Redefining Bradykinesia

Subtle bradykinesia features are easier to identify and more prevalent than questionable dystonia in essential tremor

Essential tremor (ET) is characterized by upper limbs action tremor, sometimes extending to other body parts. However, ET can present with additional neurological features known as "soft signs." These signs of uncertain clinical significance are not sufficient to suggest an alternative neurological diagnosis, and include, among others, questionable dystonia and subtle voluntary movement alterations, i.e., bradykinesia and related features. This study aimed to explore the prevalence and relationship between questionable dystonia and subtle bradykinesia features in ET. Forty ET patients were video-recorded during clinical examination. Five movement disorder experts reviewed the videos to identify soft motor signs, i.e., dystonia and movement alterations during finger-tapping namely, (i) bradykinesia (reduced velocity), (ii) dysrhythmia, and (iii) sequence effect. Inter-rater agreement was quantified using the Fleiss' Kappa index. Data analysis was performed using nonparametric tests. We found a fair inter-rater agreement for upper limb dystonia (Fleiss' K = 0.27). Inter-rater agreement was higher (moderate) for head dystonia (Fleiss' K = 0.49) and finger-tapping assessment (Fleiss' K = 0.45). Upper limb dystonia was identified in 70% of patients, head dystonia in 35%, and finger-tapping alterations (in variable combinations) were observed in 95% of individuals (P < 0.001 by Fisher's exact test), including subtle bradykinesia and related features. No significant concordance or correlation was found between the soft signs. Subtle bradykinesia and related features are the most easily identifiable and frequent soft signs in ET, appearing in a higher percentage of patients than subtle dystonia. These findings provide insights into the clinical and pathophysiological understanding of ET.

Validation of computer vision technology for analyzing bradykinesia in outpatient clinic videos of people with Parkinson's disease

BACKGROUND

Current diagnosis and monitoring of Parkinson's disease (PD) is based on subjective clinical assessments. Objective measures of motor functioning could support clinical acumen. Computer vision (CV) technology is a promising contactless technique but requires further validation.

AIM

To investigate the performance of CV analysis of clinic-based videos of finger-tapping. Our goals were (i) to distinguish PD from healthy controls (HC), when compared to human raters, (ii) to measure the severity of bradykinesia, and (iii) detect ON/OFF medication state.

METHODS

Videos of thirty-one persons with PD and forty-nine HC were collected during clinical outpatient visits. Videos were analysed using CV to produce speed, amplitude, rhythm and composite bradykinesia measures. All videos were independently rated by three raters using the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) and Modified Bradykinesia Rating Scale (MBRS). Twenty video pairs were conducted in ON and OFF states. Classification accuracy for PD/HC state and ON/OFF state were measured using the Area under Receiver Operating characteristic curve and a confusion matrix. CV and clinical measures were correlated using Spearman coefficients.

RESULTS

CV classified disease state with higher accuracy than clinical raters (91 % sensitivity; 97 % specificity). CV measures of bradykinesia correlated significantly with clinical ratings: R = 0.740 for MDS-UPDRS, 0.715 for MBRS speed, 0.714 for amplitude and 0.504 for rhythm. CV classified ON/OFF state as accurately as clinical raters.

DISCUSSION

CV can provide a valid, objective and contactless bradykinesia assessment based on clinically collected videos, which offers promise as a new clinical outcome, including in remote settings.

Tremor Is Highly Responsive to Levodopa in Advanced Parkinson's Disease

BACKGROUND

Tremor in Parkinson's disease (PD) is commonly regarded as less responsive to levodopa than bradykinesia and rigidity, with levodopa-resistant PD tremor considered relatively common.

OBJECTIVE

The aim was to assess the levodopa responsiveness of tremor, bradykinesia, and rigidity in a population with advanced PD.

METHODS

We performed a retrospective study of 526 people with PD screened for deep brain stimulation.

RESULTS

Levodopa's Cohen's d effect sizes were in the same order of magnitude for the 3 cardinal motor symptoms. Proportional improvement in tremor (86.8%) was higher than bradykinesia (45.7%) and rigidity (67.0%) (P < 0.0001). Full resolution was more frequent for tremor (67.9%) than for bradykinesia (0.4%) or rigidity (24.8%) (P < 0.0001). Levodopa-unresponsive tremor, defined as improvement less than 25%, was documented only in 4.0%, as opposed to 19.4% for bradykinesia and 9.8% for rigidity (P < 0.0001).

CONCLUSIONS

In advanced PD, tremor was more responsive to levodopa than bradykinesia and rigidity, and levodopa-unresponsive tremor was relatively rare.

Identification of electromyographic patterns of bradykinesia in patients with Parkinson's disease

Background

Parkinson's disease (PD) is a common neurodegenerative disease characterized by rest tremor, rigidity, and bradykinesia. Assessing the severity of these symptoms is typically done using the third part of the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS III), relying on subjective evaluations by neurologists, which may lead to challenges in result interpretation. To address this issue, incorporation of surface electromyography (sEMG) in diagnostics.

Objectives

The aim of the study is to search for specific sEMG patterns that allow assessing the severity of bradykinesia.

Method

This case-control study involved 8 patients with PD at Hoehn & Yahr stages 2-3, and 7 healthy volunteers. sEMG was measured while the subjects performed the "finger tapping" and "hand movements" tests of the MDS-UPDRS III. The tests were conducted both before and after levodopa intake to identify patterns indicating changes in motor functions. During the tests, we observed the peak activity of the sEMG signal, reflecting the moments of activation of individual muscle groups involved in the implementation of the movement. Peak activity was characterized by the total number of maximum sEMG signal extrema and the distance between them. The data were compared with the healthy group.

Results

Peak activity increased after levodopa intake, indicating a reduction in bradykinesia. This feature partially correlates with clinicians' assessments and enhances the similarity of predictions by the MDS-UPDRS III scoring model to physician scores.

Conclusions

The results show the effectiveness of using sEMG and the number of peaks corresponding to the moments of muscle activation to assess bradykinesia.

Integrating Big Data, Artificial Intelligence, and motion analysis for emerging precision medicine applications in Parkinson's Disease

One of the key challenges in Big Data for clinical research and healthcare is how to integrate new sources of data, whose relation to disease processes are often not well understood, with multiple classical clinical measurements that have been used by clinicians for years to describe disease processes and interpret therapeutic outcomes. Without such integration, even the most promising data from emerging technologies may have limited, if any, clinical utility. This paper presents an approach to address this challenge, illustrated through an example in Parkinson's Disease (PD) management. We show how data from various sensing sources can be integrated with traditional clinical measurements used in PD; furthermore, we show how leveraging Big Data frameworks, augmented by Artificial Intelligence (AI) algorithms, can distinctively enrich the data resources available to clinicians. We showcase the potential of this approach in a cohort of 50 PD patients who underwent both evaluations with an Integrated Motion Analysis Suite (IMAS) composed of a battery of multimodal, portable, and wearable sensors and traditional Unified Parkinson's Disease Rating Scale (UPDRS)-III evaluations. Through techniques including Principal Component Analysis (PCA), elastic net regression, and clustering analysis we demonstrate how this combined approach can be used to improve clinical motor assessments and to develop personalized treatments. The scalability of our approach enables systematic data generation and analysis on increasingly larger datasets, confirming the integration potential of IMAS, whose use in PD assessments is validated herein, within Big Data paradigms. Compared to existing approaches, our solution offers a more comprehensive, multi-dimensional view of patient data, enabling deeper clinical insights and greater potential for personalized treatment strategies. Additionally, we show how IMAS can be integrated into established clinical practices, facilitating its adoption in routine care and complementing emerging methods, for instance, non-invasive brain stimulation. Future work will aim to augment our data repositories with additional clinical data, such as imaging and biospecimen data, to further broaden and enhance these foundational methodologies, leveraging the full potential of Big Data and AI.

What the trained eye cannot see: Quantitative kinematics and machine learning detect movement deficits in early-stage Parkinson's disease from videos

BACKGROUND

Evaluation of disease severity in Parkinson's disease (PD) relies on motor symptoms quantification. However, during early-stage PD, these symptoms are subtle and difficult to quantify by experts, which might result in delayed diagnosis and suboptimal disease management.

OBJECTIVE

To evaluate the use of videos and machine learning (ML) for automatic quantification of motor symptoms in early-stage PD.

METHODS

We analyzed videos of three movement tasks-Finger Tapping, Hand Movement, and Leg Agility- from 26 aged-matched healthy controls and 31 early-stage PD patients. Utilizing ML algorithms for pose estimation we extracted kinematic features from these videos and trained three classification models based on left and right-side movements, and right/left symmetry. The models were trained to differentiate healthy controls from early-stage PD from videos.

RESULTS

Combining left side, right side, and symmetry features resulted in a PD detection accuracy of 79 % from Finger Tap videos, 75 % from Hand Movement videos, 79 % from Leg Agility videos, and 86 % when combining the three tasks using a soft voting approach. In contrast, the classification accuracy varied between 40 % and 72 % when the movement side or symmetry were not considered.

CONCLUSIONS

Our methodology effectively differentiated between early-stage PD and healthy controls using videos of standardized motor tasks by integrating kinematic analyses of left-side, right-side, and bilateral symmetry movements. These results demonstrate that ML can detect movement deficits in early-stage PD from videos. This technology is easy-to-use, highly scalable, and has the potential to improve the management and quantification of motor symptoms in early-stage PD.

Insight into the Relationship Between Motor and Cognitive Symptoms in Essential Tremor

Essential tremor (ET) is a heterogeneous disorder characterized by bilateral upper limbs action tremor and, possibly, neurological signs of uncertain significance, including voluntary movement abnormalities and cognitive disturbances, i.e., the so-called 'soft' signs configuring the ET-plus definition. While motor and cognitive disturbances often coexist in ET, their interrelationship remains largely unexplored. Here we aim to further investigate the relationship between motor symptoms, objectively assessed through kinematic analysis, and cognitive dysfunctions in ET. Seventy ET patients underwent clinical examination, as well as kinematic recordings of tremor and finger tapping and a thorough cognitive assessment. We then tested clinic-demographic and kinematic differences between patients with and without cognitive abnormalities, i.e., with mild cognitive impairment (MCI). Correlation analysis served to explore potential associations between kinematic and cognitive data. Forty-three ET patients (61.42%) had MCI. ET-MCI patients exhibited reduced movement velocity during finger tapping compared to those with normal cognition (p < 0.001). Lower movement velocity during finger tapping was associated with poorer cognitive performance. Namely, we observed a correlation between movement velocity and performance on the Babcock Story Immediate and Delayed Recall Test (r = 0.52 and r = 0.45, both p < 0.001), as well as the interference memory task at 10 and 30 s (r = 0.3, p = 0.008 and r = 0.2, p = 0.03). In this study, we have provided data for a better pathophysiological interpretation of motor and cognitive signs in ET, including the role played by the cerebellum or extra-cerebellar areas, which possibly underpin both signs.

The Role of Cerebellum and Basal Ganglia Functional Connectivity in Altered Voluntary Movement Execution in Essential Tremor

Substantial evidence highlights the role of the cerebellum in the pathophysiology of tremor in essential tremor (ET), although its potential involvement in altered movement execution in this condition remains unclear. This study aims to explore potential correlations between the cerebellum and basal ganglia functional connectivity and voluntary movement execution abnormalities in ET, objectively assessed with kinematic techniques. A total of 20 patients diagnosed with ET and 18 healthy subjects were enrolled in this study. Tremor and repetitive finger tapping were recorded using an optoelectronic kinematic system. All participants underwent comprehensive 3T-MRI examinations, including 3D-T1 and blood-oxygen-level dependent (BOLD) sequences during resting state. Morphometric analysis was conducted on the 3D-T1 images, while a seed-based analysis was performed to investigate the resting-state functional connectivity (rsFC) of dorsal and ventral portions of the dentate nucleus and the external and internal segments of the globus pallidus. Finally, potential correlations between rsFC alterations in patients and clinical as well as kinematic scores were assessed. Finger tapping movements were slower in ET than in healthy subjects. Compared to healthy subjects, patients with ET exhibited altered FC of both dentate and globus pallidus with cerebellar, basal ganglia, and cortical areas. Interestingly, both dentate and pallidal FC exhibited positive correlations with movement velocity in patients, differently from that we observed in healthy subjects, indicating the higher the FC, the faster the finger tapping. The findings of this study indicate the possible role of both cerebellum and basal ganglia in the pathophysiology of altered voluntary movement execution in patients with ET.

Neural correlates of bradykinesia in Parkinson's disease: a kinematic and functional MRI study

Bradykinesia is defined as a "complex" of motor alterations including decreased movement amplitude and/or speed and tendency to reduce them with movement repetition (sequence effect). This study aimed at investigating the neural and kinematic correlates of bradykinesia during hand-tapping in people with Parkinson's disease (pwPD) relative to healthy controls. Twenty-five pwPD and 25 age- and sex-matched healthy controls underwent brain functional MRI (fMRI) during a hand-tapping task: subjects alternatively opened and closed their right hand as fully and quickly as possible. Hand-tapping kinematic parameters were objectively measured during the fMRI task using an optical fibre glove. During the fMRI task, pwPD showed reduced hand-tapping amplitude (hypokinesia) and a greater sequence effect. PwPD relative to healthy controls showed a reduced activity of fronto-parietal areas, middle cingulum/supplementary motor area (SMA), parahippocampus, pallidum/thalamus and motor cerebellar areas. Moreover, pwPD showed an increased activity of brain cognitive areas such as superior temporal gyrus, posterior cingulum, and cerebellum crus I. The decreased activity of cerebellum IV-V-VI, vermis IV-V, inferior frontal gyrus, and cingulum/SMA correlated with hypokinesia and with the sequence effect. Interestingly, a reduced activity of areas involved in motor planning and timing correlated both with hypokinesia and with the sequence effect in pwPD. This study has the major strength of collecting objective motor parameters and brain activity simultaneously, providing a unique opportunity to investigate the neural correlates of the "bradykinesia complex".

Circular walking is useful for assessing the risk of falls in early progressive supranuclear palsy

BACKGROUND

Progressive supranuclear palsy (PSP) is characterized by early onset postural instability and frequent falls. Circular walking necessitates dynamic postural control, which is impaired in patients with PSP. We aimed to explore gait parameters associated with the risk of falls in patients with PSP, focusing on circular walking.

METHODS

Sixteen drug-naïve patients with PSP, 22 drug-naïve patients with Parkinson's disease (PD), and 23 healthy controls were enrolled. Stride lengths/velocities and their coefficients of variation (CV) during straight and circular walking (walking around a circle of 1-m diameter) were measured under single-task and cognitive dual-task conditions. Correlation analysis was performed between gait parameters and postural instability and gait difficulty (PIGD) motor subscores, representing the risk of falls.

RESULTS

Patients with PSP had significantly higher CVs of stride lengths/velocities during circular walking than those during straight walking, and the extent of exacerbation of CVs in patients with PSP was larger than that in patients with PD under single-task conditions. Stride lengths/velocities and their CVs were significantly correlated with PIGD motor subscores in patients with PSP only during single-task circular walking. In addition, patients with PSP showed progressive decrements of stride lengths/velocities over steps only during single-task circular walking.

CONCLUSIONS

Worse gait parameters during circular walking are associated with an increased risk of falls in patients with PSP. Circular walking is a challenging task to demand the compromised motor functions of patients with PSP, unmasking impaired postural control and manifesting sequence effect. Assessing circular walking is useful for evaluating the risk of falls in patients with early PSP.

Improving efficacy of repetitive transcranial magnetic stimulation for treatment of Parkinson disease gait disorders

Parkinson disease (PD) is a neurodegenerative disorder that causes motor and cognitive deficits, presenting complex challenges for therapeutic interventions. Repetitive transcranial magnetic stimulation (rTMS) is a type of neuromodulation that can produce plastic changes in neural activity. rTMS has been trialed as a therapy to treat motor and non-motor symptoms in persons with Parkinson disease (PwP), particularly treatment-refractory postural instability and gait difficulties such as Freezing of Gait (FoG), but clinical outcomes have been variable. We suggest improving rTMS neuromodulation therapy for balance and gait abnormalities in PwP by targeting brain regions in cognitive-motor control networks. rTMS studies in PwP often targeted motor targets such as the primary motor cortex (M1) or supplementary motor area (SMA), overlooking network interactions involved in posture-gait control disorders. We propose a shift in focus toward alternative stimulation targets in basal ganglia-cortex-cerebellum networks involved in posture-gait control, emphasizing the dorsolateral prefrontal cortex (dlPFC), cerebellum (CB), and posterior parietal cortex (PPC) as potential targets. rTMS might also be more effective if administered during behavioral tasks designed to activate posture-gait control networks during stimulation. Optimizing stimulation parameters such as dosage and frequency as used clinically for the treatment of depression may also be useful. A network-level perspective suggests new directions for exploring optimal rTMS targets and parameters to maximize neural plasticity to treat postural instabilities and gait difficulties in PwP.

Dysrhythmia as a prominent feature of Parkinson's disease: An app-based tapping test

INTRODUCTION

Smartphone applications (apps) are instruments that assist with objective measurements during the clinical assessment of patients with movement disorders. We aim to test the hypothesis that Parkinson's disease (PD) patients will exhibit an increase in tapping variability and a decrease in tapping speed over a one-year period, compared to healthy controls (HC).

METHODS

Data was prospectively collected from participants enrolled in our Cincinnati Cohort Biomarker Program, in 2021-2023. Participants diagnosed with PD and age-matched HC were examined over a one-year-interval with a tapping test performed with customized smartphone app. Tapping speed (taps/s), inter-tap intervals and variability (movement regularity), and sequence effect were measured.

RESULTS

We included 295 PD patients and 62 HC. At baseline, PD subjects showed higher inter-tap variability than HC (coefficient-of-variation-CV, 37 ms [22-64] vs 26 ms [8-51]) (p = 0.007). Conversely, there was no difference in inter-tap intervals (411 ms [199-593] in PD versus 478 ms [243-618] in HC) and tapping speed (3.42[2.70-4.76] taps/s in PD versus 3.21 taps/s [2.57-4.54] in HC) (p > 0.05). Only PD subjects (n = 135), at the one-year follow-up, showed a decreased tapping speed vs baseline (3.44 taps/s [2.86-4.81] versus 3.39 taps/s [2.58,4.30]) (p = 0.036), without significant changes in inter-tap variability (CV, 32 ms [18,55] baseline versus 34 ms [22,59] follow-up) (p = 0.142). No changes were found in HC at the one-year follow up (all p values>0.05).

CONCLUSIONS

Inter-tap variability (dysrhythmia) but no inter-tap intervals or tapping speed are reliably distinctive feature of an app-based bradykinesia assessment in PD.

Clinical and kinematic characterization of parkinsonian soft signs in essential tremor

BACKGROUND

Subtle parkinsonian signs, i.e., rest tremor and bradykinesia, are considered soft signs for defining essential tremor (ET) plus.

OBJECTIVES

Our study aimed to further characterize subtle parkinsonian signs in a relatively large sample of ET patients from a clinical and neurophysiological perspective.

METHODS

We employed clinical scales and kinematic techniques to assess a sample of 82 ET patients. Eighty healthy controls matched for gender and age were also included. The primary focus of our study was to conduct a comparative analysis of ET patients (without any soft signs) and ET-plus patients with rest tremor and/or bradykinesia. Additionally, we investigated the asymmetry and side concordance of these soft signs.

RESULTS

In ET-plus patients with parkinsonian soft signs (56.10% of the sample), rest tremor was clinically observed in 41.30% of cases, bradykinesia in 30.43%, and rest tremor plus bradykinesia in 28.26%. Patients with rest tremor had more severe and widespread action tremor than other patients. Furthermore, we observed a positive correlation between the amplitude of action and rest tremor. Most ET-plus patients had an asymmetry of rest tremor and bradykinesia. There was no side concordance between these soft signs, as confirmed through both clinical examination and kinematic evaluation.

CONCLUSIONS

Rest tremor and bradykinesia are frequently observed in ET and are often asymmetric but not concordant. Our findings provide a better insight into the phenomenology of ET and suggest that the parkinsonian soft signs (rest tremor and bradykinesia) in ET-plus may originate from distinct pathophysiological mechanisms.

Extrapyramidal System/Symptoms/Signs Should Be Retired

The term "extrapyramidal system/symptoms/signs" and the acronym "EPS" have been abundantly used in neurology and psychiatry literature for more than a century. However, EPS has been increasingly criticized, especially by movement disorder neurologists, for its lack of clinical, anatomical, and physiologic definition. Contrary to traditional assumptions, pyramidal and extrapyramidal systems are not mutually exclusive. The acronym EPS, commonly used to denote drug-induced movement disorders, lacks specificity in conveying the nature and severity of these and other movement disorders. Consequently, we propose that the term is retired from scientific literature and that clinicians use specific phenomenologic descriptors for the various hypokinetc and hyperkinetic movement disorders.

Why so slow? Models of parkinsonian bradykinesia

Bradykinesia, or slowness of movement, is a defining feature of Parkinson disease (PD) and a major contributor to the negative effects on quality of life associated with this disorder and related conditions. A dominant pathophysiological model of bradykinesia in PD has existed for approximately 30 years and has been the basis for the development of several therapeutic interventions, but accumulating evidence has made this model increasingly untenable. Although more recent models have been proposed, they also appear to be flawed. In this Perspective, I consider the leading prior models of bradykinesia in PD and argue that a more functionally related model is required, one that considers changes that disrupt the fundamental process of accurate information transmission. In doing so, I review emerging evidence of network level functional connectivity changes, information transfer dysfunction and potential motor code transmission error and present a novel model of bradykinesia in PD that incorporates this evidence. I hope that this model may reconcile inconsistencies in its predecessors and encourage further development of therapeutic interventions.

Distinguishing essential tremor from Parkinson's disease: clinical and experimental tools

INTRODUCTION

Essential tremor (ET) and Parkinson's disease (PD) are the most common causes of tremor and the most prevalent movement disorders, with overlapping clinical features that can lead to diagnostic challenges, especially in the early stages.

AREAS COVERED

In the present paper, the authors review the clinical and experimental studies and emphasized the major aspects to differentiate between ET and PD, with particular attention to cardinal phenomenological features of these two conditions. Ancillary and experimental techniques, including neurophysiology, neuroimaging, fluid biomarker evaluation, and innovative methods, are also discussed for their role in differential diagnosis between ET and PD. Special attention is given to investigations and tools applicable in the early stages of the diseases, when the differential diagnosis between the two conditions is more challenging. Furthermore, the authors discuss knowledge gaps and unsolved issues in the field.

EXPERT OPINION

Distinguishing ET and PD is crucial for prognostic purposes and appropriate treatment. Additionally, accurate diagnosis is critical for optimizing clinical and experimental research on pathophysiology and innovative therapies. In a few years, integrated technologies could enable accurate, reliable diagnosis from early disease stages or prodromal stages in at-risk populations, but further research combining different techniques is needed.

Differential Responses to Low- and High-Frequency Subthalamic Nucleus Deep Brain Stimulation on Sensor-Measured Components of Bradykinesia in Parkinson's Disease

INTRODUCTION

The current approach to assessing bradykinesia in Parkinson's Disease relies on the Unified Parkinson's Disease Rating Scale (UPDRS), which is a numeric scale. Inertial sensors offer the ability to probe subcomponents of bradykinesia: motor speed, amplitude, and rhythm. Thus, we sought to investigate the differential effects of high-frequency compared to low-frequency subthalamic nucleus (STN) deep brain stimulation (DBS) on these quantified facets of bradykinesia.

METHODS

We recruited advanced Parkinson's Disease subjects with a chronic bilateral subthalamic nucleus (STN) DBS implantation to a single-blind stimulation trial where each combination of medication state (OFF/ON), electrode contacts, and stimulation frequency (60 Hz/180 Hz) was assessed. The Kinesia One sensor system was used to measure upper limb bradykinesia. For each stimulation trial, subjects performed extremity motor tasks. Sensor data were recorded continuously. We identified STN DBS parameters that were associated with improved upper extremity bradykinesia symptoms using a mixed linear regression model.

RESULTS

We recruited 22 subjects (6 females) for this study. The 180 Hz STN DBS (compared to the 60 Hz STN DBS) and dopaminergic medications improved all subcomponents of upper extremity bradykinesia (motor speed, amplitude, and rhythm). For the motor rhythm subcomponent of bradykinesia, ventral contacts yielded improved symptom improvement compared to dorsal contacts.

CONCLUSION

The differential impact of high- and low-frequency STN DBS on the symptoms of bradykinesia may advise programming for these patients but warrants further investigation. Wearable sensors represent a valuable addition to the armamentarium that furthers our ability to conduct objective, quantitative clinical assessments.

Bradykinesia in dystonic hand tremor: kinematic analysis and clinical rating

Introduction

Bradykinesia is an essential diagnostic criterion for Parkinson's disease (PD) but is frequently observed in many non-parkinsonian movement disorders, complicating differential diagnosis, particularly in disorders featuring tremors. The presence of bradykinetic features in the subset of dystonic tremors (DT), either "pure" dystonic tremors or tremors associated with dystonia, remains currently unexplored. The aim of the current study was to evaluate upper limb bradykinesia in DT patients, comparing them with healthy controls (HC) and patients with PD by observing repetitive finger tapping (FT).

Methods

The protocol consisted of two main parts. Initially, the kinematic recording of repetitive FT was performed using optical hand tracking system (Leap Motion Controller). The values of amplitude, amplitude decrement, frequency, frequency decrement, speed, acceleration and number of halts of FT were calculated. Subsequently, three independent movement disorder specialists from different movement disorders centres, blinded to the diagnosis, rated the presence of FT bradykinesia based on video recordings.

Results

Thirty-six subjects participated in the study (12 DT, 12 HC and 12 early-stage PD). Kinematic analysis revealed no significant difference in the selected parameters of FT bradykinesia between DT patients and HC. In comparisons between DT and PD patients, PD patients exhibited bigger amplitude decrement and slower FT performance. In the blinded clinical assessment, bradykinesia was rated, on average, as being present in 41.6% of DT patients, 27.7% of HC, and 91.7% of PD patients. While overall inter-rater agreement was moderate, weak agreement was noted within the DT group.

Discussion

Clinical ratings indicated signs of bradykinesia in almost half of DT patients. The objective kinematic analysis confirmed comparable parameters between DT and HC individuals, with more pronounced abnormalities in PD across various kinematic parameters. Interpretation of bradykinesia signs in tremor patients with DT should be approached cautiously and objective motion analysis might complement the diagnostic process and serve as a decision support system in the choice of clinical entities.

Harnessing Voice Analysis and Machine Learning for Early Diagnosis of Parkinson's Disease: A Comparative Study Across Three Datasets

OBJECTIVE

This study evaluates the efficacy of voice analysis combined with machine learning (ML) techniques in enabling the diagnosis of Parkinson's disease (PD).

METHODS

Voice data, phonation of the vowel "a," from three distinct datasets (two from the University of California Irvine ML Repository and one from figshare) for 432 participants (278 PD patients) were analyzed. We employed four ML models-Artificial Neural Networks, Random Forest, Gradient Boosting (GB), and Support Vector Machine (SVM)-alongside two ensemble methods (soft voting classifier-Ensemble Voting Classifier and stacking method-Ensemble Stacking Model (ESM)). The models underwent 50 iterations of evaluation, involving various data splits and 10-fold cross-validation. Comparative analysis was done using one-way Analysis of Variance followed by Bonferroni posthoc corrections.

RESULTS

The ESM, SVM, and GB models emerged as the top performers, demonstrating superior performance across metrics, including accuracy, sensitivity, specificity, precision, F1 score, and area under the receiver operating characteristic curve (ROC AUC). Despite data heterogeneity and variable selection limitations, the models showed high values for all metrics.

CONCLUSIONS

ML integration with voice analysis, mainly through ESM, SVM, and GB, is promising for early PD diagnosis. Using multi-source data and a large sample size enhances our findings' validity, reliability, and generalizability.

SIGNIFICANCE

Integrating advanced ML techniques with voice analysis demonstrates substantial potential for improving early PD detection, offering valuable tools for speech-language pathologists (SLPs). These findings provide clinically relevant insights that can be applied within the scope of SLP practice to refine diagnostic processes and facilitate early intervention.

MocapMe: DeepLabCut-Enhanced Neural Network for Enhanced Markerless Stability in Sit-to-Stand Motion Capture

This study examined the efficacy of an optimized DeepLabCut (DLC) model in motion capture, with a particular focus on the sit-to-stand (STS) movement, which is crucial for assessing the functional capacity in elderly and postoperative patients. This research uniquely compared the performance of this optimized DLC model, which was trained using 'filtered' estimates from the widely used OpenPose (OP) model, thereby emphasizing computational effectiveness, motion-tracking precision, and enhanced stability in data capture. Utilizing a combination of smartphone-captured videos and specifically curated datasets, our methodological approach included data preparation, keypoint annotation, and extensive model training, with an emphasis on the flow of the optimized model. The findings demonstrate the superiority of the optimized DLC model in various aspects. It exhibited not only higher computational efficiency, with reduced processing times, but also greater precision and consistency in motion tracking thanks to the stability brought about by the meticulous selection of the OP data. This precision is vital for developing accurate biomechanical models for clinical interventions. Moreover, this study revealed that the optimized DLC maintained higher average confidence levels across datasets, indicating more reliable and accurate detection capabilities compared with standalone OP. The clinical relevance of these findings is profound. The optimized DLC model's efficiency and enhanced point estimation stability make it an invaluable tool in rehabilitation monitoring and patient assessments, potentially streamlining clinical workflows. This study suggests future research directions, including integrating the optimized DLC model with virtual reality environments for enhanced patient engagement and leveraging its improved data quality for predictive analytics in healthcare. Overall, the optimized DLC model emerged as a transformative tool for biomechanical analysis and physical rehabilitation, promising to enhance the quality of patient care and healthcare delivery efficiency.

Objective assessment of the effects of opicapone in Parkinson's disease through kinematic analysis

BACKGROUND

Opicapone (OPC) is a third-generation, selective peripheral COMT inhibitor that improves peripheral L-DOPA bioavailability and reduces OFF time and end-of-dose motor fluctuations in Parkinson's disease (PD) patients.

OBJECTIVES

In this study, we objectively assessed the effects of adding OPC to L-DOPA on bradykinesia in PD through kinematic analysis of finger movements.

METHODS

We enrolled 20 treated patients with PD and motor fluctuations. Patients underwent two experimental sessions (L-DOPA, L-DOPA + OPC), separated by at least 1 week. In each session, patients were clinically evaluated and underwent kinematic movement analysis of repetitive finger movements at four time points: (i) before their usual morning dose of L-DOPA (T0), (ii) 30 min (T1), (iii) 1 h and 30 min (T2), and (iv) 3 h and 30 min after the L-DOPA intake (T3).

RESULTS

Movement velocity and amplitude of finger movements were higher in PD patients during the session with OPC compared to the session without OPC at all the time points tested. Importantly, the variability of finger movement velocity and amplitude across T0-T3 was significantly lower in the L-DOPA + OPC than L-DOPA session.

CONCLUSIONS

This study is the first objective assessment of the effects of adding OPC to L-DOPA on bradykinesia in patients with PD and motor fluctuations. OPC, in addition to the standard dopaminergic therapy, leads to significant improvements in bradykinesia during clinically relevant periods associated with peripheral L-DOPA dynamics, i.e., the OFF state in the morning, delayed-ON, and wearing-OFF periods.

Noradrenergic alterations in Parkinson's disease: a combined 11C-yohimbine PET/neuromelanin MRI study

Degeneration of the noradrenergic system is now considered a pathological hallmark of Parkinson's disease, but little is known about its consequences in terms of parkinsonian manifestations. Here, we evaluated two aspects of the noradrenergic system using multimodal in vivo imaging in patients with Parkinson's disease and healthy controls: the pigmented cell bodies of the locus coeruleus with neuromelanin sensitive MRI; and the density of α2-adrenergic receptors (ARs) with PET using 11C-yohimbine. Thirty patients with Parkinson's disease and 30 age- and sex-matched healthy control subjects were included. The characteristics of the patients' symptoms were assessed using the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS). Patients showed reduced neuromelanin signal intensity in the locus coeruleus compared with controls and diminished 11C-yohimbine binding in widespread cortical regions, including the motor cortex, as well as in the insula, thalamus and putamen. Clinically, locus coeruleus neuronal loss was correlated with motor (bradykinesia, motor fluctuations, tremor) and non-motor (fatigue, apathy, constipation) symptoms. A reduction of α2-AR availability in the thalamus was associated with tremor, while a reduction in the putamen, the insula and the superior temporal gyrus was associated with anxiety. These results highlight a multifaceted alteration of the noradrenergic system in Parkinson's disease since locus coeruleus and α2-AR degeneration were found to be partly uncoupled. These findings raise important issues about noradrenergic dysfunction that may encourage the search for new drugs targeting this system, including α2-ARs, for the treatment of Parkinson's disease.

The sound of Parkinson's disease: A model of audible bradykinesia

INTRODUCTION

Evaluation of bradykinesia is based on five motor tasks from the MDS-UPDRS. Visually scoring these motor tasks is subjective, resulting in significant interrater variability. Recent observations suggest that it may be easier to hear the characteristic features of bradykinesia, such as the decrement in sound intensity or force of repetitive movements. The objective is to evaluate whether audio signals derived during four MDS-UPDRS tasks can be used to detect and grade bradykinesia, using two machine learning models.

METHODS

54 patients with Parkinson's disease and 28 healthy controls were filmed while executing the bradykinesia motor tasks. Several features were extracted from the audio signal, including number of taps, speed, sound intensity, decrement and freezes. For each motor task, two supervised machine learning models were trained, Logistic Regression (LR) and Support Vector Machine (SVM).

RESULTS

Both classifiers were able to separate patients from controls reasonably well for the leg agility task, area under the receiver operating characteristic curve (AUC): 0.92 (95%CI: 0.78-0.99) for LR and 0.93 (0.81-1.00) for SVM. Also, models were able to differentiate less severe bradykinesia from severe bradykinesia, particularly for the pronation-supination motor task, with AUC: 0.90 (0.62-1.00) for LR and 0.82 (0.45-0.97) for SVM.

CONCLUSION

This audio-based approach discriminates PD from healthy controls with moderate-high accuracy and separated individuals with less severe bradykinesia from those with severe bradykinesia. Sound analysis may contribute to the identification and monitoring of bradykinesia.

Interhemispheric imbalance and bradykinesia features in Parkinson's disease

In patients with Parkinson's disease, the connectivity between the two primary motor cortices may be altered. However, the correlation between asymmetries of abnormal interhemispheric connections and bradykinesia features has not been investigated. Furthermore, the potential effects of dopaminergic medications on this issue remain largely unclear. The aim of the present study is to investigate the interhemispheric connections in Parkinson's disease by transcranial magnetic stimulation and explore the potential relationship between interhemispheric inhibition and bradykinesia feature asymmetry in patients. Additionally, we examined the impact of dopaminergic therapy on neurophysiological and motor characteristics. Short- and long-latency interhemispheric inhibition was measured in 18 Parkinson's disease patients and 18 healthy controls, bilaterally. We also assessed the corticospinal and intracortical excitability of both primary motor cortices. We conducted an objective analysis of finger-tapping from both hands. Correlation analyses were performed to explore potential relationships among clinical, transcranial magnetic stimulation and kinematic data in patients. We found that short- and long-latency interhemispheric inhibition was reduced (less inhibition) from both hemispheres in patients than controls. Compared to controls, finger-tapping movements in patients were slower, more irregular, of smaller amplitudes and characterized by a progressive amplitude reduction during movement repetition (sequence effect). Among Parkinson's disease patients, the degree of short-latency interhemispheric inhibition imbalance towards the less affected primary motor cortex correlated with the global clinical motor scores, as well as with the sequence effect on the most affected hand. The greater the interhemispheric inhibition imbalance towards the less affected hemisphere (i.e. less inhibition from the less to the most affected primary motor cortex than that measured from the most to the less affected primary motor cortex), the more severe the bradykinesia in patients. In conclusion, the inhibitory connections between the two primary motor cortices in Parkinson's disease are reduced. The interhemispheric disinhibition of the primary motor cortex may have a role in the pathophysiology of specific bradykinesia features in patients, i.e. the sequence effect.

Identifying Subtle Motor Deficits Before Parkinson's Disease is Diagnosed: What to Look for?

Motor deficits typical of Parkinson's disease (PD), such as gait and balance disturbances, tremor, reduced arm swing and finger movement, and voice and breathing changes, are believed to manifest several years prior to clinical diagnosis. Here we describe the evidence for the presence and progression of motor deficits in this pre-diagnostic phase in order to provide suggestions for the design of future observational studies for an effective, quantitatively oriented investigation. On the one hand, these future studies must detect these motor deficits in as large (potentially, population-based) cohorts as possible with high sensitivity and specificity. On the other hand, they must describe the progression of these motor deficits in the pre-diagnostic phase as accurately as possible, to support the testing of the effect of pharmacological and non-pharmacological interventions. Digital technologies and artificial intelligence can substantially accelerate this process.

Subtle changes in central dopaminergic tone underlie bradykinesia in essential tremor

INTRODUCTION

In this research, our primary objective was to explore the correlation between basal ganglia dopaminergic neurotransmission, assessed using 123I-FP-CIT (DAT-SPECT), and finger movements abnormalities in patients with essential tremor (ET) and Parkinson's disease (PD).

METHODS

We enrolled 16 patients with ET, 17 with PD, and 18 healthy controls (HC). Each participant underwent comprehensive clinical evaluations, kinematic assessments of finger tapping. ET and PD patients underwent DAT-SPECT imaging. The DAT-SPECT scans were subjected to both visual and semi-quantitative analysis using DaTQUANT®. We then investigated the correlations between the clinical, kinematic, and DAT-SPECT data, in patients.

RESULTS

Our findings confirm that individuals with ET exhibited slower finger tapping than HC. Visual evaluation of radiotracer uptake in both striata demonstrated normal levels within the ET patient cohort, while PD patients displayed reduced uptake. However, there was notable heterogeneity in the quantification of uptake within the striata among ET patients. Additionally, we found a correlation between the amount of radiotracer uptake in the striatum and movement velocity during finger tapping in patients. Specifically, lower radioligand uptake corresponded to decreased movement velocity (ET: coef. = 0.53, p-adj = 0.03; PD: coef. = 0.59, p-adj = 0.01).

CONCLUSION

The study's findings suggest a potential link between subtle changes in central dopaminergic tone and altered voluntary movement execution, in ET. These results provide further insights into the pathophysiology of ET. However, longitudinal studies are essential to determine whether the slight reduction in dopaminergic tone observed in ET patients represents a distinct subtype of the disease or could serve as a predictor for the clinical progression into PD.

Parkinsonism in complex neurogenetic disorders: lessons from hereditary dementias, adult-onset ataxias and spastic paraplegias

Parkinsonism is a syndrome characterized by bradykinesia in combination with either rest tremor, rigidity, or both. These features are the cardinal manifestations of Parkinson's disease, the most common cause of parkinsonism, and atypical parkinsonian disorders. However, parkinsonism can be a manifestation of complex neurological and neurodegenerative genetically determined disorders, which have a vast and heterogeneous motor and non-motor phenotypic features. Hereditary dementias, adult-onset ataxias and spastic paraplegias represent only few of this vast group of neurogenetic diseases. This review will provide an overview of parkinsonism's clinical features within adult-onset neurogenetic diseases which a neurologist could face with. Understanding parkinsonism and its characteristics in the context of the aforementioned neurological conditions may provide insights into pathophysiological mechanisms and have important clinical implications, including diagnostic and therapeutic aspects.

Objective measurement versus clinician-based assessment for Parkinson's disease

INTRODUCTION

Although clinician-based assessment through standardized clinical rating scales is currently the gold standard for quantifying motor impairment in Parkinson's disease (PD), it is not without limitations, including intra- and inter-rater variability and a degree of approximation. There is increasing evidence supporting the use of objective motion analyses to complement clinician-based assessment. Objective measurement tools hold significant potential for improving the accuracy of clinical and research-based evaluations of patients.

AREAS COVERED

The authors provide several examples from the literature demonstrating how different motion measurement tools, including optoelectronics, contactless and wearable systems allow for both the objective quantification and monitoring of key motor symptoms (such as bradykinesia, rigidity, tremor, and gait disturbances), and the identification of motor fluctuations in PD patients. Furthermore, they discuss how, from a clinician's perspective, objective measurements can help in various stages of PD management.

EXPERT OPINION

In our opinion, sufficient evidence supports the assertion that objective monitoring systems enable accurate evaluation of motor symptoms and complications in PD. A range of devices can be utilized not only to support diagnosis but also to monitor motor symptom during the disease progression and can become relevant in the therapeutic decision-making process.

Exploring the Complex Phenotypes of Impaired Finger Dexterity in Mild-to-moderate Stage Parkinson's Disease: A Time-Series Analysis

BACKGROUND

Impaired dexterity is an early motor symptom in Parkinson's disease (PD) that significantly impacts the daily activity of patients; however, what constitutes complex dexterous movements remains controversial.

OBJECTIVE

To explore the characteristics of finger dexterity in mild-to-moderate stage PD.

METHODS

We quantitatively assessed finger dexterity in 48 mild-to-moderate stage PD patients and 49 age-matched controls using a simple alternating two-finger typing test for 15 seconds. Time-series analyses of various kinematic parameters with machine learning were compared between sides and groups.

RESULTS

Both the more and less affected hands of patients with PD had significantly lower typing frequency and slower typing velocity than the non-dominant and the dominant hands of controls (p = 0.019, p = 0.016, p < 0.001, p < 0.001). The slope of the typing velocity decreased with time, indicating a sequence effect in the PD group. A typing duration of 6 seconds was determined sufficient to discriminate PD patients from controls. Typing error, repetition, and repetition rate were significantly higher in the more affected hands of patients with PD than in the non-dominant hand of controls (p < 0.001, p = 0.03, p < 0.001). The error rate was constant, whereas the repetition rate was steep during the initiation of typing. A predictive model of the more affected hand demonstrated an accuracy of 70% in differentiating PD patients from controls.

CONCLUSION

Our study demonstrated complex components of impaired finger dexterity in mild-to-moderate stage PD, namely bradykinesia with sequence effects, error, and repetition at the initiation of movement, suggesting that multiple neural networks may be involved in dexterity deficits in PD.

May Bradykinesia Features Aid in Distinguishing Parkinson's Disease, Essential Tremor, And Healthy Elderly Individuals?

BACKGROUND

Bradykinesia is the hallmark feature of Parkinson's disease (PD); however, it can manifest in other conditions, including essential tremor (ET), and in healthy elderly individuals.

OBJECTIVE

Here we assessed whether bradykinesia features aid in distinguishing PD, ET, and healthy elderly individuals.

METHODS

We conducted simultaneous video and kinematic recordings of finger tapping in 44 PD patients, 69 ET patients, and 77 healthy elderly individuals. Videos were evaluated blindly by expert neurologists. Kinematic recordings were blindly analyzed. We calculated the inter-raters agreement and compared data among groups. Density plots assessed the overlapping in the distribution of kinematic data. Regression analyses and receiver operating characteristic curves determined how the kinematics influenced the likelihood of belonging to a clinical score category and diagnostic group.

RESULTS

The inter-rater agreement was fair (Fleiss K = 0.32). Rater found the highest clinical scores in PD, and higher scores in ET than healthy elderly individuals (p < 0.001). In regard to kinematic analysis, the groups showed variations in movement velocity, with PD presenting the slowest values and ET displaying less velocity than healthy elderly individuals (all ps < 0.001). Additionally, PD patients showed irregular rhythm and sequence effect. However, kinematic data significantly overlapped. Regression analyses showed that kinematic analysis had high specificity in differentiating between PD and healthy elderly individuals. Nonetheless, accuracy decreased when evaluating subjects with intermediate kinematic values, i.e., ET patients.

CONCLUSION

Despite a considerable degree of overlap, bradykinesia features vary to some extent in PD, ET, and healthy elderly individuals. Our findings have implications for defining bradykinesia and categorizing patients.