Bradykinesia In Parkinson's Disease Research Articles

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.

ATST-Net: A method to identify early symptoms in the upper and lower extremities of PD

Bradykinesia, a core symptom of motor disorders in Parkinson's disease (PD), is a major criterion for screening early PD patients in clinical practice. Currently, many studies have proposed automatic assessment schemes for bradykinesia in PD. However, existing schemes suffer from problems such as dependence on professional equipment, single evaluation tasks, difficulty in obtaining samples and low accuracy. This paper proposes a manual feature extraction- and neural network-based method to evaluate bradykinesia, effectively solving the problem of a small sample size. This method can automatically assess finger tapping (FT), hand movement (HM), toe tapping (TT) and bilateral foot sensitivity tasks (LA) through a unified model. Data were obtained from 120 individuals, including 93 patients with Parkinson's disease and 27 age- and sex-matched normal controls (NCs). Manual feature extraction and Attention Time Series Two-stream Networks (ATST-Net) were used for classification. Accuracy rates of 0.844, 0.819, 0.728, and 0.768 were achieved for FT, HM, TT, and LA, respectively. To our knowledge, this study is the first to simultaneously evaluate the upper and lower limbs using a unified model that has significant advantages in both model training and transfer learning.

A small-sample time-series signal augmentation and analysis method for quantitative assessment of bradykinesia in Parkinson's disease

Patients with Parkinson's disease (PD) usually have varying degrees of bradykinesia, and the current clinical assessment is mainly based on the Movement Disorder Society Unified PD Rating Scale, which can hardly meet the needs of objectivity and accuracy. Therefore, this paper proposed a small-sample time series classification method (DTW-TapNet) based on dynamic time warping (DTW) data augmentation and attentional prototype network. Firstly, for the problem of small sample sizes of clinical data, a DTW-based data merge method is used to achieve data augmentation. Then, the time series are dimensionally reorganized using random grouping, and convolutional operations are performed to learn features from multivariate time series. Further, attention mechanism and prototype learning are introduced to optimize the distance of the class prototype to which each time series belongs to train a low-dimensional feature representation of the time series, thus reducing the dependency on data volume. Clinical experiments were conducted to collect motion capture data of upper and lower limb movements from 36 patients with PD and eight healthy controls. For the upper limb movement data, the proposed method improved the classification accuracy, weighted precision, and kappa coefficient by 8.89%-15.56%, 9.22%-16.37%, and 0.13-0.23, respectively, compared with support vector machines, long short-term memory, and convolutional prototype network. For the lower limb movement data, the proposed method improved the classification accuracy, weighted precision, and kappa coefficient by 8.16%-20.41%, 10.01%-23.73%, and 0.12-0.28, respectively. The experiments and results show that the proposed method can objectively and accurately assess upper and lower limb bradykinesia in PD.

A Causality-Aware Graph Convolutional Network Framework for Rigidity Assessment in Parkinsonians.

Rigidity is one of the common motor disorders in Parkinson's disease (PD), which lead to life quality deterioration. The widely-used rating-scale-based approach for rigidity assessment still depends on the availability of experienced neurologists and is limited by rating subjectivity. Given the recent successful applications of quantitative susceptibility mapping (QSM) in auxiliary PD diagnosis, automated assessment of PD rigidity can be essentially achieved through QSM analysis. However, a major challenge is the performance instability due to the confounding factors (e.g., noise and distribution shift) which conceal the truly-causal features. Therefore, we propose a causality-aware graph convolutional network (GCN) framework, where causal feature selection is combined with causal invariance to ensure that causality-informed model decisions are reached. Firstly, a GCN model that integrates causal feature selection is systematically constructed at three graph levels: node, structure, and representation. In this model, a causal diagram is learned to extract a subgraph with truly-causal information. Secondly, a non-causal perturbation strategy is developed along with an invariance constraint to ensure the stability of the assessment results under different distributions, and thus avoid spurious correlations caused by distribution shifts. The superiority of the proposed method is shown by extensive experiments and the clinical value is revealed by the direct relevance of selected brain regions to rigidity in PD. Besides, its extensibility is verified on other two tasks: PD bradykinesia and mental state for Alzheimer's disease. Overall, we provide a clinically-potential tool for automated and stable assessment of PD rigidity. Our source code will be available at https://github.com/SJTUBME-QianLab/Causality-Aware-Rigidity.

Short-term plasticity of the motor cortex compensates for bradykinesia in Parkinson’s disease

Patients with Parkinson's disease (PD) show impaired short-term potentiation (STP) mechanisms in the primary motor cortex (M1). However, the role played by this neurophysiological abnormality in bradykinesia pathophysiology is unknown. In this study, we used a multimodal neuromodulation approach to test whether defective STP contributes to bradykinesia. We evaluated STP by measuring motor-evoked potential facilitation during 5 Hz-repetitive transcranial magnetic stimulation (rTMS) and assessed repetitive finger tapping movements through kinematic techniques. Also, we used transcranial alternating current stimulation (tACS) to drive M1 oscillations and experimentally modulate bradykinesia. STP was assessed during tACS delivered at beta (β) and gamma (γ) frequency, and during sham-tACS. Data were compared to those recorded in a group of healthy subjects. In PD, we found that STP was impaired during sham- and γ-tACS, while it was restored during β-tACS. Importantly, the degree of STP impairment was associated with the severity of movement slowness and amplitude reduction. Moreover, β-tACS-related improvements in STP were linked to changes in movement slowness and intracortical GABA-A-ergic inhibition during stimulation, as assessed by short-interval intracortical inhibition (SICI). Patients with prominent STP amelioration had greater SICI reduction (cortical disinhibition) and less slowness worsening during β-tACS. Dopaminergic medications did not modify β-tACS effects. These data demonstrate that abnormal STP processes are involved in bradykinesia pathophysiology and return to normal levels when β oscillations increase. STP changes are likely mediated by modifications in GABA-A-ergic intracortical circuits and may represent a compensatory mechanism against β-induced bradykinesia in PD.

Bradykinesia and Its Progression Are Related to Interhemispheric Beta Coherence.

Bradykinesia is the major cardinal motor sign of Parkinson disease (PD), but its neural underpinnings are unclear. The goal of this study was to examine whether changes in bradykinesia following long-term subthalamic nucleus (STN) deep brain stimulation (DBS) are linked to local STN beta (13-30 Hz) dynamics or a wider bilateral network dysfunction. Twenty-one individuals with PD implanted with sensing neurostimulators (Activa® PC + S, Medtronic, PLC) in the STN participated in a longitudinal 'washout' therapy study every three to 6 months for an average of 3 years. At each visit, participants were withdrawn from medication (12/24/48hours) and had DBS turned off (>60minutes) before completing a repetitive wrist-flexion extension task, a validated quantitative assessment of bradykinesia, while local field potentials were recorded. Local STN beta dynamics were investigated via beta power and burst duration, while interhemispheric beta synchrony was assessed with STN-STN beta coherence. Higher interhemispheric STN beta coherence, but not contralateral beta power or burst duration, was significantly associated with worse bradykinesia. Bradykinesia worsened off therapy over time. Interhemispheric STN-STN beta coherence also increased over time, whereas beta power and burst duration remained stable. The observed change in bradykinesia was related to the change in interhemispheric beta coherence, with greater increases in synchrony associated with further worsening of bradykinesia. Together, these findings implicate interhemispheric beta synchrony as a neural correlate of the progression of bradykinesia following chronic STN DBS. This could imply the existence of a pathological bilateral network contributing to bradykinesia in PD. ANN NEUROL 2023;93:1029-1039.

Kinect-based objective evaluation of bradykinesia in patients with Parkinson's disease.

To quantify bradykinesia in Parkinson's disease (PD) with a Kinect depth camera-based motion analysis system and to compare PD and healthy control (HC) subjects. Fifty PD patients and twenty-five HCs were recruited. The Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III) was used to evaluate the motor symptoms of PD. Kinematic features of five bradykinesia-related motor tasks were collected using Kinect depth camera. Then, kinematic features were correlated with the clinical scales and compared between groups. Significant correlations were found between kinematic features and clinical scales (P < 0.05). Compared with HCs, PD patients exhibited a significant decrease in the frequency of finger tapping (P < 0.001), hand movement (P < 0.001), hand pronation-supination movements (P = 0.005), and leg agility (P = 0.003). Meanwhile, PD patients had a significant decrease in the speed of hand movements (P = 0.003) and toe tapping (P < 0.001) compared with HCs. Several kinematic features exhibited potential diagnostic value in distinguishing PD from HCs with area under the curve (AUC) ranging from 0.684-0.894 (P < 0.05). Furthermore, the combination of motor tasks exhibited the best diagnostic value with the highest AUC of 0.955 (95% CI = 0.913-0.997, P < 0.001). The Kinect-based motion analysis system can be applied to evaluate bradykinesia in PD. Kinematic features can be used to differentiate PD patients from HCs and combining kinematic features from different motor tasks can significantly improve the diagnostic value.

A tree-structure-guided graph convolutional network with contrastive learning for the assessment of parkinsonian hand movements.

Bradykinesia is one of the core motor symptoms of Parkinson's disease (PD). Neurologists typically perform face-to-face bradykinesia assessment in PD patients according to the Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS). As this human-expert assessment lacks objectivity and consistency, an automated and objective assessment scheme for bradykinesia is critically needed. In this paper, we propose a tree-structure-guided graph convolutional network with contrastive learning scheme to solve the challenge of difficulty in fine-grained feature extraction and insufficient model stability, finally achieving the video-based automated assessment of Parkinsonian hand movements, which represent a vital MDS-UPDRS component for examining upper-limb bradykinesia. Specifically, a tri-directional skeleton tree scheme is proposed to achieve effective fine-grained modeling of spatial hand dependencies. In this scheme, hand skeletons are extracted from videos, and then the spatial structures of these skeletons are constructed through depth-first tree traversal. Afterwards, a tree max-pooling module is employed to establish remote exchange between outer and inner nodes, hierarchically gather the most salient motion features, and hence achieve fine-grained mining. Finally, a group-sparsity-induced momentum contrast is also developed to learn similar motion patterns under different interference through contrastive learning. This can promote stable learning of discriminative spatial-temporal features with invariant motion semantics. Comprehensive experiments on a large clinical video dataset reveal that our method achieves competitive results, and outperforms other sensor-based and RGB-depth methods. The proposed method leads to accurate assessment of PD bradykinesia through videos collected by low-cost consumer cameras of limited capabilities. Hence, our work provides a convenient tool for PD telemedicine applications with modest hardware requirements.

Pharmacological actions of a novel and highly selective D3 dopamine receptor agonist, ML417, in a rodent model of Parkinson’s disease

Since its first use in treating Parkinson’s disease (PD), L‐DOPA has remained the gold standard of therapy for this disorder, defined by the progressive degeneration of dopaminergic neurons in the CNS leading to profound bradykinesia and tremor. The efficacy of L‐DOPA wanes over time and is associated with increasing side effects, including motor fluctuations and dyskinesias. Several dopaminergic agonists have also been introduced to treat PD, including pramipexole and ropinirole, which exhibit fewer motor side effects but are associated with impulse control disorders such as excessive gambling and hypersexuality. Notably, the dopamine receptor subtype(s) mediating the therapeutic actions and/or side effects in PD therapy remain unknown. However, the preference of pramipexole and ropinirole for the D3 dopamine receptor (D3R) suggests the involvement of this subtype, although these drugs also activate the D2R at therapeutic doses. Importantly, no drug currently employed to treat PD alters the course of the disease and the discovery of neuroprotective agents remain an unmet need in PD therapeutics. Recently, we discovered a novel, potent and highly selective agonist for the D3R, ML417, that is brain penetrant and was found to protect against 6‐OHDA‐induced neurodegeneration of dopaminergic neurons (Moritz et al., J. Med. Chem. 63: 5526, 2020). In the current study, we used ML417 to probe the role of the D3R in a rat model of PD. We initially sought to investigate the role of the D3R in ameliorating bradykinesia in a hemi‐parkinsonian rat model induced by 6‐OHDA infusion into the medial forebrain bundle. Using a validated cylindrical treadmill test of locomotion, doses of ML417 up to 20 mg/kg had no effect on improving impairments in walking as assessed by step counts in the hemi‐parkinsonian rats. In contrast, administration of L‐DOPA (6 mg/kg) significantly improves locomotion in the same model. Further, pretreatment with a D3R‐selective antagonist, SB277011A (30 mg/kg), did not attenuate the effects of L‐DOPA in reducing bradykinesia. These results suggest that the D3R does not mediate the anti‐bradykinetic effects of current PD therapeutics. However, we hypothesize that D3R stimulation may be beneficial for the treatment of L‐DOPA‐induced dyskinesias (LIDs) in PD. To test this, we used a chronic L‐DOPA administration paradigm (12 mg/kg/day for 7 days) to induce dyskinesias in the hemi‐parkinsonian rats. Subsequently, the effects of ML417 and SB277011A were assessed in these animals using an abnormal involuntary movement (AIMs) scoring method. Pretreatment with a single dose of ML417 (20 mg/kg) significantly reduced the intensity and duration of dyskinesias promoted with a single dose of L‐DOPA (6 mg/kg). Further, co‐administration of SB277011A (30 mg/kg) with ML417 attenuated the anti‐dyskinetic effects of ML417, suggesting that the benefit is D3R‐mediated. Overall, this study implies that D3R stimulation has no therapeutic effect on bradykinesia in PD, however, it may be beneficial in treating dyskinesias arising from L‐DOPA therapy.

Frequency of hand movements as a possible diagnostic tool for parkinsonian bradykinesia. Proposal of a simple bedside test.

Bradykinesia, dysrhythmia, and decrement in hand movements (HM) are core symptoms of Parkinson's disease (PD). The maximal rate of repetitive rhythm-preserving HM can be a diagnostic tool for PD bradykinesia. To improve the clinical diagnosis of bradykinesia by identifying the frequencies at which rhythmic HM become irregular in PD patients compared to healthy age-matched controls. Forty PD patients and 16 controls were asked to alternately perform left and right hand movements following the rate of a metronome with sound stimulation beginning at 85 beats per minute (BPM) and increasing in increments of 15 BPM up to 355 BPM. The rhythm of the HM for each rate was assessed visually, and the threshold frequency at which the subject could no longer rhythmically continue HM was measured by the metronome. The increasing rates of HM until reaching that threshold were compared between patients with PD and controls. The mean rates of a metronome in PD vs. healthy subjects were 173.3 ± 42.0 vs. 248.8 ± 48.5 BPM (p < 0.001) and 164.8 ± 34.2 vs. 241.2 ± 40.1 BPM (p < 0.001) for the dominant and non-dominant hands, respectively. The areas under the ROC curve were 0.929 [95%CI: (0.86-0.99)] for the dominant hand and 0.947 [95%CI: (0.88-1.0)] for the non-dominant hand. The BMP score cut-off value was 208 (sensitivity 72.7%, specificity 100%) for the dominant hand and 206 (sensitivity 87.5%, specificity 95%) for the non-dominant hand. The proposed test quantified the frequencies of rhythmic HMs in PD patients vs. controls and improved the diagnosis of bradykinesia in PD patients.

Intraoperative Quantitative Measurements for Bradykinesia Evaluation during Deep Brain Stimulation Surgery Using Leap Motion Controller: A Pilot Study.

Deep brain stimulation (DBS) has shown a remarkably high effectiveness for Parkinson's disease (PD). In many PD patients during DBS surgery, the therapeutic effects of the stimulation test are estimated by assessing changes in bradykinesia as the stimulation voltage is increased. In this study, we evaluated the potential of the leap motion controller (LMC) to quantify the motor component of bradykinesia in PD during DBS surgery, as this could make the intraoperative assessment of bradykinesia more accurate. Seven participants with idiopathic PD receiving chronic bilateral subthalamic nucleus deep brain stimulation (DBS) therapy were recruited. The motor tasks of finger tapping (FT), hand opening and closing (OC), and hand pronation and supination (PS) were selected pre- and intraoperatively in accordance with the Movement Disorder Society revision of the Unified Parkinson's Disease Rating Scale. During the test, participants performed these tasks in sequence while being simultaneously monitored by the LMC and two professional clinicians. Key kinematic parameters differed between the preoperative and intraoperative conditions. We suggest that the average velocity () and average amplitude () of PS isolate the bradykinetic feature from that movement to provide a measure of the intraoperative state of the motor system. The LMC achieved promising results in evaluating PD patients' hand and finger bradykinesia during DBS surgery.

Instrumental analysis of finger tapping reveals a novel early biomarker of parkinsonism in idiopathic rapid eye movement sleep behaviour disorder

BackgroundIdiopathic rapid eye movement sleep behaviour (iRBD) is considered as a risk factor for Parkinson's disease (PD) development. Evaluation of repetitive movements with finger tapping, which serves as a principal task to measure the extent of bradykinesia in PD, may undercover potential PD patients. The aim of this study was to explore whether finger tapping abnormalities, evaluated with a 3D motion capture system, are already present in RBD patients. MethodsFinger tapping data was acquired using a contactless 3D motion capture system from 40 RBD subjects and compared to 25 de-novo PD patients and 25 healthy controls. Objective assessment of amplitude decrement, maximum opening velocity and their combination representing finger tapping decrement was performed in the sequence of the first ten tapping movements. The association between instrumental finger tapping data and semi-quantitative clinical evaluation was analyzed. ResultsWhile significant differences between PD and controls were found for all investigated finger tapping measures (p < 0.002), RBD differed from controls in finger tapping amplitude (p = 0.004) and velocity (p = 0.007) decrement but not in maximal opening velocity. A significant relationship between the motor score from the Movement Disorders Society - Unified Parkinson's Disease Rating Scale and finger tapping decrement was shown for both patient groups, ie RBD (r = 0.36, p = 0.02) and PD (r = 0.60, p = 0.002). ConclusionsIn our group of RBD patients we demonstrated amplitude decrement of repetitive movements, which may correspond with prodromal bradykinesia. Our findings suggest instrumental analysis of finger tapping abnormalities as a potential novel clinical marker reflecting subclinical motor disturbances in RBD.

Bradykinesia Is Driven by Cumulative Beta Power During Continuous Movement and Alleviated by Gabaergic Modulation in Parkinson's Disease.

Spontaneous and “event-related” motor cortex oscillations in the beta (15–30 Hz) frequency range are well-established phenomena. However, the precise functional significance of these features is uncertain. An understanding of the specific function is of importance for the treatment of Parkinson's disease (PD), where attenuation of augmented beta throughout the motor network coincides with functional improvement. Previous research using a discrete movement task identified normalization of elevated spontaneous beta and postmovement beta rebound following GABAergic modulation. Here, we explore the effects of the gamma-aminobutyric acid type A modulator, zolpidem, on beta power during the performance of serial movement in 17 (15M, 2F; mean age, 66 ± 6.3 years) PD patients, using a repeated-measures, double-blinded, randomized, placebo-control design. Motor symptoms were monitored before and after treatment, using time-based Unified Parkinson's Disease Rating Scale measurements and beta oscillations in primary motor cortex (M1) were measured during a serial-movement task, using magnetoencephalography. We demonstrate that a cumulative increase in M1 beta power during a 10-s tapping trial is reduced following zolpidem, but not placebo, which is accompanied by an improvement in movement speed and efficacy. This work provides a clear mechanism for the generation of abnormally elevated beta power in PD and demonstrates that perimovement beta accumulation drives the slowing, and impaired initiation, of movement. These findings further indicate a role for GABAergic modulation in bradykinesia in PD, which merits further exploration as a therapeutic target.

Research Progress on Evaluation Method of Parkinson's Disease Bradykinesia Detection Based on Wearable Device

Parkinson's Disease (PD) is a neurodegenerative disease that occurs in the middle-aged and elderly population and has dyskinesia as the main clinical symptom. Bradykinesia is a typical dyskinesia symptom of Parkinson's disease. The evaluation of bradykinesia based on wearable devices is an important support for individualized diagnosis and telemedicine. This paper focuses on the bradykinesia, expound the existing detection and evaluation techniques for wearable devices and data analysis methods. This paper also analyzes and discusses some current problems in the field and future research directions.

Quantitative Analysis of Bradykinesia and Rigidity in Parkinson's Disease.

In the last decades, several studies showed that wearable sensors, used for assessing Parkinson's disease (PD) motor symptoms and recording their fluctuations, could provide a quantitative and reliable tool for patient's motor performance monitoring. The aim of this study is to make a step forward the capability of quantitatively describing PD motor symptoms. The specific aims are: identify the most sensible place where to locate sensors to monitor PD bradykinesia and rigidity, and identify objective indexes able to discriminate PD OFF/ON motor status, and PD patients from healthy subjects (HSs). Fourteen PD patients (H&Y stage 1-2.5), and 13 age-matched HSs, were enrolled. Five magneto-inertial wearable sensors, placed on index finger, thumb, metacarpus, wrist, and arm, were used as motion tracking systems. Sensors were placed on the most affected arm of PD patients, and on dominant hand of HS. Three UPDRS part III tasks were evaluated: rigidity (task 22), finger tapping (task 23), and prono-supination movements of the hands (task 25). A movement disorders expert rated the three tasks according to the UPDRS part III scoring system. In order to describe each task, different kinematic indexes from sensors were extracted and analyzed. Four kinematic indexes were extracted: fatigability; total time; total power; smoothness. The last three well-described PD OFF/ON motor status, during finger-tapping task, with an index finger sensor. During prono-supination task, wrist sensor was able to differentiate PD OFF/ON motor condition. Smoothness index, used as a rigidity descriptor, provided a good discrimination of the PD OFF/ON motor status. Total power index, showed the best accuracy for PD vs healthy discrimination, with any sensor location among index finger, thumb, metacarpus, and wrist. The present study shows that, in order to better describe the kinematic features of Parkinsonian movements, wearable sensors should be placed on a distal location on upper limb, on index finger or wrist. The proposed indexes demonstrated a good correlation with clinical scores, thus providing a quantitative tool for research purposes in future studies in this field.

Levodopa-Induced Changes in Electromyographic Patterns in Patients with Advanced Parkinson’s Disease

Levodopa medication is the most efficient treatment for motor symptoms of Parkinson’s disease (PD). Levodopa significantly alleviates rigidity, rest tremor, and bradykinesia in PD. The severity of motor symptoms can be graded with UPDRS-III scale. Levodopa challenge test is routinely used to assess patients’ eligibility to deep-brain stimulation (DBS) in PD. Feasible and objective measurements to assess motor symptoms of PD during levodopa challenge test would be helpful in unifying the treatment. Twelve patients with advanced PD who were candidates for DBS treatment were recruited to the study. Measurements were done in four phases before and after levodopa challenge test. Rest tremor and rigidity were evaluated using UPDRS-III score. Electromyographic (EMG) signals from biceps brachii and kinematic signals from forearm were recorded with wireless measurement setup. The patients performed two different tasks: arm isometric tension and arm passive flexion–extension. The electromyographic and the kinematic signals were analyzed with parametric, principal component, and spectrum-based approaches. The principal component approach for isometric tension EMG signals showed significant decline in characteristics related to PD during levodopa challenge test. The spectral approach on passive flexion–extension EMG signals showed a significant decrease on involuntary muscle activity during the levodopa challenge test. Both effects were stronger during the levodopa challenge test compared to that of patients’ personal medication. There were no significant changes in the parametric approach for EMG and kinematic signals during the measurement. The results show that a wireless and wearable measurement and analysis can be used to study the effect of levodopa medication in advanced Parkinson’s disease.

App-Based Bradykinesia Tasks for Clinic and Home Assessment in Parkinson's Disease: Reliability and Responsiveness.

Clinical rating of bradykinesia in Parkinson disease (PD) is challenging as it must combine several movement features into a single score. Additionally, in-clinic assessment cannot capture fluctuations throughout the day. To evaluate the reliability and responsiveness of a motion sensor-based tablet app for objective bradykinesia assessment in clinic and at home as compared to clinical ratings. Thirty-two PD patients treated with subthalamic deep brain stimulation (DBS) were outfitted with a motion sensor on the index finger of the more affected hand to perform two repetitions of finger-tapping, hand opening-closing, and arm pronation-supination tasks with DBS on and 10, 20, and 30 minutes after turning DBS off. Tasks were videotaped for blinded clinician rating using the Modified Bradykinesia Rating Scale (MBRS). Participants were then sent home with an app-based system to perform two repetitions of the same tasks six times per day spaced two hours apart, three days per week, for two weeks. Intraclass correlation (ICC) and minimal detectable change (MDC) were calculated. As the effects of DBS wore off, motion sensors detected worsening of amplitude sooner than did clinician-rated MBRS for all three tasks. ICCs were significantly higher and MDCs were significantly lower for motion sensors in the clinic and at home than for clinician ratings (p < 0.01). The tablet-based app demonstrated higher reliability and responsiveness in capturing bradykinesia-related tasks in the clinic and at home than did clinician ratings. This tool may enhance the assessment of novel therapies.

Objective Assessment of Bradykinesia Estimated from the Wrist Extension in Older Adults and Patients with Parkinson's Disease.

Parkinson's disease (PD) presents several motor signs, including tremor and bradykinesia. However, these signs can also be found in other motor disorders and in neurologically healthy older adults. The incidence of bradykinesia in PD is relatively high in all stages of the disorder, even when compared to tremor. Thus, this research proposes an objective assessment of bradykinesia in patients with PD (G PD: 15 older adults with Parkinson's disease, 65.3±9.1years) and older adults (G HV: 12 healthy older adults, 60.1±6.1years). The severity of bradykinesia in the participants of G PD was assessed using the Unified Parkinson's Disease Rating Scale. Movement and muscular activity were detected by means of inertial (accelerometer, gyroscope, magnetometer) and electromyographic sensors while the participants performed wrist extension against gravity with the forearm on pronation. Mean and standard error of inertial and electromyographic signal parameters could discriminate PD patients from healthy older adults (p value <0.05). In discriminating patients with PD from healthy older adults, the mean sensitivity and specificity were respectively 86.67 and 83.33%. The discrimination between the groups, based on the objective evaluation of bradykinesia, may contribute to the accurate diagnosis of PD and to the monitoring of therapies to control parkinsonian bradykinesia, and opens the possibility for further comparative studies considering individuals suffering from other motor disorders.

Quantitative Assessment of the Arm/Hand Movements in Parkinson's Disease Using a Wireless Armband Device.

We present an approach for quantitative assessment of the arm/hand movements in patients with Parkinson’s disease (PD), from sensor data acquired with a wearable, wireless armband device (Myo sensor). We propose new Movement Performance Indicators that can be adopted by practitioners for the quantitative evaluation of motor performance and support their clinical evaluations. In addition, specific Movement Performance Indicators can indicate the presence of the bradykinesia symptom. The study includes seventeen PD patients and sixteen age-matched controls. A set of representative arm/hand movements is defined under the supervision of movement disorder specialist. In order to assist the evaluations, and for progress monitoring purposes, as well as for assessing the amount of bradykinesia in PD, a total set of 84 Movement Performance Indicators are computed from the sensor readings. Subsequently, we investigate whether wireless armband device, with the use of the proposed Movement Performance Indicators can be utilized: (1) for objective and precise quantitative evaluation of the arm/hand movements of Parkinson’s patients, (2) for assessment of the bradykinesia motor symptom, and (3) as an adequate low-cost alternative for the sensor glove. We conducted extensive analysis of proposed Movement Performance Indicators and results are indicating following clinically relevant characteristics: (i) adequate reliability as measured by ICC; (ii) high accuracy in discrimination between the patients and controls, and between the disease stages (support to disease diagnosis and progress monitoring, respectively); (iii) substantial difference in comparison between the left-hand and the right-hand movements across controls and patients, as well as between disease stage groups; (iv) statistically significant correlation with clinical scales (tapping test and UPDRS-III Motor Score); and (v) quantitative evaluation of bradykinesia symptom. Results suggest that the proposed approach has a potential to be adopted by physicians, to afford them with quantitative, objective and precise methods and data during clinical evaluations and support the assessment of bradykinesia.

Progressive resistance exercise restores some properties of the triphasic EMG pattern and improves bradykinesia: the PRET-PD randomized clinical trial.

In Parkinson's disease (PD), the characteristic triphasic agonist and antagonist muscle activation pattern during ballistic movement is impaired: the number of agonist muscle bursts is increased, and the amplitudes of the agonist and antagonist bursts are reduced. The breakdown of the triphasic electromyographic (EMG) pattern has been hypothesized to underlie bradykinesia in PD. Progressive resistance exercise has been shown to improve clinical measures of bradykinesia, but it is not clear whether the benefits for bradykinesia are accompanied by changes in agonist and antagonist muscle activity. This study examined the spatiotemporal changes in agonist and antagonist muscle activity following 24 mo of progressive resistance exercise and the combined relationship between spatiotemporal muscle activity and strength measures and upper limb bradykinesia. We compared the effects of progressive resistance exercise training (PRET) with a nonprogressive exercise intervention, modified Fitness Counts (mFC), in patients with PD. We randomized 48 participants with mild-to-moderate PD to mFC or PRET. At the study endpoint of 24 mo, participants randomized to PRET compared with mFC had significantly faster movement velocity, accompanied by significant increases in the duration, magnitude, and magnitude normalized to duration of the 1st agonist burst and fewer number of agonist bursts before peak velocity. The antagonist muscle activity was increased relative to baseline but did not differ between groups. Spatiotemporal EMG muscle activity and muscle strength were significantly associated with upper limb bradykinesia. These findings demonstrate that progressive resistance exercise improves upper limb movement velocity and restores some aspects of the triphasic EMG pattern.