Interactions of motor and non-motor symptoms in Parkinson's disease

Parkinson’s disease (PD) is characterized by motor dysfunction and multiple non-motor symptoms. Though motor/non-motor interactions are common, the lines of research focusing on motor and non-motor symptoms mainly remain separate. The present studies assessed interactions between several motor aspects of PD (impaired gait, side of motor-symptom onset, tremor, motor-symptom severity) and non-motor symptoms (cognition, anxiety, self-perceived stigma) in non-demented individuals with idiopathic PD. Study 1 examined cognitive and motor performance during dual tasking, specifically executive function while walking. The impact of dual tasking on walking (speed, stride frequency) was greater for PD (N=19) than NC participants (N=13). The PD group had fewer set-shifts than NC on dual tasking, and demonstrated greater cognitive variability on dual tasking. Study 2 considered mechanisms of visuospatial dysfunction in PD (N=79) by assessing how side of motor-symptom onset (left versus right) and cognition (attention, executive function) affect spatial judgment on a dynamic line bisection task. In contrast to a rightward-biased parietal-neglect pattern, the PD group showed a leftward bias that occurred when attention was directed to the left side of space, regardless of side of onset. The extent and variability of bias correlated with frontally-mediated neuropsychological performance for PD but not NC (N=67). Both results suggested frontal-attentional rather than parietal-neglect mechanisms of spatial bias. Study 3 assessed how motor symptoms contribute to self-reported anxiety on the Beck Anxiety Inventory (BAI). Factor analysis identified a five-item PD motor factor, which correlated with motor-symptom severity and mediated the difference on BAI total scores between PD (N=100) and NC (N=74). Removal of the motor-factor items (e.g., “hands trembling”) significantly reduced BAI scores for PD relative to NC and reduced the size of the correlation between the BAI and motor-symptom severity. Study 4 examined the contributions of motor and non-motor symptoms to self-perceived stigma in PD (N=362). Contrary to expectations, perceived stigma was not predicted by motor symptoms but rather by depression and, for men only, by younger age. These studies provide insight into interactions that occur between motor and non-motor symptoms in PD in multiple aspects of daily function, highlighting potential avenues for future research and intervention

Spatial judgment in Parkinson's disease: Contributions of attentional and executive dysfunction

Spatial judgment is impaired in Parkinson's disease (PD), with previous research suggesting that disruptions in attention and executive function are likely contributors. If judgment of center places demands on frontal systems, performance on tests of attention/executive function may correlate with extent of bias in PD, and attentional disturbance may predict inconsistency in spatial judgment. The relation of spatial judgment to attention/executive function may differ for those with left-side versus right-side motor onset (LPD, RPD), reflecting effects of attentional lateralization. We assessed 42 RPD, 37 LPD, and 67 healthy control participants with a Landmark task (LM) in which a cursor moved horizontally from the right (right-LM) or left (left-LM). The task was to judge the center of the line. Participants also performed neuropsychological tests of attention and executive function. LM group differences were found on left-LM only, with both PD subgroups biased leftward of the control group (RPD p < .05; LPD p < .01; no RPD-LPD difference). For left-LM trials, extent of bias significantly correlated with performance on the cognitive tasks for PD but not for the control group. PD showed greater variability in perceived center than the control group; this variability correlated with performance on the cognitive tasks. The correlations between performance on the test of spatial judgment and the tests of attention/executive function suggest that frontal-based attentional dysfunction affects dynamic spatial judgment, both in extent of spatial bias and in consistency of response as indexed by intertrial variability. (PsycINFO Database Record (c) 2019 APA, all rights reserved).R01 NS067128 - NINDS NIH HHS; R21 NS043730 - NINDS NIH HHS; National Institute of Neurological Disorders and Stroke; American Parkinson's Disease Association; Massachusetts ChapterAccepted manuscrip

Executive control of walking in people with Parkinson’s disease with freezing of gait

Background: Walking abnormalities in people with Parkinson’s disease (PD) are characterized by a shift in locomotor control from healthy automaticity to compensatory prefrontal executive control. Indirect measures of automaticity of walking (e.g., step-to-step variability and dual-task cost) suggest that freezing of gait (FoG) may be associated with reduced automaticity of walking. However, the influence of FoG status on actual prefrontal cortex (PFC) activity during walking remains unclear. Objective: To investigate the influence of FoG status on automaticity of walking in people with PD. Methods: Forty-seven people with PD were distributed into two groups based on FoG status, which was assessed by the New Freezing of Gait Questionnaire: PD-FoG (n=23; UPDRS-III=35) and PD+FoG (n=24; UPDRS-III=43.1). Participants walked over a 9m straight path (with a 180° turn at each end) for 80s. Two conditions were tested Off medication: single- and dual-task walking (i.e., with a concomitant cognitive task). A portable functional near-infrared spectroscopy system recorded PFC activity while walking (including turns). Wearable inertial sensors were used to calculate spatiotemporal gait parameters. Results: PD+FoG had greater PFC activation during both single and dual-task walking than PD-FoG (p=0.031). There were no differences in gait between PD-FoG and PD+FoG. Both groups decreased gait speed (p=0.029) and stride length (p<0.001) during dual-task walking compared to single-task walking. Conclusions: These findings suggest that PD+FoG have reduced automaticity of walking, even in absence of FoG episodes. PFC activity while walking seems to be more sensitive than gait measures in identifying reduction in automaticity of walking in PD+FoG

BIOMECHANICAL MARKERS AS INDICATORS OF POSTURAL INSTABILITY PROGRESSION IN PARKINSON'S DISEASE

The long term objective of this research is to identify quantitative biomechanical parameters of postural instability in patients with Parkinson’s disease (PD) that can in turn be used to assess fall risk. Currently, clinical assessments in PD are not sufficiently sensitive to predict fall risk, making a history of falls to be the best predictor of a future fall. Identifying biomechanical measures to predict risk of falls in PD would provide a quantitative justification to implement fall-reducing therapies prior to a first fall and help prevent the associated debilitating fractures or even morbidity. While past biomechanical studies have shown the presence of balance deficits in PD patients, which often include a broad spectrum of disease stages, compared to healthy controls (HC), no studies have assessed whether such parameters can distinguish the onset of postural instability prior to clinical presentation, and if such parameters persist following clinical presentation of postural instability. Toward this end this study had three goals: • Determine if biomechanical assessment of a quasi-static task, postural sway, could provide preclinical indication of postural instability in PD. • Define a mathematical model (based on principal component analysis, PCA) with biomechanical and clinical measures as inputs to quantitatively score earlier postural instability presence and progression in PD. • Investigate if biomechanical assessment of a dynamic task, gait initiation, could provide preclinical indication of postural instability in PD. Specific Aim 1 determined that some biomechanical postural sway variables showed evidence of preclinical postural instability and increased with PD progression. This aim distinguished mild PD (Hoehn and Yahr stage (H&Y) 2, without postural deficits) compared to HC suggesting preclinical indication of postural instability, and confirmed these parameters persisted in moderate PD (H&Y 3, with postural deficits). Specifically, trajectory, variation, and peak measures of the center of pressure (COP) during postural sway showed significant differences (p < .05) in mild PD compared to healthy controls, and these differences persisted in moderate PD. Schwab and England clinical score best correlated with the COP biomechanical measures. These results suggest that postural sway COP measures may provide preclinical indication of balance deficits in PD and increase with clinical PD progression. Specific Aim 2 defined a PCA model based on biomechanical measures of postural sway and clinical measures in mild PD, moderate PD, and HC. PCA modeling based on a correlation matrix structure identified both biomechanical and clinical measures as the primary drivers of variation in the data set. Further, a PCA model based on these selected parameters was able to significantly differentiate (p < .05) all 3 groups, suggesting PCA scores may help with preclinical indication of postural instability (mild PD versus HC) and could be sensitive to clinical disease progression (mild PD versus moderate PD and moderate PD versus HC). AP sway path length and a velocity parameter were the 2 primary measures that explained the variability in the data set, suggesting further investigation of these parameters and mathematical models for scoring postural instability progression is warranted. Specific Aim 3 determined that a velocity measure from biomechanical assessment of gait initiation (peak COP velocity towards the swing foot during locomotion) showed evidence of preclinical postural instability in PD. Because balance is a complex task, having a better understanding of both quasi-static (postural sway) and dynamic (gait initiation) tasks can provide further insight about balance deficits resulting from PD. Several temporal and kinematic parameters changed with increasing disease progression, with significant difference in moderate PD versus HC, but missed significance in mild PD compared to HC. Total Unified Parkinson’s Disease Rating Scale (UPDRS) and Pull Test clinical scores best correlated with the biomechanical measures of the gait initiation response. These results suggest dynamic biomechanical assessment may provide additional information in quantifying preclinical postural instability and progression in PD. In summary, reducing fall risk in PD is a high priority effort to maintain quality of life by allowing continued independence and safe mobility. Since no effective screening method exists to measure fall risk, our team is developing a multi-factorial method to detect postural instability through clinical balance assessment, and in doing so, provide the justification for implementing fall reducing therapies before potentially debilitating falls begin

Computer vision of video to measure bradykinesia and tremor in Parkinson’s Disease

The assessment of Parkinson’s disease is based upon clinician visual judgement. At the centre of this is a characteristic visible impairment of movement – bradykinesia – with often another visible sign, tremor. My thesis is that computer interpretation of video can provide clinically meaningful measures of finger tapping bradykinesia, and hand tremor, in Parkinson’s disease. A scoping literature review of technologies to automate the finger tapping test for bradykinesia in Parkinson’s (to 2021) identified 54 studies. Published methods include surface contact, infrared, gyroscope, accelerometer. There is a wide variation in strength and significance of correlations with clinical ratings, classification accuracies and group mean differences. Interrater reliability for judging finger tapping bradykinesia was investigated for 21 neurologists using 137 videos rated by the Movement Disorder Society revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS). There was only moderate agreement, intraclass correlation coefficient 0.53 (standard linear model) and 0.65 (cumulative linked mixed model). 24% of control videos were judged as bradykinesia. 70% of videos were correctly identified as Parkinson’s/control. A computer vision optical flow method was applied to 70 finger tapping videos, with dimensionality reduction using principal component analysis before input to classification models. Test accuracy was 0.8 for mild/moderate/severe bradykinesia and 0.67 for the presence of Parkinson’s disease. The computer vision pose estimation technique DeepLabCut was applied to 133 finger tapping videos. Resultant measures correlated well with clinical ratings of bradykinesia (Spearman coefficients): −0.74 speed, 0.66 amplitude, −0.65 rhythm for Modified Bradykinesia Rating Scale; −0.56 speed, 0.61 amplitude, −0.50 rhythm, −0.69 combined for MDS-UPDRS. All p < .001. Eulerian video magnification was applied to 48 videos of atremulous hands. The proportion of hands correctly classified as parkinsonian/control by clinicians was higher after Eulerian magnification (OR = 2.67; CI = [1.39, 5.17]; p < 0.003). Optical flow with Fourier transform was applied to 40 videos of tremulous hands. Bland-Altman analysis of dominant tremor frequency from video compared with accelerometer showed excellent agreement: 95% limits of agreement −0.38 Hz to +0.35 Hz. These results suggest that standard smartphone video can be used to derive measures of bradykinesia and tremor, and could form the basis of a tool to augment clinical assessment

Motor Adaptation and Automaticity in People with Parkinson’s Disease and Freezing of Gait

Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by cell death in the substantia nigra pars compacta, resulting in motor symptoms of tremor, rigidity, bradykinesia and gait impairment. Freezing of gait (FOG) is one serious gait disturbance, characterized by a transient inability produce effective stepping during walking and turning, and affects roughly half of people with PD at some point during their disease. Despite the ongoing research on the behavioral, neurological, and cognitive characteristics of people with FOG (PD+FOG), the mechanisms underlying freezing are still poorly understood. The overall aim of this work was to further investigate motor behavior in PD+FOG to provide insight into its potential mechanisms. The first experiment investigated possible cerebellar dysfunction in PD+FOG by examining visuomotor adaptation, a well-known cerebellar-dependent process. We found that there were no differences in reaching or walking adaptation between freezers and non-freezers, however non-freezers exhibited smaller after-effects compared to freezers and healthy older adults. Furthermore, adults with PD, as well as older and younger adults adapt walking patterns slower than reaching patterns, indicating walking is a more complex task requiring greater sensorimotor processing to modify. Overall, this study showed that cerebellar function, in terms of its role in sensorimotor adaptation, is relatively preserved in PD and FOG. In the second experiment, we examined motor automaticity of saccadic eye movements and reaching. Reduced automaticity is a likely motor-cognitive mechanism that contributes to freezing behavior, however automaticity in other motor systems has yet to fully described. Using an anti-saccade task, we found that PD+FOG participants were slower to respond to both automatic and non-automatic eye movements, and had increased saccade velocity variability compared to PD-FOG and controls. These changes were not related to disease severity or general cognition. In contrast, both PD groups were slower to execute (greater latency) reaching movements during both pro- and anti-reaching, but no freezer non-freezer differences were noted. PD+FOG reached with lower peak velocity compared to older adults but were similar to PD-FOG during both automatic and non-automatic conditions. These data show that changes in automaticity and control exist outside locomotor centers, indicating freezing may be a global motor disturbance. Altogether, the work in this dissertation furthers our knowledge on motor control in PD+FOG and provides additional evidence that freezing affects non-gait motor function

Inertial sensor based full body 3D kinematics in the differential diagnosis between Parkinson’s Disease and mimics

The differential diagnosis of Parkinson’s Disease (PD) remains challenging with frequent mis and underdiagnosis. DAT-Scan has been a useful technique for assessing the lost integrity of the nigrostriatal pathway in PD and differentiating true parkinsonism from mimics. However, DAT-Scan remains unavailable in most non-specialized clinical centres, making imperative the search for other easy and low-cost solutions. This dissertation aimed to investigate the role of inertial sensors in distinguishing between the denervated and the non-denervated individuals. In this dissertation, we've used Inertial Sensor Based 3D Full Body Kinematics (FBK) and tested if this technique was able to distinguish between patients with changes in the DAT-Scan from those without. This was divided into two parts, being that firstly, a group of individuals was referred by the attending physician for DAT-Scan (123I-FP-CIT SPECT) to be able to compare FBK in those with and without evidence of dopaminergic depletion. Second, it was tested whether FBK could be used as a metric for the severity of dopaminergic depletion. Twenty-one patients participated in this study, being recruited from the Nuclear Medicine Unit in the Champalimaud Clinical Centre (CCC), Lisbon. Within these 21 patients, 10 of them had denervation (mean age, 68.4 ± 7.8 years) and the remaining 11 (mean age, 66.6 ± 7.4 years) did not present denervation. The analysis between the worst uptake ratio features and dimensional features, as well as the asymmetry indexes in the striatum revealed significant differences between denervated and non-denervated individuals. On the contrary, the kinematics did not do it. Overall, based on the collected kinematics data, it was identified that there was not any significant correlation between the kinematics and the DAT-Scan. What means that these kinematics variables were not able to explain the DAT-Scan. On the other hand, it was also checked that the kinematics data were strongly correlated to the motor symptoms (MDS-UPDRS III). This way, it was concluded that the classical biomechanics did not distinguish denervated from non-denervated individuals. Therefore, the kinematics could not give the same answer as the DAT-Scan. In spite of these results it would be relevant to keep researching other methods in order to find out the distinction between the denervation and no denervation in a low-cost way

The Effect of Moderate Parkinson's Disease on the Biomechanics of Compensatory Backwards Stepping

Postural instability leading to falls is one of the major unmet needs in the treatment of Parkinson's disease (PD). The progression of postural instability is not well understood, and a better understanding of the biomechanics underlying the progression of postural instability may be instrumental in the development of more sensitive clinical measures of postural instability and fall risk in PD. The biomechanical analysis of the response to a balance perturbation provides an opportunity to better understand postural instability in PD. This study examined the compensatory stepping response to a backwards pull in participants with moderate PD compared to age-range matched healthy controls. The first study investigated the overall response to a balance disturbance in moderate PD, and found that patients with moderate PD utilized more steps to regain balance, had a longer weight shift time, and used a base-width neutral step as a strategy to regain balance, compared to controls. The second study further investigated the compensatory response by focusing on the preparation phase and found that participants with moderate PD used multiple anticipatory postural adjustments (APAs), resulting in longer liftoff times and significantly different movement in the center of pressure prior to liftoff compared to healthy controls. The third study investigated the effects of PD and step strategy (single step, multiple steps, and a base-width neutral step) on balance recovery and found that participants with moderate PD took significantly longer to recover balance, and that the type of strategy used to respond to the disturbance significantly impacted recovery time. Additionally, the use of a base-width neutral step as the first step in the response emerged as a strategy that has not been previously documented and significantly delays balance recovery. These results suggest that moderate PD significantly impairs the compensatory response to a backwards pull. Furthermore, this impairment could be attributed to a delay in the preparation phase of the step response. This delay was associated with the use of multiple anticipatory postural adjustments and/or the use of a base-width neutral step as the first step in the response. Further study should examine the progression of impairment in these compensatory responses across PD severity levels, and the correlation with fall risk

Clinical Decision Support Systems with Game-based Environments, Monitoring Symptoms of Parkinson’s Disease with Exergames

Parkinson’s Disease (PD) is a malady caused by progressive neuronal degeneration, deriving in several physical and cognitive symptoms that worsen with time. Like many other chronic diseases, it requires constant monitoring to perform medication and therapeutic adjustments. This is due to the significant variability in PD symptomatology and progress between patients. At the moment, this monitoring requires substantial participation from caregivers and numerous clinic visits. Personal diaries and questionnaires are used as data sources for medication and therapeutic adjustments. The subjectivity in these data sources leads to suboptimal clinical decisions. Therefore, more objective data sources are required to better monitor the progress of individual PD patients. A potential contribution towards more objective monitoring of PD is clinical decision support systems. These systems employ sensors and classification techniques to provide caregivers with objective information for their decision-making. This leads to more objective assessments of patient improvement or deterioration, resulting in better adjusted medication and therapeutic plans. Hereby, the need to encourage patients to actively and regularly provide data for remote monitoring remains a significant challenge. To address this challenge, the goal of this thesis is to combine clinical decision support systems with game-based environments. More specifically, serious games in the form of exergames, active video games that involve physical exercise, shall be used to deliver objective data for PD monitoring and therapy. Exergames increase engagement while combining physical and cognitive tasks. This combination, known as dual-tasking, has been proven to improve rehabilitation outcomes in PD: recent randomized clinical trials on exergame-based rehabilitation in PD show improvements in clinical outcomes that are equal or superior to those of traditional rehabilitation. In this thesis, we present an exergame-based clinical decision support system model to monitor symptoms of PD. This model provides both objective information on PD symptoms and an engaging environment for the patients. The model is elaborated, prototypically implemented and validated in the context of two of the most prominent symptoms of PD: (1) balance and gait, as well as (2) hand tremor and slowness of movement (bradykinesia). While balance and gait affections increase the risk of falling, hand tremors and bradykinesia affect hand dexterity. We employ Wii Balance Boards and Leap Motion sensors, and digitalize aspects of current clinical standards used to assess PD symptoms. In addition, we present two dual-tasking exergames: PDDanceCity for balance and gait, and PDPuzzleTable for tremor and bradykinesia. We evaluate the capability of our system for assessing the risk of falling and the severity of tremor in comparison with clinical standards. We also explore the statistical significance and effect size of the data we collect from PD patients and healthy controls. We demonstrate that the presented approach can predict an increased risk of falling and estimate tremor severity. Also, the target population shows a good acceptance of PDDanceCity and PDPuzzleTable. In summary, our results indicate a clear feasibility to implement this system for PD. Nevertheless, long-term randomized clinical trials are required to evaluate the potential of PDDanceCity and PDPuzzleTable for physical and cognitive rehabilitation effects