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

Balance and gait in Parkinson’s disease : from perceptions to performance

The overall aim of this thesis was to explore perceptions and performance of balance and gait in people with Parkinson’s disease (PwPD), and to evaluate both the current evidence for exercise-induced neuroplasticity and the feasibility of investigating exercise-induced neuroplastic changes among PwPD. This thesis includes four papers of different designs; a qualitative interview study (paper I), a systematic review and meta-analysis (paper II), a pilot RCT (paper III) and a crosssectional study (paper IV). Participants in papers I, III & IV were recruited through advertisement in newspapers and through the Parkinson association in Stockholm (sample sizes n=18, n=13 and n=93, respectively), whereas paper II selected studies from database searches (included studies n=13, total participant sample n=213). Five themes emerged from the qualitative content analysis of the interviews, the underlying patterns of which formed the overarching theme “Focus and determination to regain control over shifting balance”. In paper II, the narrative synthesis revealed that a majority of the studies indicated that exercise can possibly induce positive neuroplastic changes in PwPD, but the evidence according to the GRADE analysis was very low. In paper III we found that a proposed design to explore associations between changes in behavioral outcomes and neuroplasticity after ten weeks of the HiBalance training was feasible and acceptable given a few modifications ahead of the RCT. Finally paper IV showed that people with mild to moderate PD exhibited impaired performance across most domains of gait when simultaneously having to concentrate on a cognitive task (dual tasking). Impaired cognitive function was associated with higher costs on gait, as well as a tendency to use a posture-second prioritization in which the cognitive task was prioritized over walking. Balance was perceived as both bodily equilibrium and a mind-body interplay. The meaning of balance was described through concepts of control and the ability to control one’s body in everyday life. Regarding exercise-induced neuroplasticity in PD, published studies showed promising results, but more high-quality RCTs, using scientifically sound methodology are needed in order to drive this research field forward. Our proposed RCT design to evaluate neuroplastic changes after the HiBalance training was feasible, but needed strengthening regarding blinding procedures, the MRI paradigm and the dual task gait assessment. Walking while simultaneously concentrating on a cognitive task impaired performance on both tasks, especially among those with cognitive impairment. These findings provide preliminary evidence to suggest that dual task training and assessment should be planned and instructed differently according to cognitive status in PwPD

Unsupervised feature extraction with autoencoder : for the representation of parkinson´s disease patients

Dissertation presented as partial requirement for obtaining the Master’s degree in Information Management, with a specialization in Knowledge Management and Business IntelligenceData representation is one of the fundamental concepts in machine learning. An appropriate representation is found by discovering a structure and automatic detection of patterns in data. In many domains, representation or feature learning is a critical step in improving the performance of machine learning algorithms due to the multidimensionality of data that feeds the model. Some tasks may have different perspectives and approaches depending on how data is represented. In recent years, deep artificial neural networks have provided better solutions to several pattern recognition problems and classification tasks. Deep architectures have also shown their effectiveness in capturing latent features for data representation. In this document, autoencoders will be examined to obtain the representation of Parkinson's disease patients and compared with conventional representation learning algorithms. The results will show whether the proposed method of feature selection leads to the desired accuracy for predicting the severity of Parkinson’s disease

Effect of Qigong Exercise on Sleep Quality and Gait Performance in Parkinson's Disease

Background: Parkinson's disease (PD) involves a variety of motor and non-motor symptoms. Current medical therapy has been successful at managing a majority of these features; however, several issues, including gait complications and sleeping disorders, may involve impairments not fully resolved by standard therapy. This study aimed to determine the impact of Qigong as a potential complementary therapy in the management of gait and sleep related symptoms in PD. Methods: Seven subjects (age 66.86 ± 8.13 years) with PD participated in a six-week Qigong exercise intervention. Pre- and post-intervention testing was performed to assess sleep quality, fatigue, and gait performance in these subjects. Standard clinical assessments specific to PD were used for the assessment of sleep quality and fatigue. Gait performance was assessed using three-dimensional motion capture during the completion of several tasks. Overall gait performance (stride time, stride length, double support time, and velocity), gait variability (stride time variability and stride length variability), and turning performance (number of steps and total time to turn) were analyzed in the gait tasks. Results: Following the intervention, subjects showed a general trend of improvements in sleep quality. Fatigue remained unchanged. Assessment of gait performance showed significant improvement in overall gait function and gait variability, and no apparent change in turn performance. Gait function was improved by a significant reduction of stride time and a slight increase in stride length. Together these changes resulted in significant improvements to gait velocity. Additionally, time spent in double support was reduced following the intervention. Overall gait variability improved significantly, particularly in the reduction of stride time variability. Conclusions: These results suggest that the Qigong intervention implemented for this group may provide potential benefits to people with PD in regards to gait performance and sleep quality. Further studies are required to provide a more definitive measure of these results with increased statistical power

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

Personalizing functional Magnetic Resonance Protocols for Studying Neural Substrates of Motor Deficits in Parkinson’s Disease

Parkinson’s disease (PD) is a progressive neurodegenerative movement disorder characterized by a large number of motor and non-motor deficits, which significantly contribute to reduced quality of life. Despite the definition of the broad spectrum of clinical characteristics, mechanisms triggering illness, the nature of its progression and a character of therapeutic effects still remain unknown. The enormous advances in magnetic resonance imaging (MRI) in the last decades have significantly affected the research attempts to uncover the functional and structural abnormalities in PD and have helped to develop and monitor various treatment strategies, of which dopamine replacement strategies, mainly in form of levodopa, has been the gold standard since the late seventies and eighties. Motor, task-related functional MRI (fMRI) has been extensively used to assess the pathological state of the motor circuitry in PD. Several studies employed motor paradigms and fMRI to review the functional brain responses of participants to levodopa treatment. Interestingly, they provided conflicting results. Wide spectrum of symptoms, variability and asymmetry of the disease presentation, several treatment approaches and their divergent outcomes make PD enormously heterogeneous. In this work we hypothesized that not considering the disease heterogeneity might have been an adequate cause for the discrepant results in aforementioned studies. We show that not accounting for the disease variability might indeed compromise the results and invalidate the consequent interpretations. Accordingly, we propose and formalize a statistical approach to account for the intra and inter subject variability. This might help to minimize this bias in future motor fMRI studies revealing the functional brain dysfunction and contribute to the understanding of still unknown pathophysiological mechanisms underlying PD

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