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.

Pedal : identification of models for duodenal administration of levodopa

Backgound and aims: The main purpose of the PEDAL study is to identify and estimate sample individual pharmacokinetic- pharmacodynamic (PK/PD) models for duodenal infusion of levodopa/carbidopa (Duodopa®) that can be used for in numero simulation of treatment strategies. Other objectives are to study the absorption of Duodopa® and to form a basis for power calculation for a future larger study. PK/PD based on oral levodopa is problematic because of irregular gastric emptying. Preliminary work with data from [Gundert-Remy U et al. Eur J Clin Pharmacol 1983;25:69-72] suggested that levodopa infusion pharmacokinetics can be described by a two-compartment model. Background research led to a hypothesis for an effect model incorporating concentration-unrelated fluctuations, more complex than standard E-max models. Methods: PEDAL involved a few patients already on Duodopa®. A bolus dose (normal morning dose plus 50%) was given after a washout during night. Data collection continued until the clinical effect was back at baseline. The procedure was repeated on two non-consecutive days per patient. The following data were collected in 5 to 15 minutes intervals: i) Accelerometer data. ii) Three e-diary questions about ability to walk, feelings of “off” and “dyskinesia”. iii) Clinical assessment of motor function by a physician. iv) Plasma concentrations of levodopa, carbidopa and the metabolite 3-O-methyldopa. The main effect variable will be the clinical assessment. Results: At date of abstract submission, lab analyses were currently being performed. Modelling results, simulation experiments and conclusions will be presented in our poster.

A pharmacokinetic-pharmacodynamic model for duodenal levodopa infusion

Objective Levodopa in presence of decarboxylase inhibitors is following two-compartment kinetics and its effect is typically modelled using sigmoid Emax models. Pharmacokinetic modelling of the absorption phase of oral distributions is problematic because of irregular gastric emptying. The purpose of this work was to identify and estimate a population pharmacokinetic- pharmacodynamic model for duodenal infusion of levodopa/carbidopa (Duodopa®) that can be used for in numero simulation of treatment strategies. Methods The modelling involved pooling data from two studies and fixing some parameters to values found in literature (Chan et al. J Pharmacokinet Pharmacodyn. 2005 Aug;32(3-4):307-31). The first study involved 12 patients on 3 occasions and is described in Nyholm et al. Clinical Neuropharmacology 2003:26:156-63. The second study, PEDAL, involved 3 patients on 2 occasions. A bolus dose (normal morning dose plus 50%) was given after a washout during night. Plasma samples and motor ratings (clinical assessment of motor function from video recordings on a treatment response scale between -3 and 3, where -3 represents severe parkinsonism and 3 represents severe dyskinesia.) were repeatedly collected until the clinical effect was back at baseline. At this point, the usual infusion rate was started and sampling continued for another two hours. Different structural absorption models and effect models were evaluated using the value of the objective function in the NONMEM package. Population mean parameter values, standard error of estimates (SE) and if possible, interindividual/interoccasion variability (IIV/IOV) were estimated. Results Our results indicate that Duodopa absorption can be modelled with an absorption compartment with an added bioavailability fraction and a lag time. The most successful effect model was of sigmoid Emax type with a steep Hill coefficient and an effect compartment delay. Estimated parameter values are presented in the table. Conclusions The absorption and effect models were reasonably successful in fitting observed data and can be used in simulation experiments.

Comparison of treatment of incomplete abortion with misoprostol by physicians and midwives at district level in Uganda : a randomised controlled equivalence trial

BACKGROUND: Misoprostol is established for the treatment of incomplete abortion but has not been systematically assessed when provided by midwives at district level in a low-resource setting. We investigated the effectiveness and safety of midwives diagnosing and treating incomplete abortion with misoprostol, compared with physicians. METHODS: We did a multicentre randomised controlled equivalence trial at district level at six facilities in Uganda. Eligibility criteria were women with signs of incomplete abortion. We randomly allocated women with first-trimester incomplete abortion to clinical assessment and treatment with misoprostol either by a physician or a midwife. The randomisation (1:1) was done in blocks of 12 and was stratified for study site. Primary outcome was complete abortion not needing surgical intervention within 14-28 days after initial treatment. The study was not masked. Analysis of the primary outcome was done on the per-protocol population with a generalised linear-mixed effects model. The predefined equivalence range was -4% to 4%. The trial was registered at ClinicalTrials.gov, number NCT01844024. FINDINGS: From April 30, 2013, to July 21, 2014, 1108 women were assessed for eligibility. 1010 women were randomly assigned to each group (506 to midwife group and 504 to physician group). 955 women (472 in the midwife group and 483 in the physician group) were included in the per-protocol analysis. 452 (95·8%) of women in the midwife group had complete abortion and 467 (96·7%) in the physician group. The model-based risk difference for midwife versus physician group was -0·8% (95% CI -2·9 to 1·4), falling within the predefined equivalence range (-4% to 4%). The overall proportion of women with incomplete abortion was 3·8% (36/955), similarly distributed between the two groups (4·2% [20/472] in the midwife group, 3·3% [16/483] in the physician group). No serious adverse events were recorded. INTERPRETATION: Diagnosis and treatment of incomplete abortion with misoprostol by midwives is equally safe and effective as when provided by physicians, in a low-resource setting. Scaling up midwives' involvement in treatment of incomplete abortion with misoprostol at district level would increase access to safe post-abortion care. FUNDING: The Swedish Research Council, Karolinska Institutet, and Dalarna University.

Women's acceptability of misoprostol treatment for incomplete abortion by midwives and physicians : secondary outcome analysis from a randomized controlled equivalence trial at district level in Uganda

OBJECTIVE: This study aimed to assess women´s acceptability of diagnosis and treatment of incomplete abortion with misoprostol by midwives, compared with physicians. METHODS: This was an analysis of secondary outcomes from a multi-centre randomized controlled equivalence trial at district level in Uganda. Women with first trimester incomplete abortion were randomly allocated to clinical assessment and treatment with misoprostol by a physician or a midwife. The randomisation (1:1) was done in blocks of 12 and stratified for health care facility. Acceptability was measured in expectations and satisfaction at a follow up visit 14-28 days following treatment. Analysis of women's overall acceptability was done using a generalized linear mixed-effects model with an equivalence range of -4% to 4%. The study was not masked. The trial is registered at ClinicalTrials.org, NCT 01844024. RESULTS: From April 2013 to June 2014, 1108 women were assessed for eligibility of which 1010 were randomized (506 to midwife and 504 to physician). 953 women were successfully followed up and included in the acceptability analysis. 95% (904) of the participants found the treatment satisfactory and overall acceptability was found to be equivalent between the two study groups. Treatment failure, not feeling calm and safe following treatment, experiencing severe abdominal pain or heavy bleeding following treatment, were significantly associated with non-satisfaction. No serious adverse events were recorded. CONCLUSIONS: Treatment of incomplete abortion with misoprostol by midwives and physician was highly, and equally, acceptable to women. TRIAL REGISTRATION: ClinicalTrials.gov NCT01844024.

Speech Assessment for the Classification of Hypokinetic Dysthria in Parkinson Disease

The aim of this thesis is to investigate computerized voice assessment methods to classify between the normal and Dysarthric speech signals. In this proposed system, computerized assessment methods equipped with signal processing and artificial intelligence techniques have been introduced. The sentences used for the measurement of inter-stress intervals (ISI) were read by each subject. These sentences were computed for comparisons between normal and impaired voice. Band pass filter has been used for the preprocessing of speech samples. Speech segmentation is performed using signal energy and spectral centroid to separate voiced and unvoiced areas in speech signal. Acoustic features are extracted from the LPC model and speech segments from each audio signal to find the anomalies. The speech features which have been assessed for classification are Energy Entropy, Zero crossing rate (ZCR), Spectral-Centroid, Mean Fundamental-Frequency (Meanf0), Jitter (RAP), Jitter (PPQ), and Shimmer (APQ). Naïve Bayes (NB) has been used for speech classification. For speech test-1 and test-2, 72% and 80% accuracies of classification between healthy and impaired speech samples have been achieved respectively using the NB. For speech test-3, 64% correct classification is achieved using the NB. The results direct the possibility of speech impairment classification in PD patients based on the clinical rating scale.

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).

Automatic and objective assessment of alternating tapping performance in Parkinson’s disease

This paper presents the development and evaluation of a method for enabling quantitative and automatic scoring of alternating tapping performance of patients with Parkinson’s disease (PD). Ten healthy elderly subjects and 95 patients in different clinical stages of PD have utilized a touch-pad handheld computer to perform alternate tapping tests in their home environments. First, a neurologist used a web-based system to visually assess impairments in four tapping dimensions (‘speed’, ‘accuracy’, ‘fatigue’ and ‘arrhythmia’) and a global tapping severity (GTS). Second, tapping signals were processed with time series analysis and statistical methods to derive 24 quantitative parameters. Third, principal component analysis was used to reduce the dimensions of these parameters and to obtain scores for the four dimensions. Finally, a logistic regression classifier was trained using a 10-fold stratified cross-validation to map the reduced parameters to the corresponding visually assessed GTS scores. Results showed that the computed scores correlated well to visually assessed scores and were significantly different across Unified Parkinson’s Disease Rating Scale scores of upper limb motor performance. In addition, they had good internal consistency, had good ability to discriminate between healthy elderly and patients in different disease stages, had good sensitivity to treatment interventions and could reflect the natural disease progression over time. In conclusion, the automatic method can be useful to objectively assess the tapping performance of PD patients and can be included in telemedicine tools for remote monitoring of tapping.

Automatic spiral analysis for objective assessment of motor symptoms in Parkinson's disease

Objective: To develop a method for objective quantification of PD motor symptoms related to Off episodes and peak dose dyskinesias, using spiral data gathered by using a touch screen telemetry device. The aim was to objectively characterize predominant motor phenotypes (bradykinesia and dyskinesia), to help in automating the process of visual interpretation of movement anomalies in spirals as rated by movement disorder specialists. Background: A retrospective analysis was conducted on recordings from 65 patients with advanced idiopathic PD from nine different clinics in Sweden, recruited from January 2006 until August 2010. In addition to the patient group, 10 healthy elderly subjects were recruited. Upper limb movement data were collected using a touch screen telemetry device from home environments of the subjects. Measurements with the device were performed four times per day during week-long test periods. On each test occasion, the subjects were asked to trace pre-drawn Archimedean spirals, using the dominant hand. The pre-drawn spiral was shown on the screen of the device. The spiral test was repeated three times per test occasion and they were instructed to complete it within 10 seconds. The device had a sampling rate of 10Hz and measured both position and time-stamps (in milliseconds) of the pen tip. Methods: Four independent raters (FB, DH, AJ and DN) used a web interface that animated the spiral drawings and allowed them to observe different kinematic features during the drawing process and to rate task performance. Initially, a number of kinematic features were assessed including ‘impairment’, ‘speed’, ‘irregularity’ and ‘hesitation’ followed by marking the predominant motor phenotype on a 3-category scale: tremor, bradykinesia and/or choreatic dyskinesia. There were only 2 test occasions for which all the four raters either classified them as tremor or could not identify the motor phenotype. Therefore, the two main motor phenotype categories were bradykinesia and dyskinesia. ‘Impairment’ was rated on a scale from 0 (no impairment) to 10 (extremely severe) whereas ‘speed’, ‘irregularity’ and ‘hesitation’ were rated on a scale from 0 (normal) to 4 (extremely severe). The proposed data-driven method consisted of the following steps. Initially, 28 spatiotemporal features were extracted from the time series signals before being presented to a Multilayer Perceptron (MLP) classifier. The features were based on different kinematic quantities of spirals including radius, angle, speed and velocity with the aim of measuring the severity of involuntary symptoms and discriminate between PD-specific (bradykinesia) and/or treatment-induced symptoms (dyskinesia). A Principal Component Analysis was applied on the features to reduce their dimensions where 4 relevant principal components (PCs) were retained and used as inputs to the MLP classifier. Finally, the MLP classifier mapped these components to the corresponding visually assessed motor phenotype scores for automating the process of scoring the bradykinesia and dyskinesia in PD patients whilst they draw spirals using the touch screen device. For motor phenotype (bradykinesia vs. dyskinesia) classification, the stratified 10-fold cross validation technique was employed. Results: There were good agreements between the four raters when rating the individual kinematic features with intra-class correlation coefficient (ICC) of 0.88 for ‘impairment’, 0.74 for ‘speed’, 0.70 for ‘irregularity’, and moderate agreements when rating ‘hesitation’ with an ICC of 0.49. When assessing the two main motor phenotype categories (bradykinesia or dyskinesia) in animated spirals the agreements between the four raters ranged from fair to moderate. There were good correlations between mean ratings of the four raters on individual kinematic features and computed scores. The MLP classifier classified the motor phenotype that is bradykinesia or dyskinesia with an accuracy of 85% in relation to visual classifications of the four movement disorder specialists. The test-retest reliability of the four PCs across the three spiral test trials was good with Cronbach’s Alpha coefficients of 0.80, 0.82, 0.54 and 0.49, respectively. These results indicate that the computed scores are stable and consistent over time. Significant differences were found between the two groups (patients and healthy elderly subjects) in all the PCs, except for the PC3. Conclusions: The proposed method automatically assessed the severity of unwanted symptoms and could reasonably well discriminate between PD-specific and/or treatment-induced motor symptoms, in relation to visual assessments of movement disorder specialists. The objective assessments could provide a time-effect summary score that could be useful for improving decision-making during symptom evaluation of individualized treatment when the goal is to maximize functional On time for patients while minimizing their Off episodes and troublesome dyskinesias.

Automatic spiral analysis for objective assessment of motor symptoms in Parkinson's disease

A challenge for the clinical management of advanced Parkinson’s disease (PD) patients is the emergence of fluctuations in motor performance, which represents a significant source of disability during activities of daily living of the patients. There is a lack of objective measurement of treatment effects for in-clinic and at-home use that can provide an overview of the treatment response. The objective of this paper was to develop a method for objective quantification of advanced PD motor symptoms related to off episodes and peak dose dyskinesia, using spiral data gathered by a touch screen telemetry device. More specifically, the aim was to objectively characterize motor symptoms (bradykinesia and dyskinesia), to help in automating the process of visual interpretation of movement anomalies in spirals as rated by movement disorder specialists. Digitized upper limb movement data of 65 advanced PD patients and 10 healthy (HE) subjects were recorded as they performed spiral drawing tasks on a touch screen device in their home environment settings. Several spatiotemporal features were extracted from the time series and used as inputs to machine learning methods. The methods were validated against ratings on animated spirals scored by four movement disorder specialists who visually assessed a set of kinematic features and the motor symptom. The ability of the method to discriminate between PD patients and HE subjects and the test-retest reliability of the computed scores were also evaluated. Computed scores correlated well with mean visual ratings of individual kinematic features. The best performing classifier (Multilayer Perceptron) classified the motor symptom (bradykinesia or dyskinesia) with an accuracy of 84% and area under the receiver operating characteristics curve of 0.86 in relation to visual classifications of the raters. In addition, the method provided high discriminating power when distinguishing between PD patients and HE subjects as well as had good test-retest reliability. This study demonstrated the potential of using digital spiral analysis for objective quantification of PD-specific and/or treatment-induced motor symptoms.

Self-assessment of the outcome of early medical abortion versus clinic follow-up in India : a randomised, controlled, non-inferiority trial

Background: The need for multiple clinical visits remains a barrier to women accessing safe legal medical abortion services. Alternatives to routine clinic follow-up visits have not been assessed in rural low-resource settings. We compared the effectiveness of standard clinic follow-up versus home assessment of outcome of medical abortion in a low-resource setting. Methods: This randomised, controlled, non-inferiority trial was done in six health centres (three rural, three urban) in Rajasthan, India. Women seeking early medical abortion up to 9 weeks of gestation were randomly assigned (1:1) to either routine clinic follow-up or self-assessment at home. Randomisation was done with a computer-generated randomisation sequence, with a block size of six. The study was not blinded. Women in the home-assessment group were advised to use a pictorial instruction sheet and take a low-sensitivity urine pregnancy test at home, 10-14 days after intake of mifepristone, and were contacted by a home visit or telephone call to record the outcome of the abortion. The primary (non-inferiority) outcome was complete abortion without continuing pregnancy or need for surgical evacuation or additional mifepristone and misoprostol. The non-inferiority margin for the risk difference was 5%. All participants with a reported primary outcome and who followed the clinical protocol were included in the analysis. This study is registered with ClinicalTrials.gov, number NCT01827995. Findings: Between April 23, 2013, and May 15, 2014, 731 women were recruited and assigned to clinic follow-up (n=366) or home assessment (n=365), of whom 700 were analysed for the main outcomes (n=336 and n=364, respectively). Complete abortion without continuing pregnancy, surgical intervention, or additional mifepristone and misoprostol was reported in 313 (93%) of 336 women in the clinic follow-up group and 347 (95%) of 364 women in the home-assessment group (difference -2.2%, 95% CI -5.9 to 1.6). One case of haemorrhage occurred in each group (rate of adverse events 0.3% in each group); no other adverse events were noted. Interpretation Home assessment of medical abortion outcome with a low-sensitivity urine pregnancy test is non-inferior to clinic follow-up, and could be introduced instead of a clinic follow-up visit in a low-resource setting.