Computerized spiral analysis using the iPad

Upper limb intention tremor assessment: opportunities and challenges in wearable technology

BACKGROUND

Tremors are involuntary rhythmic movements commonly present in neurological diseases such as Parkinson's disease, essential tremor, and multiple sclerosis. Intention tremor is a subtype associated with lesions in the cerebellum and its connected pathways, and it is a common symptom in diseases associated with cerebellar pathology. While clinicians traditionally use tests to identify tremor type and severity, recent advancements in wearable technology have provided quantifiable ways to measure movement and tremor using motion capture systems, app-based tasks and tools, and physiology-based measurements. However, quantifying intention tremor remains challenging due to its changing nature.

METHODOLOGY & RESULTS

This review examines the current state of upper limb tremor assessment technology and discusses potential directions to further develop new and existing algorithms and sensors to better quantify tremor, specifically intention tremor. A comprehensive search using PubMed and Scopus was performed using keywords related to technologies for tremor assessment. Afterward, screened results were filtered for relevance and eligibility and further classified into technology type. A total of 243 publications were selected for this review and classified according to their type: body function level: movement-based, activity level: task and tool-based, and physiology-based. Furthermore, each publication's methods, purpose, and technology are summarized in the appendix table.

CONCLUSIONS

Our survey suggests a need for more targeted tasks to evaluate intention tremors, including digitized tasks related to intentional movements, neurological and physiological measurements targeting the cerebellum and its pathways, and signal processing techniques that differentiate voluntary from involuntary movement in motion capture systems.

Utilizing a tablet-based artificial intelligence system to assess movement disorders in a prospective study

Spiral drawings on paper are used as routine measures in hospitals to assess Parkinson's Disease motor deficiencies. In the age of emerging mobile health tools and Artificial Intelligence a comprehensive digital setup enables granular biomarker analyses and improved differential diagnoses in movement disorders. This study aims to evaluate on discriminatory features among Parkison's Disease patients, healthy subjects and diverse movement disorders. Overall, 24 Parkinson's Disease patients, 27 healthy controls and 26 patients with similar differential diagnoses were assessed with a novel tablet-based system. It utilizes an integrative assessment by combining a structured symptoms questionnaire-the Parkinson's Disease Non-Motor Scale-and 2-handed spiral drawing captured on a tablet device. Three different classification tasks were evaluated: Parkinson's Disease patients versus healthy control group (Task 1), all Movement disorders versus healthy control group (Task 2) and Parkinson's Disease patients versus diverse other movement disorder patients (Task 3). To systematically study feature importances of digital biomarkers a Machine Learning classifier is cross-validated and interpreted with SHapley Additive exPlanations (SHAP) values. The number of non-motor symptoms differed significantly for Tasks 1 and 2 but not for Task 3. The proposed drawing features partially differed significantly for all three tasks. The diagnostic accuracy was on average 94.0% in Task 1, 89.4% in Task 2, and 72% in Task 3. While the accuracy in Task 3 only using the symptom questionnaire was close to the baseline, it greatly improved when including the tablet-based features from 60 to 72%. The accuracies for all three tasks were significantly improved by integrating the two modalities. These results show that tablet-based drawing features can not only be captured by consumer grade devices, but also capture specific features to Parkinson's Disease that significantly improve the diagnostic accuracy compared to the symptom questionnaire. Therefore, the proposed system provides an objective type of disease characterization of movement disorders, which could be utilized for home-based assessments as well.Clinicaltrials.gov Study-ID: NCT03638479.

Characteristics of Drawing Process Differentiate Alzheimer’s Disease and Dementia with Lewy Bodies

Background: Early differential diagnosis of Alzheimer’s disease (AD) and dementia with Lewy bodies (DLB) is important for treatment and disease management, but it remains challenging. Although computer-based drawing analysis may help differentiate AD and DLB, it has not been extensively studied. Objective: We aimed to identify the differences in features characterizing the drawing process between AD, DLB, and cognitively normal (CN) individuals, and to evaluate the validity of using these features to identify and differentiate AD and DLB. Methods: We collected drawing data with a digitizing tablet and pen from 123 community-dwelling older adults in three clinical diagnostic groups of mild cognitive impairment or dementia due to AD (n = 47) or Lewy body disease (LBD; n = 27), and CN (n = 49), matched for their age, sex, and years of education. We then investigated drawing features in terms of the drawing speed, pressure, and pauses. Results: Reduced speed and reduced smoothness in speed and pressure were observed particularly in the LBD group, while increased pauses and total durations were observed in both the AD and LBD groups. Machine-learning models using these features achieved an area under the receiver operating characteristic curve (AUC) of 0.80 for AD versus CN, 0.88 for LBD versus CN, and 0.77 for AD versus LBD. Conclusion: Our results indicate how different types of drawing features were particularly discriminative between the diagnostic groups, and how the combination of these features can facilitate the identification and differentiation of AD and DLB.

Automated Analysis of Drawing Process to Estimate Global Cognition in Older Adults: Preliminary International Validation on the US and Japan Data Sets

BACKGROUND

With the aging of populations worldwide, early detection of cognitive impairments has become a research and clinical priority, particularly to enable preventive intervention for dementia. Automated analysis of the drawing process has been studied as a promising means for lightweight, self-administered cognitive assessment. However, this approach has not been sufficiently tested for its applicability across populations.

OBJECTIVE

The aim of this study was to evaluate the applicability of automated analysis of the drawing process for estimating global cognition in community-dwelling older adults across populations in different nations.

METHODS

We collected drawing data with a digital tablet, along with Montreal Cognitive Assessment (MoCA) scores for assessment of global cognition, from 92 community-dwelling older adults in the United States and Japan. We automatically extracted 6 drawing features that characterize the drawing process in terms of the drawing speed, pauses between drawings, pen pressure, and pen inclinations. We then investigated the association between the drawing features and MoCA scores through correlation and machine learning-based regression analyses.

RESULTS

We found that, with low MoCA scores, there tended to be higher variability in the drawing speed, a higher pause:drawing duration ratio, and lower variability in the pen's horizontal inclination in both the US and Japan data sets. A machine learning model that used drawing features to estimate MoCA scores demonstrated its capability to generalize from the US dataset to the Japan dataset (R2=0.35; permutation test, P<.001).

CONCLUSIONS

This study presents initial empirical evidence of the capability of automated analysis of the drawing process as an estimator of global cognition that is applicable across populations. Our results suggest that such automated analysis may enable the development of a practical tool for international use in self-administered, automated cognitive assessment.

Trsper: a web-based application for Archimedes spiral analysis

BACKGROUND

We built a web-based application of the Archimedes spiral exam that implements clinically validated spiral metrics and tested drawing instructions to define a clinical workflow.

METHODS

We designed an HTML5 and Javascript implementation of the spiral exam to run on mobile touchscreen devices. We then recruited 10 volunteers each for 2 experiments designed to validate the programmed spiral metrics and assess how instructions or drawing implement affect the results. In task one, volunteers drew 5 spirals each while following 6 different instruction sets (n=30 spirals each, n=300 spirals total) that varied by support of the drawing hand and tracing condition (either tracing a spiral template, drawing in-between it, or freehand). In task two, volunteers drew 5 spirals each while following 2 instruction sets and drawing using a stylus or their dominant index finger (n=20 spirals each, n=200 spirals total).

RESULTS

Principal components analysis of calculated metrics revealed that the experiments grouped by instruction set and by subject. Mean Euclidean distance between experiments represented as 11-dimensional vectors revealed that consistency varied among instruction tasks and that drawing with a stylus produced more consistent results than did using the dominant index finger. Using experimental data and simulated abnormal spirals, we designed a decision support system that accurately identifies potentially abnormal spirals.

CONCLUSIONS

We built and validated a robust digital implementation of the Archimedes spiral exam and recommend a sensitive and specific workflow on the basis of data gathered from healthy volunteers.

The Accuracy of a Screening System for Carpal Tunnel Syndrome Using Hand Drawing

When carpal tunnel syndrome (CTS), an entrapment neuropathy, becomes severe, thumb motion is reduced, which affects manual dexterity, such as causing difficulties in writing; therefore, early detection of CTS by screening is desirable. To develop a screening method for CTS, we developed a tablet app to measure the stylus trajectory and pressure of the stylus tip when drawing a spiral on a tablet screen using a stylus and, subsequently, used these data as training data to predict the classification of participants as non-CTS or CTS patients using a support vector machine. We recruited 33 patients with CTS and 31 healthy volunteers for this study. From our results, non-CTS and CTS were classified by our screening method with 82% sensitivity and 71% specificity. Our CTS screening method can facilitate the screening for potential patients with CTS and provide a quantitative assessment of CTS.

Drawing Direction Effect on a Task's Performance Characteristics among People with Essential Tremor

Essential tremor (ET) is a common movement disorder affecting the performance of various daily tasks, including drawing. While spiral-drawing task characteristics have been described among patients with ET, research about the significance of the drawing direction of both spiral and lines tasks on the performance process is scarce. This study mapped inter-group differences between people with ET and controls related to drawing directions and the intra-effect of the drawing directions on the tremor level among people with ET. Twenty participants with ET and eighteen without ET drew spirals and vertical and horizontal lines on a digitizer with an inking pen. Time-based outcome measures were gathered to address the effect of the drawing directions on tremor by analyzing various spiral sections and comparing vertical and horizontal lines. Significant group differences were found in deviation of the spiral radius from a filtered radius curve and in deviation of the distance curve from a filtered curve for both line types. Significant differences were found between defined horizontal and vertical spiral sections within each group and between both line types within the ET group. A significant correlation was found between spiral and vertical line deviations from filtered curve outcome measures. Achieving objective measures about the significance of drawing directions on actual performance may support the clinical evaluation of people with ET toward developing future intervention methods for improving their functional abilities.

Using computerized spiral analysis to evaluate deep brain stimulation outcomes in Parkinson disease

OBJECTIVE

To determine whether spiral analysis can monitor the effects of deep brain stimulation (DBS) in Parkinson disease (PD) and provide a window on clinical features that change post-operatively. Clinical evaluation after DBS is subjective and insensitive to small changes. Spiral analysis is a computerized test that quantifies kinematic, dynamic, and spatial aspects of spiral drawing. Validated computational indices are generated and correlate with a range of clinically relevant motor findings. These include measures of overall clinical severity (Severity), bradykinesia and rigidity (Smoothness), amount of tremor (Tremor), irregularity of drawing movements (Variability), and micrographia (Tightness).

METHODS

We retrospectively evaluated the effect of subthalamic nucleus (STN) (n = 66) and ventral intermediate thalamus (Vim) (n = 10) DBS on spiral drawing in PD subjects using spiral analysis. Subjects freely drew ten spirals on plain paper with an inking pen on a graphics tablet. Five spiral indices (Severity, Smoothness, Tremor, Variability, Tightness) were calculated and compared pre- and post-operatively using Wilcoxon-rank sum tests, adjusting for multiple comparisons.

RESULTS

Severity improved after STN and Vim DBS (p < 0.005). Smoothness (p < 0.01) and Tremor (p < 0.02) both improved after STN and Vim DBS. Variability improved only with Vim DBS. Neither STN nor Vim DBS significantly changed Tightness.

CONCLUSIONS

All major spiral indices, except Tightness, improved after DBS. This suggests spiral analysis monitors DBS effects in PD and provides an objective window on relevant clinical features that change post-operatively. It may thus have utilization in clinical trials or investigations into the neural pathways altered by DBS. The lack of change in Tightness supports the notion that DBS does not improve micrographia.

Wearable Peripheral Electrical Stimulation Devices for the Reduction of Essential Tremor: A Review

Essential tremor is the most common pathological tremor, with a prevalence of 6.3% in people over 65 years of age. This disorder interferes with a patient's ability to carry out activities of daily living independently, and treatment with medical and surgical interventions is often insufficient or contraindicated. Mechanical orthoses have not been widely adopted by patients due to discomfort and lack of discretion. Over the past 30 years, peripheral electrical stimulation has been investigated as a possible treatment for patients who have not found other treatment options to be satisfactory, with wearable devices revolutionizing this emerging approach in recent years. In this paper, an overview of essential tremor and its current medical and surgical treatment options are presented. Following this, tremor detection, measurement and characterization methods are explored with a focus on the measurement options that can be incorporated into wearable devices. Then, novel interventions for essential tremor are described, with a detailed review of open and closed-loop peripheral electrical stimulation methods. Finally, discussion of the need for wearable closed-loop peripheral electrical stimulation devices for essential tremor, approaches in their implementation, and gaps in the literature for further research are presented.

What the Tech? The Management of Neurological Dysfunction Through the Use of Digital Technology

Worldwide, it is estimated that millions of individuals suffer from a neurological disorder which can be the result of head injuries, ischaemic events such as a stroke, or neurodegenerative disorders such as Parkinson's disease (PD) and multiple sclerosis (MS). Problems with mobility and hemiparesis are common for these patients, making daily life, social factors and independence heavily affected. Current therapies aimed at improving such conditions are often tedious in nature, with patients often losing vital motivation and positive outlook towards their rehabilitation. The interest in the use of digital technology in neuro-rehabilitation has skyrocketed in the past decade. To gain insight, a systematic review of the literature in the field was conducting following the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA) guidelines for three categories: stroke, Parkinson's disease and multiple sclerosis. It was found that the majority of the literature (84%) was in favour of the use of digital technologies in the management of neurological dysfunction; with some papers taking a "neutral" or "against" standpoint. It was found that the use of technologies such as virtual reality (VR), robotics, wearable sensors and telehealth was highly accepted by patients, helped to improve function, reduced anxiety and make therapy more accessible to patients living in more remote areas. The most successful therapies were those that used a combination of conventional therapies and new digital technologies.

A Mobile Application for Smart Computer-Aided Self-Administered Testing of Cognition, Speech, and Motor Impairment

We present a model for digital neural impairment screening and self-assessment, which can evaluate cognitive and motor deficits for patients with symptoms of central nervous system (CNS) disorders, such as mild cognitive impairment (MCI), Parkinson's disease (PD), Huntington's disease (HD), or dementia. The data was collected with an Android mobile application that can track cognitive, hand tremor, energy expenditure, and speech features of subjects. We extracted 238 features as the model inputs using 16 tasks, 12 of them were based on a self-administered cognitive testing (SAGE) methodology and others used finger tapping and voice features acquired from the sensors of a smart mobile device (smartphone or tablet). Fifteen subjects were involved in the investigation: 7 patients with neurological disorders (1 with Parkinson's disease, 3 with Huntington's disease, 1 with early dementia, 1 with cerebral palsy, 1 post-stroke) and 8 healthy subjects. The finger tapping, SAGE, energy expenditure, and speech analysis features were used for neural impairment evaluations. The best results were achieved using a fusion of 13 classifiers for combined finger tapping and SAGE features (96.12% accuracy), and using bidirectional long short-term memory (BiLSTM) (94.29% accuracy) for speech analysis features.

A customizable tablet app for hand movement research outside the lab

BACKGROUND

Precise behavioral measurements allow the discovery of movement constraints that provide insights into sensory-motor processes and their underlying neural mechanisms. For instance, when humans draw an ellipse on a piece of paper, the instantaneous speed of the pen co-varies tightly with the local curvature of the path. Known as the speed-curvature power law, this phenomenon relates to fundamental questions of motor control.

NEW METHOD

We have developed a software app for displaying static curves or dynamic targets while recording finger or stylus movements on Android touch-screen tablets. Designed for human hand movement research, the app is free, ready-to-use, open-source and customizable.

RESULTS

We provide a template experimental protocol, and detailed explanations to use it and flexibly modify the code for different kinds of tasks. Our validation of the app demonstrates laboratory-quality results outside the laboratory. We also provide raw data and analysis scripts.

COMPARISON WITH EXISTING METHODS

Commonly used laboratory devices for recording hand movement trajectories are large, heavy and expensive. In turn, software apps are often not published, nor customizable. Our app running on tablets becomes an affordable, flexible, and portable tool suited for quantitative and robust behavioral studies with large number of participants and outside the laboratory (e.g. in a classroom, a hospital, or at home).

CONCLUSIONS

The affordability, flexibility, and resolution of our tablet app provide an effective tool to study behavior quantitatively in the real world.

Quantitative Assessment of Finger Movement Profile in a Visual-Motor Task Based on a Tablet Computer: The Application in Parkinson's Disease

BACKGROUND/OBJECTIVE

Easily applicable, quantitative assessment of movement is widely needed in various clinical settings, especially in the evaluation of Parkinson's disease (PD).

METHODS

We developed a highly repeatable tablet computer-based finger movement assessment system (FMAS) to record finger movement profile in a visual-motor task both in PD (n = 217) and healthy participants (n = 221).

RESULTS

We found age-related declines in finger movement performance among the healthy participants but not in PD patients with the FMAS. Significant differences in movement time (MT) and latency/MT ratio but not in latency were observed in PD patients as compared with healthy subjects (P < 0.000). Meanwhile, we identified the latency/MT ratio as the optimal parameter to differentiate PD from age-matched healthy subjects in an age-independent manner (cut-off 1.08 with corresponding AUC = 0.861). In addition, a significant correlation was found between finger movement parameters and the Hoehn and Yahr scale (H-Y scale), UPDRS III score and the duration of the disease in PD patients (P < 0.01).

CONCLUSION

It was suggested that the tablet computer-based evaluation of finger movement provided an easily applicable quantitative method to assess the conditions of PD patients.

A Randomized Crossover Pilot Study of Telemedicine Delivered via iPads in Parkinson's Disease

Background

We investigated the feasibility and safety of a video-based telemedicine system, delivered via a tablet, in Parkinson's disease (PD).

Methods

In a randomized, crossover, open-label pilot trial, we compared a telemedicine period (regular visits every two months with intermediate video calls via an iPad mini) with a control period (regular visits every two months), both lasting 6 months. We included 10 patients diagnosed with PD according to the British Brain Bank criteria, aged 20–75 years. The primary outcome was the PD questionnaire summary index (PDQ-39 SI). Secondary outcomes included the Hoehn and Yahr Stage and scores on the Unified PD Rating Scale (UPDRS) part I–IV, Beck Depression Inventory (BDI), and visual analog scale for satisfaction.

Results

Both study periods were completed by 10 patients with PD. Friedman's test revealed that there were no significant differences between the two periods in primary and secondary outcomes (p > 0.05). With respect to visual analog scale scores for satisfaction, participants indicated high satisfaction with the telemedicine system. The number of extra hospital visits and phone calls did not differ between the periods. There were no adverse events or side effects.

Conclusions

We observed that a telemedicine system delivered via a tablet could successfully be used by patients as a part of their care. Further studies investigating the use of telemedicine to replace in-person visits are warranted. This trial is registered with UMIN000015536.

Current behavioral assessments of movement disorders in children

Pediatric movement disorders (PMDs) are common and have recently received increasing attention. As these disorders have special clinical features, the selection of appropriate behavioral assessment tools that can clearly distinguish movement disorders from other diseases (eg, epilepsy and neuromuscular disorders) is crucial for achieving an accurate diagnosis and treatment. However, few studies have focused on behavioral assessments in children. The present report attempts to provide a critical review of the available subjective and objective assessment tests for common PMDs. We believe that the principles of objectification, multi-purpose use, and simplification are also applicable to the selection and development of satisfactory pediatric behavioral assessment tools. We expect that the development of wearable sensors, virtual reality, and augmented reality will lead to the establishment of more reliable and simple tests. In addition, more rigorous randomized controlled trials that have been specifically designed to evaluate behavioral testing in children are also expected in the future.

Automatic Analysis of Archimedes' Spiral for Characterization of Genetic Essential Tremor Based on Shannon's Entropy and Fractal Dimension

Among neural disorders related to movement, essential tremor has the highest prevalence; in fact, it is twenty times more common than Parkinson's disease. The drawing of the Archimedes' spiral is the gold standard test to distinguish between both pathologies. The aim of this paper is to select non-linear biomarkers based on the analysis of digital drawings. It belongs to a larger cross study for early diagnosis of essential tremor that also includes genetic information. The proposed automatic analysis system consists in a hybrid solution: Machine Learning paradigms and automatic selection of features based on statistical tests using medical criteria. Moreover, the selected biomarkers comprise not only commonly used linear features (static and dynamic), but also other non-linear ones: Shannon entropy and Fractal Dimension. The results are hopeful, and the developed tool can easily be adapted to users; and taking into account social and economic points of view, it could be very helpful in real complex environments.

The difference in visuomotor feedback velocity control during spiral drawing between Parkinson's disease and essential tremor

In a spiral task, the accuracy of the spiral trajectory, which is affected by tracing or tracking ability, differs between patients with Parkinson's disease (PD) and essential tremor (ET). However, not many studies have analyzed velocity differences between the groups during this task. This study aimed to examine differences between the groups related to this characteristic using a tablet. Fourteen PD, 12 ET, and 12 control group participants performed two tasks: tracing a given spiral (T1) and following a guiding point (T2). A digitized tablet was used to record movements and trajectory. Effects of direct visual feedback on intergroup and intragroup velocity were measured. Although PD patients had a significantly lower T1 velocity than the control group (p < 0.05), they could match the velocity of the guiding point (3.0 cm/s) in T2. There was no significant difference in the average T1 velocity between ET and the control groups (p = 0.26); however, the T2 velocity of ET patients was significantly higher than the control group (p < 0.05). They were also unable to adjust the velocity to match the guiding point, indicating that ET patients have a poorer ability to follow dynamic guidance. When both groups of patients have similar action tremor severity, their ability to follow dynamic guidance was still significantly different. Our study combined visual feedback with spiral drawing and demonstrated differences in the following-velocity distribution in PD and ET. This method may be used to distinguish the tremor presentation of both diseases, and thus, provide accurate diagnosis.

The effect of fidget spinners on fine motor control

Fidgeting, defined as the generation of small movements through nervousness or impatience, is one of cardinal characteristic of ADHD. While fidgeting is, by definition, a motor experience still nothing is known about the effects of fidgeting on motor control. Some forms of fidgeting involve also the manipulation of external objects which, through repetition, may become automatic and second nature. Both repetition and practice are important for the acquisition of motor skills and, therefore, it is plausible that the repetitive manipulation of objects may influence motor control and performance. As such, fidget spinners, by being diffuse and prone to repetitive usage, may represent interesting tool for improving motor control. In this study we examine the effect of fidget spinners on fine motor control, evaluated by a spiral-tracing task. We show that the use of fidget spinner indeed seems to have a favorable effect on fine motor control, at least in the short term, although this effect does not seem to be in any way inherent to fidget spinners themselves as much as to object manipulation in general. However, due to their widespread usage, fidget spinner may have the advantage of being an enjoyable means for improving fine motor control.

Verification of a Method for Measuring Parkinson's Disease Related Temporal Irregularity in Spiral Drawings

Parkinson’s disease (PD) is a progressive movement disorder caused by the death of dopamine-producing cells in the midbrain. There is a need for frequent symptom assessment, since the treatment needs to be individualized as the disease progresses. The aim of this paper was to verify and further investigate the clinimetric properties of an entropy-based method for measuring PD-related upper limb temporal irregularities during spiral drawing tasks. More specifically, properties of a temporal irregularity score (TIS) for patients at different stages of PD, and medication time points were investigated. Nineteen PD patients and 22 healthy controls performed repeated spiral drawing tasks on a smartphone. Patients performed the tests before a single levodopa dose and at specific time intervals after the dose was given. Three movement disorder specialists rated videos of the patients based on the unified PD rating scale (UPDRS) and the Dyskinesia scale. Differences in mean TIS between the groups of patients and healthy subjects were assessed. Test-retest reliability of the TIS was measured. The ability of TIS to detect changes from baseline (before medication) to later time points was investigated. Correlations between TIS and clinical rating scores were assessed. The mean TIS was significantly different between healthy subjects and patients in advanced groups (p-value = 0.02). Test-retest reliability of TIS was good with Intra-class Correlation Coefficient of 0.81. When assessing changes in relation to treatment, TIS contained some information to capture changes from Off to On and wearing off effects. However, the correlations between TIS and clinical scores (UPDRS and Dyskinesia) were weak. TIS was able to differentiate spiral drawings drawn by patients in an advanced stage from those drawn by healthy subjects, and TIS had good test-retest reliability. TIS was somewhat responsive to single-dose levodopa treatment. Since TIS is an upper limb high-frequency-based measure, it cannot be detected during clinical assessment.

Computer-based assessment of upper-limb incoordination in autosomal recessive spastic ataxia of Charlevoix-Saguenay patients: A pilot study

Ataxia refers to a group of neurological disorders characterized by a lack of coordination during voluntary movements. One of the most commonly used tests to assess upper-limb coordination is the Archimedes spiral test. The purpose of this research is to present an innovative computer-based Archimedes spiral test that can accurately assess coordination. Forty nine individuals (age: 25.2±7.1years) were recruited including thirteen patients diagnosed with Autosomal Recessive Spastic Ataxia of Charlevoix/Saguenay (ARSACS). Participants were instructed to trace a spiral on the touch-screen with the tip of their index finger at a self-paced velocity by following an on-screen spiral template. Mean error and maximum error as well as frequency analysis were calculated to classify healthy and ARSACS participants. While mean and maximum errors provided good results, the highest classification success rate was obtained using frequency analysis, particularly between f=1.2Hz and f=1.7Hz. Interpretation of traditional paper-drawn Archimedes spirals is limited, and several computerized versions have been reported. Herein, we present a custom-made tool that allows discrimination of measures assessing ataxia in ARSACS. This utilizes a proposed frequency method that may have the potential to track the evolution of upper-limb incoordination in patients and therefore help clinicians and scientists to better monitor their patients.

Distinguishing Different Stages of Parkinson's Disease Using Composite Index of Speed and Pen-Pressure of Sketching a Spiral

The speed and pen-pressure while sketching a spiral are lower among Parkinson’s disease (PD) patients with higher severity of the disease. However, the correlation between these features and the severity level (SL) of PD has been reported to be 0.4. There is a need for identifying parameters with a stronger correlation for considering this for accurate diagnosis of the disease. This study has proposed the use of the Composite Index of Speed and Pen-pressure (CISP) of sketching as a feature for analyzing the severity of PD. A total of 28 control group (CG) and 27 PD patients (total 55 participants) were recruited and assessed for Unified Parkinson’s Disease Rating Scale (UPDRS). They drew guided Archimedean spiral on an A3 sheet. Speed, pen-pressure, and CISP were computed and analyzed to obtain their correlation with severity of the disease. The correlation of speed, pen-pressure, and CISP with the severity of PD was −0.415, −0.584, and −0.641, respectively. Mann–Whitney U test confirmed that CISP was suitable to distinguish between PD and CG, while non-parametric k-sample Kruskal–Wallis test confirmed that it was significantly different for PD SL-1 and PD SL-3. This shows that CISP during spiral sketching may be used to differentiate between CG and PD and between PD SL-1 and PD SL-3 but not SL-2.

New insight in spiral drawing analysis methods - Application to action tremor quantification

OBJECTIVE

Spiral drawing is one of the standard tests used to assess tremor severity for the clinical evaluation of medical treatments. Tremor severity is estimated through visual rating of the drawings by movement disorders experts. Different approaches based on the mathematical signal analysis of the recorded spiral drawings were proposed to replace this rater dependent estimate. The objective of the present study is to propose new numerical methods and to evaluate them in terms of agreement with visual rating and reproducibility.

METHODS

Series of spiral drawings of patients with essential tremor were visually rated by a board of experts. In addition to the usual velocity analysis, three new numerical methods were tested and compared, namely static and dynamic unraveling, and empirical mode decomposition. The reproducibility of both visual and numerical ratings was estimated, and their agreement was evaluated.

RESULTS

The statistical analysis demonstrated excellent agreement between visual and numerical ratings, and more reproducible results with numerical methods than with visual ratings.

CONCLUSIONS

The velocity method and the new numerical methods are in good agreement. Among the latter, static and dynamic unravelling both display a smaller dispersion and are easier for automatic analysis.

SIGNIFICANCE

The reliable scores obtained through the proposed numerical methods allow considering that their implementation on a digitized tablet, be it connected with a computer or independent, provides an efficient automatic tool for tremor severity assessment.