respiratory impedance sample entropy (SampEnZrs) and recurrence period density entropy (RPDEnZrs). Similar analyses were performed by evaluating the airflow pattern sample entropy (SampEnV') and recurrence period density entropy (RPDEnV'). Groups of 34 controls and 34 asbestos-exposed patients were evaluated in the respiratory impedance entropy analysis, while groups of 34 controls and 30 asbestos-exposed patients were investigated in the analysis of airflow entropy. Asbestos exposition introduced a significant reduction of RPDEnV' in non-smoker patients (p < 0.0004), which suggests that the airflow pattern becomes less complex in these patients. Smoker patients also presented a reduction in RPDEnV' (p < 0.05). These finding are consistent with the reduction in respiratory system adaptability to daily life activities observed in these patients. It was observed a significant reduction in SampEnV' in smoker patients in comparison with non-smokers (p < 0.02). Diagnostic accuracy evaluations in the whole group of patients (including non-smokers and smokers) indicated that RPDEnV' might be useful in the diagnosis of respiratory abnormalities in asbestos-exposed patients, showing an accuracy of 72.0%. In specific groups of non-smokers, RPDEnV' also presented adequate accuracy (79.0%), while in smoker patients, SampEnV' and RPDEnV' presented adequate accuracy (70.7% and 70.2%, respectively). Taken together, these results suggest that entropy analysis may provide an early and sensitive functional indicator of interstitial asbestosis.

The effects of age and musculoskeletal pain on force variability among manual workers

The present study investigated the influence of age and musculoskeletal pain on force variability during a continuous isometric handgrip force task performed at 30% of maximal voluntary contraction carried out until failure. We recruited 96 male manual workers aged 51-72 years. The participants were stratified according to their age (50-59 and 60+ years) and by pain status (no pain, acute pain and chronic pain). The amplitude and structure of variability expressed as respectively standard deviation (SD) and coefficient of variation (CV), and sample entropy (SaEn) were calculated from the endurance task. The oldest group had an approximately 18% longer endurance time than the youngest group. No between-group differences were found in SD or CV, whereas a significant interaction between age and pain stage was found for SaEn. The youngest group showed lower SaEn than the oldest for both those with chronic pain and those without pain, indicating less force complexity, whereas a tendency for the opposite was found in the acute pain group. Within the pain stage groups, workers with acute pain had higher SaEn compared with both the no pain and chronic pain groups. These findings suggest that age and musculoskeletal pain differentially affects the structure of force variability in manual workers.

Increased EMG intermuscular coherence and reduced signal complexity in Parkinson's disease

OBJECTIVES

To investigate differences in surface electromyography (EMG) features in individuals with idiopathic Parkinson's disease (PD) and aged-matched controls.

METHODS

Surface EMG was recorded during isometric leg extension in PD patients prior to, and after undergoing a locomotor training programme, and in aged-matched controls. Differences in EMG structure were quantified using determinism (%DET), sample entropy (SampEn) and intermuscular coherence.

RESULTS

%DET was significantly higher, and SampEn significantly lower, in PD patients. Intermuscular coherence was also significantly higher in the PD group in theta, alpha and beta frequency bands. %DET increased and SampEn decreased with increasing Movement-Disorder-Society UPDRS scores, while theta band coherence was significantly correlated with total MDS-UPDRS scores and torque variance. Neither %DET, SampEn nor intermuscular coherence changed in response to training.

CONCLUSIONS

The differences observed are consistent with increased synchrony among motor units within and across leg muscles in PD. Differences between EMG signals recorded from the PD and control groups persisted post-therapy, after improvements in walking capacity occurred.

SIGNIFICANCE

These results provide insight into changes in motoneuron activity in PD, demonstrate increased beta band intramuscular coherence in PD for the first time, and support the development of quantitative biomarkers for PD based on advanced surface EMG features.

Persistence in postural dynamics is dependent on constraints of vision, postural orientation, and the temporal structure of support surface translations

Activities of daily living require maintaining upright posture within a variety of environmental constraints. A healthy postural control system can adapt to different environmental constraints. Afferent sensory information is used to determine where the body is in relation to the gravitational vertical and efferent motor commands make corrections with the goal of keeping the center of mass within the base of support. The purpose of this research was to understand how vision, direction of translation, and the temporal correlation of the support surface stimuli affected the persistence characteristics of postural dynamics on short and long time scales. Ten healthy young adults performed a standing task with either eyes open or closed, oriented anteriorly or mediolaterally while the support surface underwent structured translations based on different levels of temporal correlation-white noise (no correlation), pink noise (moderate correlation), and red noise and sinusoidal movements (strong correlations). Center of pressure velocity was analyzed using fractal analysis to determine the dynamics of postural control. On the short time scale, persistence was shown to be stronger with eyes closed, in the mediolateral direction, and when the structure of translation contained stronger temporal correlation. On the long time scale, anti-persistence was stronger with eyes closed, in the mediolateral direction, and for all structures of movement except red noise. This study provides deeper insight into the flexibility existing in human movement responses to structured environmental stimuli through the fractal analysis of movement variability.

Technology-based assessment of motor and nonmotor phenomena in Parkinson disease

INTRODUCTION

The increasing development and availability of portable and wearable technologies is rapidly expanding the field of technology-based objective measures (TOMs) in neurological disorders, including Parkinson disease (PD). Substantial challenges remain in the recognition of disease phenomena relevant to patients and clinicians, as well as in the identification of the most appropriate devices to carry out these measurements. Areas covered: The authors systematically reviewed PubMed for studies employing technology as outcome measures in the assessment of PD-associated motor and nonmotor abnormalities. Expert commentary: TOMs minimize intra- and inter-rater variability in clinical assessments of motor and nonmotor phenomena in PD, improving the accuracy of clinical endpoints. Critical unmet needs for the integration of TOMs into clinical and research practice are the identification and validation of relevant endpoints for individual patients, the capture of motor and nonmotor activities from an ecologically valid environment, the integration of various sensor data into an open-access, common-language platforms, and the definition of a regulatory pathway for approval of TOMs. The current lack of multidomain, multisensor, smart technologies to measure in real time a wide scope of relevant changes remain a significant limitation for the integration of technology into the assessment of PD motor and nonmotor functional disability.

Evaluation of smartphone-based testing to generate exploratory outcome measures in a phase 1 Parkinson's disease clinical trial

BACKGROUND

Ubiquitous digital technologies such as smartphone sensors promise to fundamentally change biomedical research and treatment monitoring in neurological diseases such as PD, creating a new domain of digital biomarkers.

OBJECTIVES

The present study assessed the feasibility, reliability, and validity of smartphone-based digital biomarkers of PD in a clinical trial setting.

METHODS

During a 6-month, phase 1b clinical trial with 44 Parkinson participants, and an independent, 45-day study in 35 age-matched healthy controls, participants completed six daily motor active tests (sustained phonation, rest tremor, postural tremor, finger-tapping, balance, and gait), then carried the smartphone during the day (passive monitoring), enabling assessment of, for example, time spent walking and sit-to-stand transitions by gyroscopic and accelerometer data.

RESULTS

Adherence was acceptable: Patients completed active testing on average 3.5 of 7 times/week. Sensor-based features showed moderate-to-excellent test-retest reliability (average intraclass correlation coefficient = 0.84). All active and passive features significantly differentiated PD from controls with P < 0.005. All active test features except sustained phonation were significantly related to corresponding International Parkinson and Movement Disorder Society-Sponsored UPRDS clinical severity ratings. On passive monitoring, time spent walking had a significant (P = 0.005) relationship with average postural instability and gait disturbance scores. Of note, for all smartphone active and passive features except postural tremor, the monitoring procedure detected abnormalities even in those Parkinson participants scored as having no signs in the corresponding International Parkinson and Movement Disorder Society-Sponsored UPRDS items at the site visit.

CONCLUSIONS

These findings demonstrate the feasibility of smartphone-based digital biomarkers and indicate that smartphone-sensor technologies provide reliable, valid, clinically meaningful, and highly sensitive phenotypic data in Parkinson's disease. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Characterization of Parkinsonian Hand Tremor and Validation of a High-Order Tremor Estimator

Recent progress in wearable technology has made wearable tremor suppression devices (WTSDs) for Parkinson's patients a potentially viable alternative solution for tremor management. So far, in contrast to wrist and elbow tremor, finger tremors have not been studied in depth despite the huge impact that they have on a patient's daily life. In addition, more evidence has been found showing that the performance of current tremor estimators may be limited by their model order due to the multiple harmonics present in tremor. The aim of this paper is to characterize finger and wrist tremor in both the time and frequency domains, and to propose a high-order tremor estimation algorithm. Tremor magnitudes are reported in the forms of linear acceleration, angular velocity, and angular displacement. The activation of forearm flexor and extensor muscles is also investigated. The frequency analysis shows that Parkinsonian tremors produce oscillations of the hand with pronounced harmonics. At last, a high-order weighted-frequency Fourier linear combiner (WFLC)-based Kalman filter is proposed. The percentage estimation accuracy achieved from the proposed estimator is 96.3 ± 1.7%, showing average improvements of 28.5% and 48.9% over its lower-order counterpart and the WFLC. The proposed estimator shows promise for use in a WTSD.

Dynamical Properties of Postural Control in Obese Community-Dwelling Older Adults †

Postural control is a key aspect in preventing falls. The aim of this study was to determine if obesity affected balance in community-dwelling older adults and serve as an indicator of fall risk. The participants were randomly assigned to receive a comprehensive geriatric assessment followed by a longitudinal assessment of their fall history. The standing postural balance was measured for 98 participants with a Body Mass Index (BMI) ranging from 18 to 63 kg/m², using a force plate and an inertial measurement unit affixed at the sternum. Participants' fall history was recorded over 2 years and participants with at least one fall in the prior year were classified as fallers. The results suggest that body weight/BMI is an additional risk factor for falling in elderly persons and may be an important marker for fall risk. The linear variables of postural analysis suggest that the obese fallers have significantly higher sway area and sway ranges, along with higher root mean square and standard deviation of time series. Additionally, it was found that obese fallers have lower complexity of anterior-posterior center of pressure time series. Future studies should examine more closely the combined effect of aging and obesity on dynamic balance.

Later stages of diabetic neuropathy affect the complexity of the neuromuscular system at the knee during low-level isometric contractions

INTRODUCTION

This study evaluates the complexity of force and surface electromyography (sEMG) during knee extension and flexion at low-level isometric contractions in individuals with different degrees of diabetic peripheral neuropathy (DPN).

METHODS

Ten control and 38 diabetic participants performed isometric contractions at 10%, 20%, and 30% of maximal voluntary contraction. Knee force and multichannel sEMG from vastus lateralis (VL) and biceps femoris were acquired. The SD of force and sample entropy (SaEn) of both force and sEMG were computed.

RESULTS

Participants with moderate DPN demonstrated high force-SD and low force-SaEn. Severely affected participants showed low SaEn in VL at all force levels.

DISCUSSION

DPN affects the complexity of the neuromuscular system at the knee for the extension task during low-level isometric contractions, with participants in the later stages of the disease (moderate and severe) demonstrating most of the changes. Muscle Nerve 57: 112-121, 2018.

Alterations in over-ground walking patterns in obese and overweight adults

Obesity has been associated with negative effects on postural control, including falls. Previous studies revealed different outcomes regarding the effects of obesity on gait features, and the use of BMI may lead to bias in assessing the true effects of obesity on gait. To better understand the effects of obesity on gait, it is important to examine gait features and associated body composition measures. The purpose of this study was: (1) to assess gait features of normal weight, overweight and obese adults, and (2) to assess the relationship between body composition measures and gait features. Thirty participants were assigned to one of three groups based upon their BMI at the onset of the study: healthy weight (BMI: 18.5-24.9kg/m²), overweight (BMI: 25-29.9kg/m²), or obese (BMI: 30-40kg/m²). Participants performed straight-line over-ground walking through a 200m hallway at their natural preferred speed while wearing their own shoes. The angular displacements, range of motion (ROM), and approximate entropy of kinematic data of the bilateral hips, knees, and ankles in the sagittal plane were computed. Walking speed, step length, stride length, single leg support phase, double leg support phase, swing phase and bilateral stance phase times were extracted from the GaitRite data. Overall, body mass and BMI were associated with peak flexion and ROM in the knees as well as single support, double support, stance, and swing phases. Body fat percentage did not exhibit correlations with measured gait features. Gait variables were more highly correlated with BMI and body mass instead of percent body fat, suggesting that absolute mass is more influential on gait features rather than amount of fat tissue.

Neuromuscular Alterations After Ankle Sprains: An Animal Model to Establish Causal Links After Injury

CONTEXT

The mechanisms that contribute to the development of chronic ankle instability are not understood. Investigators have developed a hypothetical model in which neuromuscular alterations that stem from damaged ankle ligaments are thought to affect periarticular and proximal muscle activity. However, the retrospective nature of these studies does not allow a causal link to be established.

OBJECTIVE

To assess temporal alterations in the activity of 2 periarticular muscles of the rat ankle and 2 proximal muscles of the rat hind limb after an ankle sprain.

DESIGN

Controlled laboratory study.

SETTING

Laboratory.

PATIENTS OR OTHER PARTICIPANTS

Five healthy adult male Long Evans rats (age = 16 weeks, mass = 400.0 ± 13.5 g).

INTERVENTION(S)

Indwelling fine-wire electromyography (EMG) electrodes were implanted surgically into the biceps femoris, medial gastrocnemius, vastus lateralis, and tibialis anterior muscles of the rats. We recorded baseline EMG measurements while the rats walked on a motor-driven treadmill and then induced a closed lateral ankle sprain by overextending the lateral ankle ligaments. After ankle sprain, the rats were placed on the treadmill every 24 hours for 7 days, and we recorded postsprain EMG data.

MAIN OUTCOME MEASURE(S)

Onset time of muscle activity, phase duration, sample entropy, and minimal detectable change (MDC) were assessed and compared with baseline using 2-tailed dependent t tests.

RESULTS

Compared with baseline, delayed onset time of muscle activity was exhibited in the biceps femoris (baseline = -16.7 ± 54.0 milliseconds [ms]) on day 0 (5.2 ± 64.1 ms; t₄ = -4.655, P = .043) and tibialis anterior (baseline = 307.0 ± 64.2 ms) muscles on day 3 (362.5 ± 55.9 ms; t₄ = -5.427, P = .03) and day 6 (357.3 ± 39.6 ms; t₄ = -3.802, P = .02). Longer phase durations were observed for the vastus lateralis (baseline = 321.9 ± 92.6 ms) on day 3 (401.3 ± 101.2 ms; t₃ = -4.001, P = .03), day 4 (404.1 ± 93.0 ms; t₃ = -3.320, P = .048), and day 5 (364.6 ± 105.2 ms; t₃ = -3.963, P = .03) and for the tibialis anterior (baseline = 103.9 ± 16.4 ms) on day 4 (154.9 ± 7.8 ms; t₃ = -4.331, P = .050) and day 6 (141.9 ± 16.2 ms; t₃ = -3.441, P = .03). After sprain, greater sample entropy was found for the vastus lateralis (baseline = 0.7 ± 0.3) on day 6 (0.9 ± 0.4; t₄ = -3.481, P = .03) and day 7 (0.9 ± 0.3; t₄ = -2.637, P = .050) and for the tibialis anterior (baseline = 0.6 ± 0.4) on day 4 (0.9 ± 0.5; t₄ = -3.224, P = .03). The MDC analysis revealed increased sample entropy values for the vastus lateralis and tibialis anterior.

CONCLUSIONS

Manually inducing an ankle sprain in a rat by overextending the lateral ankle ligaments altered the complexity of muscle-activation patterns, and the alterations exceeded the MDC of the baseline data.

Relationship between changes in vestibular sensory reweighting and postural control complexity

Complexity measures have become increasingly prominent in the postural control literature. Several studies have found associations between clinical balance improvements and complexity, but the relationship between sensory reweighting and complexity changes has remained unobserved. The purpose of this study was to determine the relationship between sensory reweighting via Wii Fit balance training and complexity. Twenty healthy adults completed 6 weeks of training. Participants completed the sensory organization test (SOT) before and after the sessions. Complexity of postural control was analyzed through sample entropy of the center-of-pressure velocity time series in the resultant, anterior-posterior (AP), and medial-lateral directions, and compared to SOT summary score changes. Significant differences were found between pre- and post-training for the condition five (p < .001, d = .525) and vestibular summary scores (p < .001, d = .611). Similarly, changes in complexity were observed from pre- to post-training in the resultant (p = .040, d = .427) direction. While the AP velocity was not significant (p = .07, d = .355), its effect size was moderate. A moderate correlation was revealed in the posttest between AP complexity and condition 5 (r = .442, p = .05), as well as between AP complexity and the vestibular summary score (r = .351, p = .13). The results of this study show that a moderate relationship exists between postural control complexity and the vestibular system, suggesting that complexity may reflect the neurosensory organization used to maintain upright stance.

Complexity of resting-state EEG activity in the patients with early-stage Parkinson's disease

To investigate the abnormal brain activities in the early stage of Parkinson's disease (PD), the electroencephalogram (EEG) signals were recorded with 20 channels from non-dementia PD patients (18 patients, 8 females) and age matched healthy controls (18 subjects, 8 females) during the resting state. Two methods based on the ordinal patterns of the recorded series, i.e., permutation entropy (PE) and order index (OI), were introduced to characterize the complexity of the cortical activities for two groups. It was observed that the resting-state EEG of PD patients showed lower PE and higher OI than healthy controls, which indicated that the early-stage PD caused the reduced complexity of EEG. We further applied two methods to determine the complexity of EEG rhythms in five sub-bands. The results showed that the gamma, beta and alpha rhythms of PD patients were characterized by lower PE and higher OI, i.e., reduced complexity, than healthy subjects. No significant differences were observed in theta or delta rhythms between two groups. The findings suggested that PE and OI were promising methods to detect the abnormal changes in the dynamics of EEG signals associated with early-stage PD. Further, such changes in EEG complexity may be the early markers of the cortical or subcortical dysfunction caused by PD.

Parkinsonian Balance Deficits Quantified Using a Game Industry Board and a Specific Battery of Four Paradigms

This study describes a cost-effective screening protocol for parkinsonism based on combined objective and subjective monitoring of balance function. Objective evaluation of balance function was performed using a game industry balance board and an automated analyses of the dynamic of the center of pressure in time, frequency, and non-linear domains collected during short series of stand up tests with different modalities and severity of sensorial deprivation. The subjective measurement of balance function was performed using the Dizziness Handicap Inventory questionnaire. Principal component analyses on both objective and subjective measurements of balance function allowed to obtained a specificity and selectivity for parkinsonian patients (vs. healthy subjects) of 0.67 and 0.71 respectively. The findings are discussed regarding the relevance of cost-effective balance-based screening system as strategy to meet the needs of broader and earlier screening for parkinsonism in communities with limited access to healthcare.

Loss of knee extensor torque complexity during fatiguing isometric muscle contractions occurs exclusively above the critical torque

The complexity of knee extensor torque time series decreases during fatiguing isometric muscle contractions. We hypothesized that because of peripheral fatigue, this loss of torque complexity would occur exclusively during contractions above the critical torque (CT). Nine healthy participants performed isometric knee extension exercise (6 s of contraction, 4 s of rest) on six occasions for 30 min or to task failure, whichever occurred sooner. Four trials were performed above CT (trials S1–S4, S1 being the lowest intensity), and two were performed below CT (at 50% and 90% of CT). Global, central, and peripheral fatigue were quantified using maximal voluntary contractions (MVCs) with femoral nerve stimulation. The complexity of torque output was determined using approximate entropy (ApEn) and the detrended fluctuation analysis-α scaling exponent (DFA-α). The MVC torque was reduced in trials below CT [by 19 ± 4% (means ± SE) in 90%CT], but complexity did not decrease [ApEn for 90%CT: from 0.82 ± 0.03 to 0.75 ± 0.06, 95% paired-samples confidence intervals (CIs), 95% CI = −0.23, 0.10; DFA-α from 1.36 ± 0.01 to 1.32 ± 0.03, 95% CI −0.12, 0.04]. Above CT, substantial reductions in MVC torque occurred (of 49 ± 8% in S1), and torque complexity was reduced (ApEn for S1: from 0.67 ± 0.06 to 0.14 ± 0.01, 95% CI = −0.72, −0.33; DFA-α from 1.38 ± 0.03 to 1.58 ± 0.01, 95% CI 0.12, 0.29). Thus, in these experiments, the fatigue-induced loss of torque complexity occurred exclusively during contractions performed above the CT.

Symmetry Analysis of Gait between Left and Right Limb Using Cross-Fuzzy Entropy

The purpose of this paper is the investigation of gait symmetry problem by using cross-fuzzy entropy (C-FuzzyEn), which is a recently proposed cross entropy that has many merits as compared to the frequently used cross sample entropy (C-SampleEn). First, we used several simulation signals to test its performance regarding the relative consistency and dependence on data length. Second, the gait time series of the left and right stride interval were used to calculate the C-FuzzyEn values for gait symmetry analysis. Besides the statistical analysis, we also realized a support vector machine (SVM) classifier to perform the classification of normal and abnormal gaits. The gait dataset consists of 15 patients with Parkinson's disease (PD) and 16 control (CO) subjects. The results show that the C-FuzzyEn values of the PD patients' gait are significantly higher than that of the CO subjects with a p value of less than 10⁻⁵, and the best classification performance evaluated by a leave-one-out (LOO) cross-validation method is an accuracy of 96.77%. Such encouraging results imply that the C-FuzzyEn-based gait symmetry measure appears as a suitable tool for analyzing abnormal gaits.

Tremor frequency characteristics in Parkinson's disease under resting-state and stress-state conditions

Tremor characteristics-amplitude and frequency components-are primary quantitative clinical factors for diagnosis and monitoring of tremors. Few studies have investigated how different patient's conditions affect tremor frequency characteristics in Parkinson's disease (PD). Here, we analyzed tremor characteristics under resting-state and stress-state conditions. Tremor was recorded using an accelerometer on the finger, under resting-state and stress-state (calculation task) conditions, during rest tremor and postural tremor. The changes of peak power, peak frequency, mean frequency, and distribution of power spectral density (PSD) of tremor were evaluated across conditions. Patients whose tremors were considered more than "mild" were selected, for both rest (n=67) and postural (n=25) tremor. Stress resulted in both greater peak powers and higher peak frequencies for rest tremor (p<0.001), but not for postural tremor. Notably, peak frequencies were concentrated around 5 Hz under stress-state condition. The distributions of PSD of tremor were symmetrical, regardless of conditions. Tremor is more evident and typical tremor characteristics, namely a lower frequency as amplitude increases, are different in stressful condition. Patient's conditions directly affect neural oscillations related to tremor frequencies. Therefore, tremor characteristics in PD should be systematically standardized across patient's conditions such as attention and stress levels.

Desktop Haptic Interface for Simulation of Hand-Tremor

This paper presents a haptic system that is conceived to support the design process of a class of products or services in order to make them more accessible to people affected by hand tremor diseases. The main aim is to foster the designer empathy allowing her/him to directly feel the effect of the impairment in first person. Specifically, a desktop haptic device is employed to induce a programmable hand-tremor, that is typically observed in people affected by some kind of neurological diseases, on healthy subjects (i.e., the designers). The developed tool is based on a wrist-attached haptic interface with a workspace that is comparable to that of the arm of the user. Such device is able to exert controlled forces on the user's wrist and induces a hand-tremor whose frequency and amplitude are correlated with those measured on impaired people. The control of the device is based on a custom trajectory-tracking algorithm that takes as input tremor signals that are acquired on patients using an optical motion tracking system. In this paper, we present the employed haptic system, the structure of the control system and the experimental validation of the controller done through the acquisition of data on six patients affected by Parkinson's disease.

Failure of Arm Movement Control in Stroke Patients, Characterized by Loss of Complexity

We study the mechanism of human arm-posture control by means of nonlinear dynamics and quantitative time series analysis methods. Utilizing linear and nonlinear measures in combination, we find that pathological tremors emerge in patient dynamics and serve as a main feature discriminating between normal and patient groups. The deterministic structure accompanied with loss of complexity inherent in the tremor dynamics is also revealed. To probe the underlying mechanism of the arm-posture dynamics, we further analyze the coupling patterns between joints and components, and discuss their roles in breaking of the organization structure. As a result, we elucidate the mechanisms in the arm-posture dynamics of normal subjects responding to the gravitational force and for the reduction of the dynamic degrees of freedom in the patient dynamics. This study provides an integrated framework for the origin of the loss of complexity in the dynamics of patients as well as the coupling structure in the arm-posture dynamics.

Spike shape analysis of electromyography for parkinsonian tremor evaluation

INTRODUCTION

Standard electromyography (EMG) parameters have limited utility for evaluation of Parkinson disease (PD) tremor. Spike shape analysis (SSA) EMG parameters are more sensitive than standard EMG parameters for studying motor control mechanisms in healthy subjects. SSA of EMG has not been used to assess parkinsonian tremor. This study assessed the utility of SSA and standard time and frequency analysis for electromyographic evaluation of PD-related resting tremor.

METHODS

We analyzed 1-s periods of EMG recordings to detect nontremor and tremor signals in relaxed biceps brachii muscle of seven mild to moderate PD patients.

RESULTS

SSA revealed higher mean spike amplitude, duration, and slope and lower mean spike frequency in tremor signals than in nontremor signals. Standard EMG parameters (root mean square, median, and mean frequency) did not show differences between the tremor and nontremor signals.

CONCLUSIONS

SSA of EMG data is a sensitive method for parkinsonian tremor evaluation.

Rethinking energy in parkinsonian motor symptoms: a potential role for neural metabolic deficits

Parkinson’s disease (PD) is characterized as a chronic and progressive neurodegenerative disorder that results in a variety of debilitating symptoms, including bradykinesia, resting tremor, rigidity, and postural instability. Research spanning several decades has emphasized basal ganglia dysfunction, predominantly resulting from dopaminergic (DA) cell loss, as the primarily cause of the aforementioned parkinsonian features. But, why those particular features manifest themselves remains an enigma. The goal of this paper is to develop a theoretical framework that parkinsonian motor features are behavioral consequence of a long-term adaptation to their inability (inflexibility or lack of capacity) to meet energetic demands, due to neural metabolic deficits arising from mitochondrial dysfunction associated with PD. Here, we discuss neurophysiological changes that are generally associated with PD, such as selective degeneration of DA neurons in the substantia nigra pars compacta (SNc), in conjunction with metabolic and mitochondrial dysfunction. We then characterize the cardinal motor symptoms of PD, bradykinesia, resting tremor, rigidity and gait disturbance, reviewing literature to demonstrate how these motor patterns are actually energy efficient from a metabolic perspective. We will also develop three testable hypotheses: (1) neural metabolic deficits precede the increased rate of neurodegeneration and onset of behavioral symptoms in PD; (2) motor behavior of persons with PD are more sensitive to changes in metabolic/bioenergetic state; and (3) improvement of metabolic function could lead to better motor performance in persons with PD. These hypotheses are designed to introduce a novel viewpoint that can elucidate the connections between metabolic, neural and motor function in PD.

Impact of Center-of-Mass Acceleration on the Performance of Ultramarathon Runners

Ultramarathon races are rapidly gaining popularity in several countries, raising interest for the improvement of training programs. The aim of this study was to use a triaxial accelerometer to compare the three-dimensional center-of-mass accelerations of two groups of ultramarathon runners with distinct performances during different running speeds and distances. Ten runners who participated in the 12-h Taipei International Ultramarathon Race underwent laboratory treadmill testing one month later. They were divided into an elite group (EG; n = 5) and a sub-elite group (SG; n = 5). The triaxial center-of-mass acceleration recorded during a level-surface progressive intensity running protocol (3, 6, 8, 9, 10, and 12 km/h; 5 min each) was used for correlation analyses with running distance during the ultramarathon. The EG showed negative correlations between mediolateral (ML) acceleration (r = −0.83 to −0.93, p < 0.05), and between anterior–posterior (AP) acceleration and running distance (r = −0.8953 to −0.9653, p < 0.05), but not for vertical control of the center of mass. This study suggests that runners reduce stride length to minimize mediolateral sway and the effects of braking on the trunk; moreover, cadence must be increased to reduce braking effects and enhance impetus. Consequently, the competition level of ultramarathons can be elevated.

Gaze and posture coordinate differently with the complexity of visual stimulus motion

In this study, we explored whether gaze and posture would exhibit coordination with the motion of a presented visual stimulus, specifically with regard to the complexity of the motion structure. Fourteen healthy adults viewed a set of four visual stimulus motion conditions, in both self-selected and semi-tandem stance, during which the stimulus moved horizontally across a screen, with position updated to follow a sine, chaos, surrogate, or random noise trajectory. Posture was measured using a standard force platform in self-selected and semi-tandem stance conditions while gaze was recorded using image-based eye-tracking equipment. Cross-correlation confirmed the continuous coordination of gaze with each type of stimulus motion, with increasing lag as stimulus motion complexity increased. Correlation dimension and approximate entropy were used to assess the complexity of the measured gaze and posture behaviors, with these values compared against those of the actual stimulus via ANOVA and dependent t tests. We found that gaze behavior was particularly sensitive to the complexity of the stimulus motion, according to both metrics. Posture seemed to be unaffected by stimulus motion viewing; however, different stance conditions did exhibit differences in posture metrics. Our results support an evolving understanding of how vision is used for determining perception and action.