Simultaneous prediction of symptom severity and cause in data from a test battery for Parkinson patients, using machine learning methods

The main purpose of this thesis project is to prediction of symptom severity and cause in data from test battery of the Parkinson’s disease patient, which is based on data mining. The collection of the data is from test battery on a hand in computer. We use the Chi-Square method and check which variables are important and which are not important. Then we apply different data mining techniques on our normalize data and check which technique or method gives good results.The implementation of this thesis is in WEKA. We normalize our data and then apply different methods on this data. The methods which we used are Naïve Bayes, CART and KNN. We draw the Bland Altman and Spearman’s Correlation for checking the final results and prediction of data. The Bland Altman tells how the percentage of our confident level in this data is correct and Spearman’s Correlation tells us our relationship is strong. On the basis of results and analysis we see all three methods give nearly same results. But if we see our CART (J48 Decision Tree) it gives good result of under predicted and over predicted values that’s lies between -2 to +2. The correlation between the Actual and Predicted values is 0,794in CART. Cause gives the better percentage classification result then disability because it can use two classes.

A home environment test battery for status assessment in patients with motor fluctuations

Background and aims Evaluating status in patients with motor fluctuations is complex and occasional observations/measurements do not give an adequate picture as to the time spent in different states. We developed a test battery to assess advanced Parkinson patients' status consisting of diary assessments and motor tests. This battery was constructed and implemented on a handheld computer with built-in mobile communication. In fluctuating patients, it should typically be used several times daily in the home environment, over periods of about one week. The aim of this battery is to provide status information in order to evaluate treatment effects in clinical practice and research, follow up treatments and disease progression and predict outcome to optimize treatment strategy. Methods Selection of diary questions was based on a previous study with Duodopa® (DIREQT). Tapping tests (with and without visual cueing) and a spiral drawing test were added. Rapid prototyping was used in development of the user interface. An evaluation with two pilot patients was performed before and after receiving new treatments for advanced disease (one received Duodopa® and one received DBS). Speed and proportion missed taps were calculated for the tapping tests and entropy of the radial drawing velocity was calculated for the spiral tests. Test variables were evaluated using non-parametric statistics. Results Post-treatment improvement was detected in both patients in many of the test variables. Conclusions Although validation work remains, preliminary results are promising and the test battery is currently being evaluated in a long-term health economics study with Duodopa® (DAPHNE).

Analysis of tapping test results in a test battery for advanced PD patients

Objective: To compare results from various tapping tests with diary responses in advanced PD. Background: A home environment test battery for assessing patient state in advanced PD, consisting of diary assessments and motor tests was constructed for a hand computer with touch screen and mobile communication. The diary questions: 1. walking, 2. time in off , on and dyskinetic states, 3. off at worst, 4. dyskinetic at worst, 5. cramps, and 6. satisfied with function, relate to the recent past. Question 7, self-assessment, allows seven steps from -3 ( very off ) to +3 ( very dyskinetic ) and relate to right now. Tapping tests outline: 8. Alternately tapping two fields (un-cued) with right hand 9. Same as 8 but using left hand 10. Tapping an active field (out of two) following a system-generated rhythm (increasing speed) with the dominant hand 11. Tapping an active field (out of four) that randomly changes location when tapped using the dominant hand Methods: 65 patients (currently on Duodopa, or candidates for this treatment) entered diary responses and performed tapping tests four times per day during one to six periods of seven days length. In total there were 224 test periods and 6039 test occasions. Speed for tapping test 10 was discardedand tests 8 and 9 were combined by taking means. Descriptive statistics were used to present the variation of the test variables in relation to self assessment (question 7). Pearson correlation coefficients between speed and accuracy (percent correct) in tapping tests and diary responses were calculated. Results: Mean compliance (percentage completed test occasions per test period) was 83% and the median was 93%. There were large differences in both mean tapping speed and accuracy between the different self-assessed states. Correlations between diary responses and tapping results were small (-0.2 to 0.3, negative values for off-time and dyskinetic-time that had opposite scale directions). Correlations between tapping results were all positive (0.1 to 0.6). Conclusions: The diary responses and tapping results provided different information. The low correlations can partly be explained by the fact that questions related to the past and by random variability, which could be reduced by taking means over test periods. Both tapping speed and accuracy reflect the motor function of the patient to a large extent.

A web application for follow-up of results from a mobile device test battery for parkinson’s disease patients

Background: A test battery consisting of self-assessments and motor tests (tapping and spiral drawing) was developed for a hand computer with touch screen in a telemedicine setting. Objectives: To develop and evaluate a web-based system that delivers decision support information to the treating clinical staff for assessing PD symptoms in their patients based on the test battery data. Methods: The test battery is currently being used in a clinical trial (DAPHNE, EudraCT No. 2005-002654-21) by sixty five patients with advanced Parkinson’s disease (PD) on 9991 test occasions (four tests per day during in all 362 week-long test periods) at nine clinics around Sweden. Test results are sent continuously from the hand unit over a mobile net to a central computer and processed with statistical methods. They are summarized into scores for different dimensions of the symptom state and an ‘overall test score’ reflecting the overall condition of the patient during a test period. The information in the web application is organized and presented graphically in a way that the general overview of the patient performance per test period is emphasized. Focus is on the overall test score, symptom dimensions and daily summaries. In a recent preliminary user evaluation, the web application was demonstrated to the fifteen study nurses who had used the test battery in the clinical trial. At least one patient per clinic was shown. Results: In general, the responses from nurses were positive. They claimed that the test results shown in the system were consistent with their own clinical observations. They could follow complications, changes and trends within their patients. Discussion: In conclusion, the system is able to summarise the various time series of motor test results and self-assessments during test periods and present them in a useful manner. Its main contribution is a novel and reliable way to capture and easily access symptom information from patients’ home environment. The convenient access to current symptom profile as well as symptom history provides a basis for individualized evaluation and adjustment of treatments.

12-month results from a novel test battery used in a duodenal levodopa infusion trial

A novel test battery consisting of self-assessments and motor tests (tapping and spiral drawing) for patients with Parkinson’s disease (PD) was developed for a hand computer with touch screen in a telemedicine setting. Tests are performed four times per day in the home environment during weeklong test periods. Results are processed into scores for different dimensions of the symptom state and an ‘overall score’ reflecting the global condition of a patient during a test period. The test battery was validated in a separate study recently submitted to Mov Disord. This test battery is currently being used in an open longitudinal trial (DAPHNE, EudraCT No. 2005- 002654-21) by sixty-five patients with advanced PD at nine clinics around Sweden. On inclusion, the patients were either receiving treatment with duodenal levodopa/carbidopa infusion (Duodopa®) (n=36), or they were candidates for receiving this treatment (n=29). We now present interim results for the first twelve months. Test periods were performed in three-month intervals. During most of the periods, UPDRS ratings were performed in afternoons at the start of the week. In twenty of the patients, scores were available during individually optimized oral polypharamacy, before receiving infusion and at least one test period after having started infusion treatment. Usability and compliance with performing tests, this far are good, both with patients and clinical staff. Correlations between test periods 2 and 3 during infusion treatment (three months apart) are stronger for overall test score than for total UPDRS, indicating good reliability. The correlation between overall test score and UPDRS for all test periods is adequate (r=-0.6). In an exact Wilcoxon signed rank test, where the endpoint is the change from the first to the twelve month test period (n=25), there was no change in test results in any of the test battery dimensions for the patients already receiving infusion when included. However, in the patients entering the study before receiving infusion, there was a significant change (improvement) from the baseline to the twelve month test period in dimensions; ‘off’, ‘dyskinesia’ and ‘satisfied’ and in the ‘overall score’ (n=15). The mean improvement in overall score after infusion was 29% (p=0.015). We conclude that the test battery is able to measure a functional improvement with infusion that is sustained over at least twelve months.

A web based decision support system for status assessment in advanced parkinson

The purpose of this work is to develop a web based decision support system, based onfuzzy logic, to assess the motor state of Parkinson patients on their performance in onscreenmotor tests in a test battery on a hand computer. A set of well defined rules, basedon an expert’s knowledge, were made to diagnose the current state of the patient. At theend of a period, an overall score is calculated which represents the overall state of thepatient during the period. Acceptability of the rules is based on the absolute differencebetween patient’s own assessment of his condition and the diagnosed state. Anyinconsistency can be tracked by highlighted as an alert in the system. Graphicalpresentation of data aims at enhanced analysis of patient’s state and performancemonitoring by the clinic staff. In general, the system is beneficial for the clinic staff,patients, project managers and researchers.

Use of Photovoltaic on an E-bike? : A Feasibility Study

In recent years the number of bicycles with e-motors has been increased steadily. Within the pedelec – bikes where an e-motor supports the pedaling – a special group of transportation bikes has developed. These bikes have storage boxes in addition to the basic parts of a bike. Due to the space available on top of those boxes it is possible to install a PV system to generate electricity which could be used to recharge the battery of the pedelec. Such a system would lead to grid independent charging of the battery and to the possibility of an increased range of motor support. The feasibility of such a PV system is investigated for a three wheeled pedelec delivered by the company BABBOE NORDIC.The measured data of the electricity generation of this mobile system is compared to the possible electricity generation of a stationary system.To measure the consumption of the pedelec different tracks are covered, and the energy which is necessary to recharge the bike battery is measured using an energy logger. This recharge energy is used as an indirect measure of the electricity consumption. A PV prototype system is installed on the bike. It is a simple PV stand alone system consisting of PV panel, charge controller with MPP tracker and a solar battery. This system has the task to generate as much electricity as possible. The produced PV current and voltage aremeasured and documented using a data logger. Afterwards the average PV power is calculated. To compare the produced electricity of the on-bike system to that of a stationary system, the irradiance on the latter is measured simultaneously. Due to partial shadings on the on-bike PV panel, which are caused by the driver and some other bike parts, the average power output during riding the bike is very low. It is too low to support the motor directly. In case of a similar installation as the PV prototype system and the intention always to park the bike on a sunny spot an on-bike system could generate electricity to at least partly recharge a bike battery during one day. The stationary PV system using the same PV panel could have produced between 1.25 and 8.1 times as much as the on-bike PV system. Even though the investigation is done for a very specific case it can be concluded that anon-bike PV system, using similar components as in the investigation, is not feasible to recharge the battery of a pedelec in an appropriate manner. The biggest barrier is that partial shadings on the PV panel, which can be hardly avoided during operation and parking, result in a significant reduction of generated electricity. Also the installation of the on-bike PV system would lead to increased weight of the whole bike and the need for space which is reducing the storage capacity. To use solar energy for recharging a bike battery an indirect way is giving better results. In this case a stationary PV stand alone system is used which is located in a sunny spot without shadings and adjusted to use the maximum available solar energy. The battery of the bike is charged using the corresponding charger and an inverter which provides AC power using the captured solar energy.

Intelligent Algorithms for a Hybrid FuelCell/Photovoltaic Standalone System : Simulation Of Hybrid FuelCell/Photovoltaic Standalone System

The Intelligent Algorithm is designed for theusing a Battery source. The main function is to automate the Hybrid System through anintelligent Algorithm so that it takes the decision according to the environmental conditionsfor utilizing the Photovoltaic/Solar Energy and in the absence of this, Fuel Cell energy isused. To enhance the performance of the Fuel Cell and Photovoltaic Cell we used batterybank which acts like a buffer and supply the current continuous to the load. To develop the main System whlogic based controller was used. Fuzzy Logic based controller used to develop this system,because they are chosen to be feasible for both controlling the decision process and predictingthe availability of the available energy on the basis of current Photovoltaic and Battery conditions. The Intelligent Algorithm is designed to optimize the performance of the system and to selectthe best available energy source(s) in regard of the input parameters. The enhance function of these Intelligent Controller is to predict the use of available energy resources and turn on thatparticular source for efficient energy utilization. A fuzzy controller was chosen to take thedecisions for the efficient energy utilization from the given resources. The fuzzy logic basedcontroller is designed in the Matlab-Simulink environment. Initially, the fuzzy based ruleswere built. Then MATLAB based simulation system was designed and implemented. Thenthis whole proposed model is simulated and tested for the accuracy of design and performanceof the system.

Visualization of spirography-based objective measures in Parkinson's disease

Objective: To investigate whether advanced visualizations of spirography-based objective measures are useful in differentiating drug-related motor dysfunctions between Off and dyskinesia in Parkinson’s disease (PD). Background: During the course of a 3 year longitudinal clinical study, in total 65 patients (43 males and 22 females with mean age of 65) with advanced PD and 10 healthy elderly (HE) subjects (5 males and 5 females with mean age of 61) were assessed. Both patients and HE subjects performed repeated and time-stamped assessments of their objective health indicators using a test battery implemented on a telemetry touch screen handheld computer, in their home environment settings. Among other tasks, the subjects were asked to trace a pre-drawn Archimedes spiral using the dominant hand and repeat the test three times per test occasion. Methods: A web-based framework was developed to enable a visual exploration of relevant spirography-based kinematic features by clinicians so they can in turn evaluate the motor states of the patients i.e. Off and dyskinesia. The system uses different visualization techniques such as time series plots, animation, and interaction and organizes them into different views to aid clinicians in measuring spatial and time-dependent irregularities that could be associated with the motor states. Along with the animation view, the system displays two time series plots for representing drawing speed (blue line) and displacement from ideal trajectory (orange line). The views are coordinated and linked i.e. user interactions in one of the views will be reflected in other views. For instance, when the user points in one of the pixels in the spiral view, the circle size of the underlying pixel increases and a vertical line appears in the time series views to depict the corresponding position. In addition, in order to enable clinicians to observe erratic movements more clearly and thus improve the detection of irregularities, the system displays a color-map which gives an idea of the longevity of the spirography task. Figure 2 shows single randomly selected spirals drawn by a: A) patient who experienced dyskinesias, B) HE subject, and C) patient in Off state. Results: According to a domain expert (DN), the spirals drawn in the Off and dyskinesia motor states are characterized by different spatial and time features. For instance, the spiral shown in Fig. 2A was drawn by a patient who showed symptoms of dyskinesia; the drawing speed was relatively high (cf. blue-colored time series plot and the short timestamp scale in the x axis) and the spatial displacement was high (cf. orange-colored time series plot) associated with smooth deviations as a result of uncontrollable movements. The patient also exhibited low amount of hesitation which could be reflected both in the animation of the spiral as well as time series plots. In contrast, the patient who was in the Off state exhibited different kinematic features, as shown in Fig. 2C. In the case of spirals drawn by a HE subject, there was a great precision during the drawing process as well as unchanging levels of time-dependent features over the test trial, as seen in Fig. 2B. Conclusions: Visualizing spirography-based objective measures enables identification of trends and patterns of drug-related motor dysfunctions at the patient’s individual level. Dynamic access of visualized motor tests may be useful during the evaluation of drug-related complications such as under- and over-medications, providing decision support to clinicians during evaluation of treatment effects as well as improve the quality of life of patients and their caregivers. In future, we plan to evaluate the proposed approach by assessing within- and between-clinician variability in ratings in order to determine its actual usefulness and then use these ratings as target outcomes in supervised machine learning, similarly as it was previously done in the study performed by Memedi et al. (2013).

A web-based system for visualizing upper limb motor performance of Parkinson’s disease patients

Objective To design, develop and set up a web-based system for enabling graphical visualization of upper limb motor performance (ULMP) of Parkinson’s disease (PD) patients to clinicians. Background Sixty-five patients diagnosed with advanced PD have used a test battery, implemented in a touch-screen handheld computer, in their home environment settings over the course of a 3-year clinical study. The test items consisted of objective measures of ULMP through a set of upper limb motor tests (finger to tapping and spiral drawings). For the tapping tests, patients were asked to perform alternate tapping of two buttons as fast and accurate as possible, first using the right hand and then the left hand. The test duration was 20 seconds. For the spiral drawing test, patients traced a pre-drawn Archimedes spiral using the dominant hand, and the test was repeated 3 times per test occasion. In total, the study database consisted of symptom assessments during 10079 test occasions. Methods Visualization of ULMP The web-based system is used by two neurologists for assessing the performance of PD patients during motor tests collected over the course of the said study. The system employs animations, scatter plots and time series graphs to visualize the ULMP of patients to the neurologists. The performance during spiral tests is depicted by animating the three spiral drawings, allowing the neurologists to observe real-time accelerations or hesitations and sharp changes during the actual drawing process. The tapping performance is visualized by displaying different types of graphs. Information presented included distribution of taps over the two buttons, horizontal tap distance vs. time, vertical tap distance vs. time, and tapping reaction time over the test length. Assessments Different scales are utilized by the neurologists to assess the observed impairments. For the spiral drawing performance, the neurologists rated firstly the ‘impairment’ using a 0 (no impairment) – 10 (extremely severe) scale, secondly three kinematic properties: ‘drawing speed’, ‘irregularity’ and ‘hesitation’ using a 0 (normal) – 4 (extremely severe) scale, and thirdly the probable ‘cause’ for the said impairment using 3 choices including Tremor, Bradykinesia/Rigidity and Dyskinesia. For the tapping performance, a 0 (normal) – 4 (extremely severe) scale is used for first rating four tapping properties: ‘tapping speed’, ‘accuracy’, ‘fatigue’, ‘arrhythmia’, and then the ‘global tapping severity’ (GTS). To achieve a common basis for assessment, initially one neurologist (DN) performed preliminary ratings by browsing through the database to collect and rate at least 20 samples of each GTS level and at least 33 samples of each ‘cause’ category. These preliminary ratings were then observed by the two neurologists (DN and PG) to be used as templates for rating of tests afterwards. In another track, the system randomly selected one test occasion per patient and visualized its items, that is tapping and spiral drawings, to the two neurologists. Statistical methods Inter-rater agreements were assessed using weighted Kappa coefficient. The internal consistency of properties of tapping and spiral drawing tests were assessed using Cronbach’s α test. One-way ANOVA test followed by Tukey multiple comparisons test was used to test if mean scores of properties of tapping and spiral drawing tests were different among GTS and ‘cause’ categories, respectively. Results When rating tapping graphs, inter-rater agreements (Kappa) were as follows: GTS (0.61), ‘tapping speed’ (0.89), ‘accuracy’ (0.66), ‘fatigue’ (0.57) and ‘arrhythmia’ (0.33). The poor inter-rater agreement when assessing “arrhythmia” may be as a result of observation of different things in the graphs, among the two raters. When rating animated spirals, both raters had very good agreement when assessing severity of spiral drawings, that is, ‘impairment’ (0.85) and irregularity (0.72). However, there were poor agreements between the two raters when assessing ‘cause’ (0.38) and time-information properties like ‘drawing speed’ (0.25) and ‘hesitation’ (0.21). Tapping properties, that is ‘tapping speed’, ‘accuracy’, ‘fatigue’ and ‘arrhythmia’ had satisfactory internal consistency with a Cronbach’s α coefficient of 0.77. In general, the trends of mean scores of tapping properties worsened with increasing levels of GTS. The mean scores of the four properties were significantly different to each other, only at different levels. In contrast from tapping properties, kinematic properties of spirals, that is ‘drawing speed’, ‘irregularity’ and ‘hesitation’ had a questionable consistency among them with a coefficient of 0.66. Bradykinetic spirals were associated with more impaired speed (mean = 83.7 % worse, P < 0.001) and hesitation (mean = 77.8% worse, P < 0.001), compared to dyskinetic spirals. Both these ‘cause’ categories had similar mean scores of ‘impairment’ and ‘irregularity’. Conclusions In contrast from current approaches used in clinical setting for the assessment of PD symptoms, this system enables clinicians to animate easily and realistically the ULMP of patients who at the same time are at their homes. Dynamic access of visualized motor tests may also be useful when observing and evaluating therapy-related complications such as under- and over-medications. In future, we foresee to utilize these manual ratings for developing and validating computer methods for automating the process of assessing ULMP of PD patients.

Self-reported symptoms and motor tests via telemetry in a 36-month levodopa-carbidopa intestinal gel infusion trial

Objective To investigate if a home environment test battery can be used to measure effects of Parkinson’s disease (PD) treatment intervention and disease progression. Background Seventy-seven patients diagnosed with advanced PD were recruited in an open longitudinal 36-month study at 10 clinics in Sweden and Norway; 40 of them were treated with levodopa-carbidopa intestinal gel (LCIG) and 37 patients were candidates for switching from oral PD treatment to LCIG. They utilized a mobile device test battery, consisting of self-assessments of symptoms and objective measures of motor function through a set of fine motor tests (tapping and spiral drawings), in their homes. Both the LCIG-naïve and LCIG-non-naïve patients used the test battery four times per day during week-long test periods. Methods Assessments The LCIG-naïve patients used the test battery at baseline (before LCIG), month 0 (first visit; at least 3 months after intraduodenal LCIG), and thereafter quarterly for the first year and biannually for the second and third years. The LCIG-non-naïve patients used the test battery from the first visit, i.e. month 0. Out of the 77 patients, only 65 utilized the test battery; 35 were LCIG-non-naïve and 30 LCIG-naïve. In 20 of the LCIG-naïve patients, assessments with the test battery were available during oral treatment and at least one test period after having started infusion treatment. Three LCIG-naïve patients did not use the test battery at baseline but had at least one test period of assessments thereafter. Hence, n=23 in the LCIG-naïve group. In total, symptom assessments in the full sample (including both patient groups) were collected during 379 test periods and 10079 test occasions. For 369 of these test periods, clinical assessments including UPDRS and PDQ-39 were performed in afternoons at the start of the test periods. The repeated measurements of the test battery were processed and summarized into scores representing patients’ symptom severities over a test period, using statistical methods. Six conceptual dimensions were defined; four subjectively-reported: ‘walking’, ‘satisfied’, ‘dyskinesia’, and ‘off’ and two objectively-measured: ‘tapping’ and ‘spiral’. In addition, an ‘overall test score’ (OTS) was defined to represent the global health condition of the patient during a test period. Statistical methods Change in the test battery scores over time, that is at baseline and follow-up test periods, was assessed with linear mixed-effects models with patient ID as a random effect and test period as a fixed effect of interest. The within-patient variability of OTS was assessed using intra-class correlation coefficient (ICC), for the two patient groups. Correlations between clinical rating scores and test battery scores were assessed using Spearman’s rank correlations (rho). Results In LCIG-naïve patients, mean OTS compared to baseline was significantly improved from the first test period on LCIG treatment until month 24. However, there were no significant changes in mean OTS scores of LCIG-non-naïve patients, except for worse mean OTS at month 36 (p<0.01, n=16). The mean scores of all subjectively-reported dimensions improved significantly throughout the course of the study, except ‘walking’ at month 36 (p=0.41, n=4). However, there were no significant differences in mean scores of objectively-measured dimensions between baseline and other test periods, except improved ‘tapping’ at month 6 and month 36, and ‘spiral’ at month 3 (p<0.05). The LCIG-naïve patients had a higher within-subject variability in their OTS scores (ICC=0.67) compared to LCIG-non-naïve patients (ICC=0.71). The OTS correlated adequately with total UPDRS (rho=0.59) and total PDQ-39 (rho=0.59). Conclusions In this 3-year follow-up study of advanced PD patients treated with LCIG we found that it is possible to monitor PD progression over time using a home environment test battery. The significant improvements in the mean OTS scores indicate that the test battery is able to measure functional improvement with LCIG sustained over at least 24 months.

Spiral drawing during self-rated dyskinesia is more impaired than during self-rated off

Background: A mobile device test battery, consisting of a patient diary collection section with disease-related questions and a fine motor test section (including spiral drawing tasks), was used by 65 patients with advanced Parkinson's disease (PD)(treated with intraduodenal levodopa/carbidopa gel infusion, Duodopa®, or candidates for this treatment) on 10439 test occasions in their home environments. On each occasion, patients traced three pre-drawn Archimedes spirals using an ergonomic stylus and self-assessed their motor function on a global Treatment Response Scale (TRS) ranging from -3 = very 'off' to 0 = 'on' to +3 = very dyskinetic. The spirals were processed by a computer-based method that generates a "spiral score" representing the PD-related drawing impairment. The scale for the score was based on a modified Bain & Findley rating scale in the range from 0 = no impairment to 5 = moderate impairment to 10 = extremely severe impairment. Objective: To analyze the test battery data for the purpose to find differences in spiral drawing performance of PD patients in relation to their self-assessments of motor function. Methods: Three motor states were used in the analysis; OFF state (including moderate and very 'off'), ON state ('on') and a dyskinetic (DYS) state (moderate and very dyskinetic). In order to avoid the problem of multiple test occasions per patient, 200 random samples of single test occasions per patient were drawn. One-way analysis of variance, ANOVA, test followed by Tukey multiple comparisons test was used to test if mean values of spiral test parameters, i.e. the spiral score and drawing completion times (in seconds), were different among the three motor states. Statistical significance was set at p<0.05. To investigate changes in the spiral score over the time-of-day test sessions for the three motor states, plots of statistical summaries were inspected. Results: The mean spiral score differed significantly across the three self-assessed motor states (p<0.001, ANOVA test). Tukey post-hoc comparisons indicate that the mean spiral score (mean ± SD; [95% CI for mean]) in DYS state (5.2 ± 1.8; [5.12, 5.28]) was higher than the mean spiral score in OFF (4.3 ± 1.7; [4.22, 4.37]) and ON (4.2 ± 1.7; [4.17, 4.29]) states. The mean spiral score was also significantly different among individual TRS values of slightly 'off' (4.02 ± 1.63), 'on' (4.07 ± 1.65) and slightly dyskinetic (4.6 ± 1.71), (p<0.001). There were no differences in drawing completion times among the three motor states (p=0.509). In the OFF and ON states, patients drew slightly more impaired spirals in the afternoon whereas in the DYS state the spiral drawing performance was more impaired in the morning. Conclusion: It was found that when patients considered themselves as being dyskinetic spiral drawing was more impaired (nearly one unit change in a 0-10 scale) compared to when they considered themselves as being 'off' and 'on'. The spiral drawing at patients that self-assessed their motor state as dyskinetic was slightly more impaired in the morning hours, between 8 and 12 o'clock, a situation possibly caused by the morning dose effect.

First-principle data-driven models for assessment of motor disorders in Parkinson’s disease

Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic.  The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.

Digital spiral analysis for objective assessment of fine motor timing variability in Parkinson's disease

OBJECTIVES: To develop a method for objective assessment of fine motor timing variability in Parkinson’s disease (PD) patients, using digital spiral data gathered by a touch screen device. BACKGROUND: A retrospective analysis was conducted on data from 105 subjects including65 patients with advanced PD (group A), 15 intermediate patients experiencing motor fluctuations (group I), 15 early stage patients (group S), and 10 healthy elderly subjects (HE) were examined. The subjects were asked to perform repeated upper limb motor tasks by tracing a pre-drawn Archimedes spiral as shown on the screen of the device. The spiral tracing test was performed using an ergonomic pen stylus, using dominant hand. The test was repeated three times per test occasion and the subjects were instructed to complete it within 10 seconds. Digital spiral data including stylus position (x-ycoordinates) and timestamps (milliseconds) were collected and used in subsequent analysis. The total number of observations with the test battery were as follows: Swedish group (n=10079), Italian I group (n=822), Italian S group (n = 811), and HE (n=299). METHODS: The raw spiral data were processed with three data processing methods. To quantify motor timing variability during spiral drawing tasks Approximate Entropy (APEN) method was applied on digitized spiral data. APEN is designed to capture the amount of irregularity or complexity in time series. APEN requires determination of two parameters, namely, the window size and similarity measure. In our work and after experimentation, window size was set to 4 and similarity measure to 0.2 (20% of the standard deviation of the time series). The final score obtained by APEN was normalized by total drawing completion time and used in subsequent analysis. The score generated by this method is hence on denoted APEN. In addition, two more methods were applied on digital spiral data and their scores were used in subsequent analysis. The first method was based on Digital Wavelet Transform and Principal Component Analysis and generated a score representing spiral drawing impairment. The score generated by this method is hence on denoted WAV. The second method was based on standard deviation of frequency filtered drawing velocity. The score generated by this method is hence on denoted SDDV. Linear mixed-effects (LME) models were used to evaluate mean differences of the spiral scores of the three methods across the four subject groups. Test-retest reliability of the three scores was assessed after taking mean of the three possible correlations (Spearman’s rank coefficients) between the three test trials. Internal consistency of the methods was assessed by calculating correlations between their scores. RESULTS: When comparing mean spiral scores between the four subject groups, the APEN scores were different between HE subjects and three patient groups (P=0.626 for S group with 9.9% mean value difference, P=0.089 for I group with 30.2%, and P=0.0019 for A group with 44.1%). However, there were no significant differences in mean scores of the other two methods, except for the WAV between the HE and A groups (P<0.001). WAV and SDDV were highly and significantly correlated to each other with a coefficient of 0.69. However, APEN was not correlated to neither WAV nor SDDV with coefficients of 0.11 and 0.12, respectively. Test-retest reliability coefficients of the three scores were as follows: APEN (0.9), WAV(0.83) and SD-DV (0.55). CONCLUSIONS: The results show that the digital spiral analysis-based objective APEN measure is able to significantly differentiate the healthy subjects from patients at advanced level. In contrast to the other two methods (WAV and SDDV) that are designed to quantify dyskinesias (over-medications), this method can be useful for characterizing Off symptoms in PD. The APEN was not correlated to none of the other two methods indicating that it measures a different construct of upper limb motor function in PD patients than WAV and SDDV. The APEN also had a better test-retest reliability indicating that it is more stable and consistent over time than WAV and SDDV.