Quantitative Oculomotor Assessment in Hereditary Ataxia: Discriminatory Power, Correlation with Severity Measures, and Recommended Parameters for Specific Genotypes

Characterizing bedside oculomotor deficits is a critical factor in defining the clinical presentation of hereditary ataxias. Quantitative assessments are increasingly available and have significant advantages, including comparability over time, reduced examiner dependency, and sensitivity to subtle changes. To delineate the potential of quantitative oculomotor assessments as digital-motor outcome measures for clinical trials in ataxia, we searched MEDLINE for articles reporting on quantitative eye movement recordings in genetically confirmed or suspected hereditary ataxias, asking which paradigms are most promising for capturing disease progression and treatment response. Eighty-nine manuscripts identified reported on 1541 patients, including spinocerebellar ataxias (SCA2, n = 421), SCA3 (n = 268), SCA6 (n = 117), other SCAs (n = 97), Friedreich ataxia (FRDA, n = 178), Niemann-Pick disease type C (NPC, n = 57), and ataxia-telangiectasia (n = 85) as largest cohorts. Whereas most studies reported discriminatory power of oculomotor assessments in diagnostics, few explored their value for monitoring genotype-specific disease progression (n = 2; SCA2) or treatment response (n = 8; SCA2, FRDA, NPC, ataxia-telangiectasia, episodic-ataxia 4). Oculomotor parameters correlated with disease severity measures including clinical scores (n = 18 studies (SARA: n = 9)), chronological measures (e.g., age, disease duration, time-to-symptom onset; n = 17), genetic stratification (n = 9), and imaging measures of atrophy (n = 5). Recurrent correlations across many ataxias (SCA2/3/17, FRDA, NPC) suggest saccadic eye movements as potentially generic quantitative oculomotor outcome. Recommendation of other paradigms was limited by the scarcity of cross-validating correlations, except saccadic intrusions (FRDA), pursuit eye movements (SCA17), and quantitative head-impulse testing (SCA3/6). This work aids in understanding the current knowledge of quantitative oculomotor parameters in hereditary ataxias, and identifies gaps for validation as potential trial outcome measures in specific ataxia genotypes.

Patient-Related Outcome Measures for Oculomotor Symptoms in the Cerebellar Ataxias: Insights from Non-Cerebellar Disorders

In patients with cerebellar ataxia (CA), symptoms related to oculomotor dysfunction significantly affect quality of life (QoL). This study aimed to analyze the literature on patient-related outcome measures (PROMs) assessing QoL impacts of vestibular and cerebellar oculomotor abnormalities in patients with CA to identify the strengths and limitations of existing scales and highlight any areas of unmet need. A systematic review was conducted (Medline, Embase) of English-language original articles reporting on QoL measures in patients with vertigo, dizziness or CA. Pre-specified parameters were retrieved, including diseases studied, scales applied and conclusions drawn. Our search yielded 3671 articles of which 467 studies (n = 111,606 participants) were deemed relevant. The most frequently studied disease entities were (a) non-specific dizziness/gait imbalance (114 studies; 54,581 participants), (b) vestibular schwannomas (66; 15,360), and (c) vestibular disorders not further specified (66; 10,259). The Dizziness Handicap Inventory (DHI) was the most frequently used PROM to assess QoL (n = 91,851), followed by the Penn Acoustic Neuroma Quality-of-Life Scale (n = 12,027) and the Activities-Specific Balance Confidence Scale (n = 2'471). QoL-scores capturing symptoms related to oculomotor abnormalities in CA were rare, focused on visual impairments (e.g., National-Eye-Institute Visual Function Questionnaire, Oscillopsia Functional Impact, oscillopsia severity score) and were unvalidated. The DHI remains the most widely used and versatile scale for evaluating dizziness. A lack of well-established PROMs for assessing the impact of oculomotor-related symptoms on QoL in CA was noted, emphasizing the need for developing and validating a new QoL-score dedicated to the oculomotor domain for individuals with CA.

Bilateral vestibulopathy: a clinical update and proposed diagnostic algorithm

Bilateral vestibulopathy (BVP) is characterized by its heterogeneous and chronic nature with various clinical presentations and multiple etiologies. This current narrative review reflects on the main insights and developments regarding clinical presentation. In addition, it proposes a new diagnostic algorithm, and describes available and potential future therapeutic modalities.

Machine Learning-Based Scoring System to Predict the Risk and Severity of Ataxic Speech Using Different Speech Tasks

The assessment of speech in Cerebellar Ataxia (CA) is time-consuming and requires clinical interpretation. In this study, we introduce a fully automated objective algorithm that uses significant acoustic features from time, spectral, cepstral, and non-linear dynamics present in microphone data obtained from different repeated Consonant-Vowel (C-V) syllable paradigms. The algorithm builds machine-learning models to support a 3-tier diagnostic categorisation for distinguishing Ataxic Speech from healthy speech, rating the severity of Ataxic Speech, and nomogram-based supporting scoring charts for Ataxic Speech diagnosis and severity prediction. The selection of features was accomplished using a combination of mass univariate analysis and elastic net regularization for the binary outcome, while for the ordinal outcome, Spearman's rank-order correlation criterion was employed. The algorithm was developed and evaluated using recordings from 126 participants: 65 individuals with CA and 61 controls (i.e., individuals without ataxia or neurotypical). For Ataxic Speech diagnosis, the reduced feature set yielded an area under the curve (AUC) of 0.97 (95% CI 0.90-1), the sensitivity of 97.43%, specificity of 85.29%, and balanced accuracy of 91.2% in the test dataset. The mean AUC for severity estimation was 0.74 for the test set. The high C-indexes of the prediction nomograms for identifying the presence of Ataxic Speech (0.96) and estimating its severity (0.81) in the test set indicates the efficacy of this algorithm. Decision curve analysis demonstrated the value of incorporating acoustic features from two repeated C-V syllable paradigms. The strong classification ability of the specified speech features supports the framework's usefulness for identifying and monitoring Ataxic Speech.

A patient with neuropathy and ataxia: what do I have to consider?

PURPOSE OF REVIEW

An increasing number of peripheral neuro(no)pathies are identified as involving other components of the neurological system, particularly those that further impair balance. Here we aim to outline an evidence-based approach to the diagnosis of patients who present with a somatosensory disorder which also involves at least one other area of neurological impairment such as the vestibular, auditory, or cerebellar systems.

RECENT FINDINGS

Detailed objective investigation of patients who present with sensory impairment, particularly where the degree of imbalance is greater than would be expected, aids the accurate diagnosis of genetic, autoimmune, metabolic, and toxic neurological disease.

SUMMARY

Diagnosis and management of complex somatosensory disorders benefit from investigation which extends beyond the presenting sensory impairment.

Interrater Reliability of the Scale for the Assessment and Rating of Ataxia, Berg Balance Scale, and Functional Independence Measure Motor Domain in Individuals With Hereditary Cerebellar Ataxia

OBJECTIVE

To determine the interrater reliability of the Scale for the Assessment and Rating of Ataxia (SARA), Berg Balance Scale (BBS), and motor domain of the FIM (m-FIM) administered by physiotherapists in individuals with a hereditary cerebellar ataxia (HCA).

DESIGN

Participants were assessed by 1 of 4 physiotherapists. Assessments were video-recorded and the remaining 3 physiotherapists scored the scales for each participant. Raters were blinded to each other's scores.

SETTING

Assessments were administered at 3 clinical locations in separate states in Australia.

PARTICIPANTS

Twenty-one individuals (mean age=47.63 years; SD=18.42; 13 male and 8 female) living in the community with an HCA were recruited (N=21).

MAIN OUTCOME MEASURES

Total and single-item scores of the SARA, BBS, and m-FIM were examined. The m-FIM was conducted by interview.

RESULTS

Intraclass coefficients (2,1) for the total scores of the m-FIM (0.92; 95% confidence interval [CI], 0.85-0.96), SARA (0.92; 95% CI, 0.86-0.96), and BBS (0.99; 95% CI, 0.98-0.99) indicated excellent interrater reliability. However, there was inconsistent agreement with the individual items, with SARA item 5 (right side) and item 7 (both sides) demonstrating poor interrater reliability and items 1 and 2 demonstrating excellent reliability.

CONCLUSIONS

The m-FIM (by interview), SARA, and BBS have excellent interrater reliability for use when assessing individuals with an HCA. Physiotherapists could be considered for administration of the SARA in clinical trials. However, further work is required to improve the agreement of the single-item scores and to examine the other psychometric properties of these scales.

A Bayesian Network Approach for Friedreich Ataxia Severity Classification using Probability Modelling

Friedreich ataxia (FRDA) requires an objective measure of severity to overcome the shortcoming of clinical scales when applied to trials for treatments. This is hindered due to the rarity of the disease resulting in small datasets. Further, the published quantitative measures for ataxia do not incorporate or underutilise expert knowledge. Bayesian Networks (BNs) provide a structure to adopt both subjective and objective measures to give a severity value while addressing these issues. The BN presented in this paper uses a hybrid learning approach, which utilises both subjective clinical assessments as well as instrumented measurements of disordered upper body movement of individuals with FRDA. The final model's estimates gave a 0.93 Pearson correlation with low error, 9.42 root mean square error and 7.17 mean absolute error. Predicting the clinical scales gave 94% accuracy for Upright Stability and Lower Limb Coordination and 67% accuracy for Functional Staging, Upper Limb Coordination and Activities of Daily Living.Clinical relevance- Due to the nature of rare diseases conventional machine learning is difficult. Most clinical trials only generate small datasets. This approach allows the combination of expert knowledge with instrumented measures to develop a clinical decision support system for the prediction of severity.

A Study of Upper-Limb Motion using Kinematic Measures for Clinical Assessment of Cerebellar Ataxia

Cerebellar Ataxia (CA) is a group of diseases affecting the cerebellum, which is responsible for movement coordination. It causes uncoordinated movements and can also impact balance, speech, and eye movements. There are no approved disease-modifying medications for CA, so clinical studies to assess potential treatments are crucial. These studies require robust, objective measurements of CA severity to reflect changes in the progression of the disease due to medication. In recent years, studies have used kinematic measures to evaluate CA severity, but the current method relies on subjective clinical observations and is insufficient for telehealth. There is a need for a non-intrusive system that can monitor people with CA regularly to better understand the disease and develop an automated assessment system. In this study, we analyzed kinematic measures of upper-limb movements during a ballistic tracking test, which primarily involves movements at the shoulder joint. We aimed to understand the challenges of identifying CA and evaluating its severity when measuring such movements. Statistical features of the kinematic signals were used to develop machine learning models for classification and regression. The Gradient Boosting Classifier model had a maximum accuracy of 74%, but the models had low specificity and performed poorly in regression, suggesting that kinematic measures from shoulder-dominated movements during ballistic tracking are not as viable for CA assessment as other measures.

Machine Learning Based Diagnosis of Vertigo using Video Head Impulse Test

This work utilises the strength of state space based dynamic modelling and the ability of machine learning based segmentation of SRM standard descriptors to reach superior diagnostic capabilities. Dynamic modelling ensured vHIT input-output characteristics generated SRM standard descriptors, which were consequently used in formation of ML classification models.The best ML model was Linear SVM when built on left and right sided data with the SRM standard descriptors: rise time, settling time, settling minimum, settling maximum, overshoot and undershoot. The model was able to classify individuals to patient or control groups with an accuracy of 100% and a sensitivity and specificity of 1.Clinical Relevance- Dizziness is one of the most common presentations to family physicians and emergency departments. It is associated with significant medical complications such as falls as well as economic costs to both the individual and the community. Vestibular diseases comprise the bulk of dizzy disorders and are often associated with dysfunction of the vestibular or inner ear balance apparatus. This is most commonly the result of hypo-function of the semi-circular canals. Clinically, the most commonly employed objective test of semicircular function is the video Head Impulse Test (vHIT). Here we provide a machine learning approach to a more comprehensible and accurate interpretation of the results obtained by the vHIT to more robustly establish the presence and severity of VOR dysfunction, and ultimately aid in the diagnosis of vestibular disorders.

A Novel Feature from Instrumented Utensils for Clinical Assessment of Friedreich Ataxia

Friedreich Ataxia (FRDA) is an inherited disorder that affects the cerebellum and other regions of the human nervous system. It causes impaired movement that affects quality and reduces lifespan. Clinical assessment of movement is a key part of diagnosis and assessment of severity. Recent studies have examined instrumented measurement of movement to support clinical assessments. This paper presents a frequency domain approach based on Average Band Power (ABP) estimation for clinical assessment using Inertial Measurement Unit (IMU) signals. The IMUs were attached to a 3D printed spoon and a cup. Participants used them to mimic eating and drinking activities during data collection. For both activities, the ABP of frequency components from individuals with FRDA clustered in 0 to 0.2Hz band. This suggests that the ABP of this frequency is affected by FRDA irrespective of the device or activity. The ABP in this frequency band was used to distinguish between FRDA and non-ataxic participants using the Area Under the Receiver-Operating-Characteristic Curve (AUC) which produced peak values greater than 0.8. The machine learning models (logistic regression and neural networks) produced accuracy greater than 80% with these features common to both devices.

Modified Recurrence Quantification Analysis for Objective Assessment of Cerebellar Ataxia

Cerebellar Ataxia (CA) is a neurological condition that affects coordination, balance and speech. Assessing its severity is important for developing effective treatment and rehabilitation plans. Traditional assessment methods involve a clinician instructing a person with ataxia to perform tests and assigning a severity score based on their performance. However, this approach is subjective as it relies on the clinician's experience, and can vary between clinicians. To address this subjectivity, some researchers have developed automated assessment methods using signal processing and data-driven approaches, such as supervised machine learning. These methods still rely on subjective ground truth and can perform poorly in real-world scenarios. This research proposed an alternative approach that uses signal processing to modify recurrence plots and compare the severity of ataxia in a person with CA to a control cohort. The highest correlation score obtained was 0.782 on the back sensor with the feet-apart and eyes-open test. The contributions of the research include modifying the recurrence plot as a measurement tool for assessing CA severity, proposing a new approach to assess severity by comparing kinematic data between people with CA and a control reference group, and identifying the best subtest and sensor position for practical use in CA assessments.

Quantitative Oculomotor Assessment in Hereditary Ataxia: Systematic Review and Consensus by the Ataxia Global Initiative Working Group on Digital-motor Biomarkers

Oculomotor deficits are common in hereditary ataxia, but disproportionally neglected in clinical ataxia scales and as outcome measures for interventional trials. Quantitative assessment of oculomotor function has become increasingly available and thus applicable in multicenter trials and offers the opportunity to capture severity and progression of oculomotor impairment in a sensitive and reliable manner. In this consensus paper of the Ataxia Global Initiative Working Group On Digital Oculomotor Biomarkers, based on a systematic literature review, we propose harmonized methodology and measurement parameters for the quantitative assessment of oculomotor function in natural-history studies and clinical trials in hereditary ataxia. MEDLINE was searched for articles reporting on oculomotor/vestibular properties in ataxia patients and a study-tailored quality-assessment was performed. One-hundred-and-seventeen articles reporting on subjects with genetically confirmed (n=1134) or suspected hereditary ataxia (n=198), and degenerative ataxias with sporadic presentation (n=480) were included and subject to data extraction. Based on robust discrimination from controls, correlation with disease-severity, sensitivity to change, and feasibility in international multicenter settings as prerequisite for clinical trials, we prioritize a core-set of five eye-movement types: (i) pursuit eye movements, (ii) saccadic eye movements, (iii) fixation, (iv) eccentric gaze holding, and (v) rotational vestibulo-ocular reflex. We provide detailed guidelines for their acquisition, and recommendations on the quantitative parameters to extract. Limitations include low study quality, heterogeneity in patient populations, and lack of longitudinal studies. Standardization of quantitative oculomotor assessments will facilitate their implementation, interpretation, and validation in clinical trials, and ultimately advance our understanding of the evolution of oculomotor network dysfunction in hereditary ataxias.

An intronic GAA repeat expansion in FGF14 causes the autosomal-dominant adult-onset ataxia SCA50/ATX-FGF14

Adult-onset cerebellar ataxias are a group of neurodegenerative conditions that challenge both genetic discovery and molecular diagnosis. In this study, we identified an intronic (GAA) repeat expansion in fibroblast growth factor 14 (FGF14). Genetic analysis of 95 Australian individuals with adult-onset ataxia identified four (4.2%) with (GAA)_>300 and a further nine individuals with (GAA)_>250. PCR and long-read sequence analysis revealed these were pure (GAA) repeats. In comparison, no control subjects had (GAA)_>300 and only 2/311 control individuals (0.6%) had a pure (GAA)_>250. In a German validation cohort, 9/104 (8.7%) of affected individuals had (GAA)_>335 and a further six had (GAA)_>250, whereas 10/190 (5.3%) control subjects had (GAA)_>250 but none were (GAA)_>335. The combined data suggest (GAA)_>335 are disease causing and fully penetrant (p = 6.0 × 10^-8, OR = 72 [95% CI = 4.3-1,227]), while (GAA)_>250 is likely pathogenic with reduced penetrance. Affected individuals had an adult-onset, slowly progressive cerebellar ataxia with variable features including vestibular impairment, hyper-reflexia, and autonomic dysfunction. A negative correlation between age at onset and repeat length was observed (R² = 0.44, p = 0.00045, slope = -0.12) and identification of a shared haplotype in a minority of individuals suggests that the expansion can be inherited or generated de novo during meiotic division. This study demonstrates the power of genome sequencing and advanced bioinformatic tools to identify novel repeat expansions via model-free, genome-wide analysis and identifies SCA50/ATX-FGF14 as a frequent cause of adult-onset ataxia.

The Electrophysiological Findings in Spinocerebellar Ataxia Type 6: Evidence From 24 Patients

PURPOSE

Peripheral neuropathy has been reported commonly in several spinocerebellar ataxia (SCA) types. To date, there is a lack of robust evidence for neuropathy or neuronopathy in SCA type 6 (SCA6). Here, we aim to evaluate the presence of neuropathy or neuronopathy in a cohort of SCA6 patients.

METHODS

Twenty-four individuals with genetically confirmed SCA6 underwent detailed neurophysiological assessment. This included nerve conduction studies, and in some, cutaneous silent periods, blink reflexes, tilt table tests, quantitative sudomotor axon reflex tests, and somatosensory (median and tibial) evoked potentials.

RESULTS

Mean age was 56.1 years (range, 22-94 years) at the time of testing. Four patients were presymptomatic of SCA6 at recruitment. The mean disease duration of symptomatic patients was 11.9 years (range, 1-40 years). Most patients (79.2%, 19/24) had no neurophysiological evidence of a peripheral neuropathy. One with impaired glucose tolerance had mild, large, and small fiber sensorimotor polyneuropathy. One elderly patient had length-dependent axonal sensorimotor polyneuropathy. Two had minor sensory abnormalities (one had type II diabetes and previous chemotherapy). One other had minor small fiber abnormalities. Ten patients (41.7%) had median neuropathies at the wrist. All somatosensory evoked potential (15/15), and most autonomic function tests (13/14) were normal.

CONCLUSIONS

A large proportion of subjects (79.2%) in our cohort had no evidence of large or small fiber neuropathy. This study does not support the presence of neuropathy or neuronopathy as a common finding in SCA6 and confirms the importance of considering comorbidities as the cause of neurophysiological abnormalities.

Clinical management guidelines for Friedreich ataxia: best practice in rare diseases

BACKGROUND

Individuals with Friedreich ataxia (FRDA) can find it difficult to access specialized clinical care. To facilitate best practice in delivering healthcare for FRDA, clinical management guidelines (CMGs) were developed in 2014. However, the lack of high-certainty evidence and the inadequacy of accepted metrics to measure health status continues to present challenges in FRDA and other rare diseases. To overcome these challenges, the Grading of Recommendations Assessment and Evaluation (GRADE) framework for rare diseases developed by the RARE-Bestpractices Working Group was adopted to update the clinical guidelines for FRDA. This approach incorporates additional strategies to the GRADE framework to support the strength of recommendations, such as review of literature in similar conditions, the systematic collection of expert opinion and patient perceptions, and use of natural history data.

METHODS

A panel representing international clinical experts, stakeholders and consumer groups provided oversight to guideline development within the GRADE framework. Invited expert authors generated the Patient, Intervention, Comparison, Outcome (PICO) questions to guide the literature search (2014 to June 2020). Evidence profiles in tandem with feedback from individuals living with FRDA, natural history registry data and expert clinical observations contributed to the final recommendations. Authors also developed best practice statements for clinical care points that were considered self-evident or were not amenable to the GRADE process.

RESULTS

Seventy clinical experts contributed to fifteen topic-specific chapters with clinical recommendations and/or best practice statements. New topics since 2014 include emergency medicine, digital and assistive technologies and a stand-alone section on mental health. Evidence was evaluated according to GRADE criteria and 130 new recommendations and 95 best practice statements were generated.

DISCUSSION AND CONCLUSION

Evidence-based CMGs are required to ensure the best clinical care for people with FRDA. Adopting the GRADE rare-disease framework enabled the development of higher quality CMGs for FRDA and allows individual topics to be updated as new evidence emerges. While the primary goal of these guidelines is better outcomes for people living with FRDA, the process of developing the guidelines may also help inform the development of clinical guidelines in other rare diseases.

Overview of the Clinical Approach to Individuals With Cerebellar Ataxia and Neuropathy

Increasingly, cerebellar syndromes are recognized as affecting multiple systems. Extracerebellar features include peripheral neuropathies affecting proprioception; cranial neuropathies such as auditory and vestibular; and neuronopathies, for example, dorsal root and vestibular. The presence of such features, which in and of themselves may cause ataxia, likely contribute to key disabilities such as gait instability and falls. Based on the evolving available literature and experience, we outline a clinical approach to the diagnosis of adult-onset ataxia where a combination of cerebellar and peripheral or cranial nerve pathology exists. Objective diagnostic modalities including electrophysiology, oculomotor, and vestibular function testing are invaluable in accurately defining an individual's phenotype. Advances in MRI techniques have led to an increased recognition of disease-specific patterns of cerebellar pathology, including those conditions where neuronopathies may be involved. Depending on availability, a stepwise approach to genetic testing is suggested. This is guided by factors such as pattern of inheritance and age at disease onset, and genetic testing may range from specific genetic panels through to whole-exome and whole-genome sequencing. Management is best performed with the involvement of a multidisciplinary team, aiming at minimization of complications such as falls and aspiration pneumonia and maximizing functional status.

RFC1-Related Disease

In 2019, a biallelic pentanucleotide repeat expansion in the gene encoding replication factor C subunit 1 (RFC1) was reported as a cause of cerebellar ataxia with neuropathy and vestibular areflexia syndrome (CANVAS). In addition, biallelic expansions were shown to account for up to 22% of cases with late-onset ataxia. Since this discovery, the phenotypic spectrum reported to be associated with RFC1 expansions has extended beyond the initial conditions to include pure cerebellar ataxia, isolated somatosensory impairment, combinations of the 2, and parkinsonism, leading to a potentially broad differential diagnosis. Genetic studies suggest RFC1 expansions may be the most common genetic cause of ataxia and are likely underdiagnosed. This review summarizes the current molecular and clinical knowledge of RFC1-related disease, with a focus on the evaluation of recent phenotype associations and highlighting the current challenges in clinical pathways to diagnosis and molecular testing.

Blockchained Federated Learning for Privacy and Security Preservation: Practical Example of Diagnosing Cerebellar Ataxia

Cerebellar ataxia (CA) refers to the incoordination of movements of the eyes, speech, trunk, and limbs caused by cerebellar dysfunction. Conventional machine learning (ML) utilizes centralised databases to train a model of diagnosing CA. Despite the high accuracy, these approaches raise privacy concern as participants' data revealed in the data centre. Federated learning is an effective distributed solution to exchange only the ML model weight rather than the raw data. However, FL is also vulnerable to network attacks from malicious devices. In this study, we depict the concept of blockchained FL with individual's validators. We simulate the proposed approach with real-world dataset collected from kinematic sensors of CA individuals with four geographically separated clinics. Experimental results show the blockchained FL maintains competitive accuracy of 89.30%, while preserving both privacy and security.

Federated Deep Learning for the Diagnosis of Cerebellar Ataxia: Privacy Preservation and Auto-crafted Feature Extractor

Cerebellar ataxia (CA) is concerned with the incoordination of movement caused by cerebellar dysfunction. Movements of the eyes, speech, trunk, and limbs are affected. Conventional machine learning approaches utilizing centralised databases have been used to objectively diagnose and quantify the severity of CA. Although these approaches achieved high accuracy, large scale deployment will require large clinics and raises privacy concerns. In this study, we propose an image transformation-based approach to leverage the advantages of state-of-the-art deep learning with federated learning in diagnosing CA. We use motion capture sensors during the performance of a standard neurological balance test obtained from four geographically separated clinics. The recurrence plot, melspectrogram, and poincaré plot are three transformation techniques explored. Experimental results indicate that the recurrence plot yields the highest validation accuracy (86.69%) with MobileNetV2 model in diagnosing CA. The proposed scheme provides a practical solution with high diagnosis accuracy, removing the need for feature engineering and preserving data privacy for a large-scale deployment.

Objective Assessment of Progression and Disease Characterization of Friedreich Ataxia via an Instrumented Drinking Cup: Preliminary Results

The monitoring of disease progression in certain neurodegenerative conditions can significantly be quantified with the help of objective assessments. The severity assessment of diseases like Friedreich ataxia (FRDA) are usually based on different subjective measures. The ability of a participant with FRDA to perform standard neurological tests is the most common way of assessing disease progression. In this feasibility study, an Ataxia Instrumented Measurement-Cup (AIM-C) is proposed to quantify the disease progression of 10 participants (mean age 39 years, onset of disease 16.3 years) in longitudinal timepoints. The device consists of a sensing system with the provision of extracting both kinetic and kinematic information while engaging in an activity closely associated with activities of daily living (ADL). A common functional task of simulated drinking was used to capture features that possesses disease progression information as well as certain other features which intrinsically correlate with commonly used clinical scales such as the modified Friedreich Ataxia Rating Scale (mFARS), the Functional Staging of Ataxia score and the ADL scale. Frequency and time-frequency domain features allowed the longitudinal assessment of participants with FRDA. Furthermore, both kinetic and kinematic measures captured clinically relevant features and correlated 85% with clinical assessments.

Diagnosis Cerebellar Ataxia using Deep Learning with Time Series Transformed Image

Cerebellar ataxia (CA) is defined by disrupted coordination of movement suffering from disease of the cerebellum. It reflects fragmented movements of the eyes, vocal, upper limbs, balance, gait, and lower limbs. This study aims to use a motion sensor to form a simple yet effective CA quantitative assessment framework. We suggest a pendant device to use a single kinematic sensor attached to the wearer's chest to investigate the balance capability. Via a standard neurological test (Romberg's standing), the device may reveal an early symptom of Cerebellar Ataxia tailoring toward rehabilitation or therapeutic program. We adopt a transformed-image based approach to leverage the advantage of state-of-the-art deep learning models into diagnosis CA. Three transform techniques are employed including recurrence plot, melspectrogram, and Poincaré plot. Experiment results show that melspectrogram transform technique performs best in implementation with MobileNetV2 to diagnose CA with an average validation accuracy of 89.99%.

Quantitative Assessment of Friedreich Ataxia via Self-Drinking Activity

Effective monitoring of the progression of neurodegenerative conditions can be significantly improved by objective assessments. Clinical assessments of conditions such as Friedreich's Ataxia (FA), currently rely on subjective measures commonly practiced in clinics as well as the ability of the affected individual to perform conventional tests of the neurological examination. In this study, we propose an ataxia measuring device, in the form of a pressure canister capable of sensing certain kinetic and kinematic parameters of interest to quantify the impairment levels of participants particularly when engaged in an activity that is closely associated with daily living. In particular, the functional task of simulated drinking was utilised to capture characteristic features of disability manifestation in terms of diagnosis (separation of individuals with FA and controls) and severity assessment of individuals diagnosed with the debilitating condition of FA. Time and frequency domain analysis of these biomarkers enabled the classification of individuals with FA and control subjects to reach an accuracy of 98% and a correlation level reaching 96% with the clinical scores.

Instrumented Objective Clinical Examination of Cerebellar Ataxia: the Upper and Lower Limb-a Review

Cerebellar dysfunction results in impairments in co-ordination or 'ataxia'. Bedside examination of cerebellar function has changed little since the early nineteenth century with the exception being the oculomotor examination which has become instrumented. Otherwise, competence and confidence in performing the clinical assessment relies heavily on the skill and experience of the clinician. Potentially, instrumented objective measurement will more accurately assess the severity of ataxia and the changes brought about by advancing therapies in pharmaceutical trials and in rehabilitation intervention. This study describes instrumented versions of several bedside tests of cerebellar function, including rhythmic tapping of the hand (RTH), finger-nose test (FNT), dysdiadochokinesia (DDK), ramp tracking (RMT), ballistic tracking (BT), rhythmic tapping of the foot (RTF) and the heel shin (HST) examination which were validated against scores from Ataxia Rating Scales (ARS) such as the Scale of Assessment and Rating of Ataxia (SARA). While all of the instrumented tests accurately distinguished between ataxic subjects and controls, there was a difference in performance, with the best four performing upper limb tests being RTH, FNT, DDK and BT. A combination of BT plus RTH provided the best correlation with the SARA and outperformed a combination of all the bedside tests (Spearman 0.8; p < 0.001 compared to 0.68; p < 0.001 for the combined set) in identifying the presence and severity of ataxia. This indicates that there is redundancy in the information provided by the bedside tests and that adding other tests to BT plus RTH does not add accuracy to the assessment of ataxia. This analysis highlighted the need for metrics that could be generalised to each of the assessments of ataxia, so, in turn, domains of stability, timing, accuracy and rhythmicity (STAR domains) were developed and compared to the SARA. The STAR criteria could potentially influence the future of instrumented assessment in CA and pave the way for further research into the objective measurement of the cerebellar examination.

The Pathology of the Vestibular System in CANVAS

OBJECTIVE

To describe the site of lesion responsible for the severe, bilateral, symmetrical, selective loss of vestibular function in Cerebellar Ataxia with Neuronopathy and Vestibular Areflexia Syndrome (CANVAS), an adult-onset recessively-inherited ataxia, characterized by progressive imbalance due to a combination of cerebellar, somatosensory, and selective vestibular impairment with normal hearing.

METHODS

Histologic examination of five temporal bones and the brainstems from four CANVAS patients and the brainstem only from one more, each diagnosed and followed from diagnosis to death by one of the clinician authors.

RESULTS

All five temporal bones showed severe loss of vestibular ganglion cells (cell counts 3-16% of normal), and atrophy of the vestibular nerves, whereas vestibular receptor hair cells and the vestibular nuclei were preserved. In contrast, auditory receptor hair cells, the auditory ganglia (cell counts 51-100% of normal), and the auditory nerves were relatively preserved. In addition, the cranial sensory ganglia (geniculate and trigeminal), present in two temporal bones, also showed severe degeneration.

CONCLUSIONS

In CANVAS there is a severe cranial sensory ganglionopathy neuronopathy (ganglionopathy) involving the vestibular, facial, and trigeminal ganglia but sparing the auditory ganglia. These observations, when coupled with the known spinal dorsal root ganglionopathy in CANVAS, indicate a shared pathogenesis of its somatosensory and cranial nerve manifestations. This is the first published account of both the otopathology and neuropathology of CANVAS, a disease that involves the central as well as the peripheral nervous system.

Developing an Instrumented Measure of Upper Limb Function in Friedreich Ataxia

Upper limb function for people with Friedreich ataxia determines capacity to participate in daily activities. Current upper limb measures available do not fully capture impairments related to Friedreich ataxia. We have developed an objective measure, the Ataxia Instrumented Measure-Spoon (AIM-S), which consists of a spoon equipped with a BioKin wireless motion capture device, and algorithms that analyse these signals, to measure ataxia of the upper limb during the pre-oral phase of eating. The aim of this study was to evaluate the AIM-S as a sensitive and functionally relevant clinical outcome for use in clinical trials. A prospective longitudinal study evaluated the capacity of the AIM-S to detect change in upper limb function over 48 weeks. Friedreich ataxia clinical severity, performance on the Nine-Hole Peg Test and Box and Block Test and responses to a purpose-designed questionnaire regarding acceptability of AIM-S were recorded. Forty individuals with Friedreich ataxia and 20 control participants completed the baseline assessment. Thirty individuals with Friedreich ataxia completed the second assessment. The sensitivity of the AIM-S to detect deterioration in upper limb function was greater than other measures. Patient-reported outcomes indicated the AIM-S reflected a daily activity and was more enjoyable to complete than other assessments. The AIM-S is a more accurate, less variable measure of upper limb function in Friedreich ataxia than existing measures. The AIM-S is perceived by individuals with Friedreich ataxia to be related to everyday life and will permit individuals who are non-ambulant to be included in future clinical trials.

A comprehensive scheme for the objective upper body assessments of subjects with cerebellar ataxia

Background

Cerebellar ataxia refers to the disturbance in movement resulting from cerebellar dysfunction. It manifests as inaccurate movements with delayed onset and overshoot, especially when movements are repetitive or rhythmic. Identification of ataxia is integral to the diagnosis and assessment of severity, and is important in monitoring progression and improvement. Ataxia is identified and assessed by clinicians observing subjects perform standardised movement tasks that emphasise ataxic movements. Our aim in this paper was to use data recorded from motion sensors worn while subjects performed these tasks, in order to make an objective assessment of ataxia that accurately modelled the clinical assessment.

Methods

Inertial measurement units and a Kinect© system were used to record motion data while control and ataxic subjects performed four instrumented version of upper extremities tests, i.e. finger chase test (FCT), finger tapping test (FTT), finger to nose test (FNT) and dysdiadochokinesia test (DDKT). Kinematic features were extracted from this data and correlated with clinical ratings of severity of ataxia using the Scale for the Assessment and Rating of Ataxia (SARA). These features were refined using Feed Backward feature Elimination (the best performing method of four). Using several different learning models, including Linear Discrimination, Quadratic Discrimination Analysis, Support Vector Machine and K-Nearest Neighbour these extracted features were used to accurately discriminate between ataxics and control subjects. Leave-One-Out cross validation estimated the generalised performance of the diagnostic model as well as the severity predicting regression model.

Results

The selected model accurately (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$96.4\%$$\end{document}96.4%) predicted the clinical scores for ataxia and correlated well with clinical scores of the severity of ataxia (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$rho = 0.8$$\end{document}rho=0.8, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p < 0.001$$\end{document}p<0.001). The severity estimation was also considered in a 4-level scale to provide a rating that is familiar to the current clinically-used rating of upper limb impairments. The combination of FCT and FTT performed as well as all four test combined in predicting the presence and severity of ataxia.

Conclusion

Individual bedside tests can be emulated using features derived from sensors worn while bedside tests of cerebellar ataxia were being performed. Each test emphasises different aspects of stability, timing, accuracy and rhythmicity of movements. Using the current models it is possible to model the clinician in identifying ataxia and assessing severity but also to identify those test which provide the optimum set of data.

Trial registration Human Research and Ethics Committee, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia (HREC Reference Number: 11/994H/16).

Balance Deficits due to Cerebellar Ataxia: A Machine Learning and Cloud-Based Approach

Cerebellar ataxia (CA) refers to the disordered movement that occurs when the cerebellum is injured or affected by disease. It manifests as uncoordinated movement of the limbs, speech, and balance. This study is aimed at the formation of a simple, objective framework for the quantitative assessment of CA based on motion data. We adopted the Recurrence Quantification Analysis concept in identifying features of significance for the diagnosis. Eighty-six subjects were observed undertaking three standard neurological tests (Romberg's, Heel-shin and Truncal ataxia) to capture 213 time series inertial measurements each. The feature selection was based on engaging six different common techniques to distinguish feature subset for diagnosis and severity assessment separately. The Gaussian Naive Bayes classifier performed best in diagnosing CA with an average double cross-validation accuracy, sensitivity, and specificity of 88.24%, 85.89%, and 92.31%, respectively. Regarding severity assessment, the voting regression model exhibited a significant correlation (0.72 Pearson) with the clinical scores in the case of the Romberg's test. The Heel-shin and Truncal tests were considered for diagnosis and assessment of severity concerning subjects who were unable to stand. The underlying approach proposes a reliable, comprehensive framework for the assessment of postural stability due to cerebellar dysfunction using a single inertial measurement unit.

Quantitative Assessment of Friedreich Ataxia through the self-drinking activity

The progression of neurodegenerative conditions can be effectively monitored and improved by using objective assessments. The conditions such as Friedreich Ataxia (FA) are clinically assessed by means of subjective measures commonly practised in clinics. Here, we propose a device capable of measuring ataxia, in the form of a `cup' capable of sensing certain kinematic parameters of interest while engaging in an activity that is closely related to daily living. In this study, the functional task of 'drinking' was utilised to diagnose participants with FA and capture features in terms of diagnosis (separation) and correlation with the clinical scales. Frequency domain analysis was incorporated enabling the classification of control subjects and FA patients to an accuracy of 88% with a correlation of 90% with the clinical scores.

A Comparative Severity Assessment of Impaired Balance due to Cerebellar Ataxia using Regression Models

Cerebellar ataxia (CA) refers to the impaired balance and coordination resulting from injury or degeneration of the cerebellum. Testing balance is one of the simplest means of assessing CA. This study compares instrumented assessment and clinical assessment scales of the balance test called Romberg's test. Inertial Measurement Unit (IMU) data were collected from a sensor attached to their chest of 53 subjects while they performed the test. The corresponding clinical scores were also tabulated. Using this data, 99 features were extracted to quantify acceleration, tremor and displacement of body sway. These features were filtered to identify the subset that better characterize the distinctive behavior of CA subjects. Elastic Net Regression model resulted a greater agreement (0.70 Pearson coefficient) with the clinical SARA scores. The overall results indicated that data from a single IMU sensor is sufficient to accurately assess balance in CA. The significance of this study is that evaluation of balance using Recurrence Quantification Analysis produces a comprehensive framework for the assessment of CA.

Multimodal Data Acquisition for the Assessment of Cerebellar Ataxia via Ballistic Tracking

Cerebellar ataxia (CA) results from injury to or disease of the cerebellum. It describes the resulting motor dysfunction, characterised by inaccuracy, incoordination and delay in initiation of movement, tremor, and imbalance. Assessment of ataxia to diagnose and monitor progress is by clinical observance of the performance of standard motor tasks. An accurate instrumented measurement of CA would therefore be of great interest. This study was aimed at assessing upper-limb ataxia during ballistic tracking of a computer-generated target in individuals with CA and controls using motion measures obtained from a Kinect camera and a wearable motioncaptured device. A set of features derived from these motion measurements were used to develop a method for objective quantification of CA. Difference between ataxic and non-ataxic movements can be readily be observed in features from both devices (p₌ 0.008) and their values associated with a standard clinical scale (rho = 0.80, p < 0.001). The combination of multimodal features improved the ability to distinguish between CA subjects and controls and to measure the severity of upper limb ataxia.

Assessment of Disease Progression in Friedreich Ataxia using an Instrumented Self Feeding Activity

Friedreich ataxia (FRDA), the most common of the inherited ataxias, is a degenerative disease that progressively affects walking and other functions leading to significant impairment associated with a shortened lifespan. It is important to monitor the progression of ataxia over periods of time for clinical and therapeutic interventions. This study was aimed at investigating the use of our instrumented measurement scheme of utilizing a motion detecting spoon in a self-feeding activity to quantify the longitudinal effect of FRDA on upper limb function. Forty individuals diagnosed with FRDA (32.8±14.9 years old) were recruited in a 12-month longitudinal study consisting of equal number of males and females (20). A set of biomarkers was extracted from the temporal and texture analysis of the movement time series data that objectively detected subtle changes during follow-up testing. The results indicated that both analyses generated features that resembled clinical ratings. Although the diagnosis and severity related performances were readily observed by temporal features, the longitudinal progression was better captured by the textural features (p = 0.029). The estimation of severity by mean of random forest regression model and LASSO exhibited a high degree of parity with the standard clinical scale (rho = 0.73, p < 0.001).

Quantitative Assessment of Cerebella Ataxia, through Automated Limb-Coordination tests

The disabilities affecting the peripheral regions of the body can be often as a result of cerebellar damage. Tremor, poor and inaccurate coordination, and irregular movements associated with gait, balance and speech are some of the manifestations. Conventionally expert opinion determines severity of Cerebellar Ataxia (CA) and the assessment is likely to be inherently subjective. The automated versions of two commonly used tests: Finger to Nose test (FNT) and Heel to Shin Test (HST), are investigated in this paper for evaluating disability and movement deficits due to CA. Limb movements are measured using Inertial Measurement Units (IMU) that captures the disability related information, using kinematic parameters such as acceleration and angular velocity considered in both time and frequency domain. Using the Singular Spectrum Analysis (SSA), the collective dominance in the data distributions of the underlying features were observed. The dominant features were combined to substantiate the correlation with the expert clinical assessments through Linear Discriminant and Regression analysis where the classifier performance was also verified by means of cross-validation. This study found that IMU features captured characteristic movements as intention tremor in FNT and not in HST. In FNT predominantly consisting of translational movements, the rotation was a dominant feature whereas acceleration were observed to be more dominant for the case of HST.

Rapid Diagnosis of Spinocerebellar Ataxia 36 in a Three-Generation Family Using Short-Read Whole-Genome Sequencing Data

BACKGROUND

Spinocerebellar ataxias are often caused by expansions of short tandem repeats. Recent methodological advances have made repeat expansion (RE) detection with whole-genome sequencing (WGS) feasible.

OBJECTIVES

The objective of this study was to determine the genetic basis of ataxia in a multigenerational Australian pedigree with autosomal-dominant inheritance.

METHODS AND RESULTS

WGS was performed on 3 affected relatives. The sequence data were screened for known pathogenic REs using 2 RE detection tools: exSTRa and ExpansionHunter. This screen provided a clear and rapid diagnosis (<5 days from receiving the sequencing data) of spinocerebellar ataxia 36, a rare form of ataxia caused by an intronic GGCCTG RE in NOP56.

CONCLUSIONS

The diagnosis of rare ataxias caused by REs is highly feasible and cost-effective with WGS. We propose that WGS could potentially be implemented as the frontline, cost-effective methodology for the molecular testing of individuals with a clinical diagnosis of ataxia. © 2020 International Parkinson and Movement Disorder Society.

Characteristics of assessment and treatment in Benign Paroxysmal Positional Vertigo (BPPV)

QUESTION:

Benign Paroxysmal Positional Vertigo (BPPV) is the most common cause of dizziness presenting to specialist vestibular centres and accounts for approximately 20–30% of referrals to these clinics. In spite of the amount of clinical knowledge surrounding its diagnosis and management, the treatment of BPPV remains challenging for even the most experienced clinicians. This study outlines the incidence of BPPV in a specialised vestibular physiotherapy clinics and discusses the various nuances encountered during assessment and treatment of BPPV.

DESIGN:

Observational Study

PARTICIPANTS:

314 patients with various forms of Benign Paroxysmal Positional Vertigo (BPPV)

INTERVENTION:

Canalith repositioning manoeuvres (CRP) for posterior canal (PC) or horizontal canal (HC) BPPV depending on the canal and variant of BPPV.

OUTCOME MEASURES:

Negative Dix-Hallpike (DHP) or Supine roll test (SRT) examination.

RESULTS:

In 91% of cases, PC BPPV was effectively treated in 2 manoeuvres or less. Similarly, 88% of HC BPPV presentations were effectively managed with 2 treatments. Bilateral PC, multiple canal or canal conversions required a greater number of treatments. There was no noticeable difference in treatment outcomes for patients who had nystagmus and symptoms during the Epley manoeuvre (EM) versus those who did not have nystagmus and symptoms throughout the EM. Nineteen percent of patients experienced post treatment down-beating nystagmus (DBN) and vertigo or “otolithic crisis” after the first or even the second consecutive EM.

CONCLUSION:

Based on the data collected, we make several clinical recommendations for assessment and treatment of BPPV. Firstly, repeated testing and treatment of BPPV within the same session is promoted as a safe and effective approach to the management of BPPV with a low risk of canal conversion. Secondly, vertigo and nystagmus throughout the EM is not indicative of treatment success. Thirdly, clinicians must remain vigilant and mindful of the possibility of post treatment otolithic crisis following the treatment of BPPV. This is to ensure patient safety and to prevent possible injurious falls. Our results challenge several clinical assumptions about the assessment and treatment of BPPV including the utility of certain markers of treatment success; hence influencing the current clinical guidelines and clinical practice and paving the way for future studies of the assessment and management of patients with BPPV.

An Instrumented Measurement Scheme for the Assessment of Upper Limb Function in Individuals with Friedreich Ataxia

Continuous and objective assessment is essential for accurate monitoring of the progression of neurodegenerative conditions such as Friedreich ataxia. However, current clinical assessments predominantly rely on the ability of the affected individual to complete specific clinical tests which may not capture the intricate kinematic details associated with ataxia Moreover, such testing often consists of a level of subjectivity of the assessing clinician. In this paper, we propose an objective measuring instrument, in the form of a spoon, equipped with the Internet-of-Things (IoT) based system and relevant machine learning techniques to quantitatively assess impairment levels while engaged in routine daily activity. In a clinical study involving individuals diagnosed with Friedreich ataxia, movement patterns during a simulated eating task were captured and kinematic biomarkers were extracted that were consistent with the frequently-used clinical rating scales. Multivariate analysis of these biomarkers allows us to accurately classify individuals with Friedreich ataxia and control subjects to an accuracy of 91%. Furthermore, the kinematic information captured from the spoon can be used to introduce an alternative assessment scheme with a greater sensitivity to ataxic movements and with less inter-rater discrepancy.

Automated Evaluation of Upper Limb Motor Impairment of Patient with Cerebellar Ataxia

Upper limb impairment with various symptoms including incoordination, tremors and prolonged motion are important factors of motor disturbance in Cerebellar ataxia (CA). Accurate assessment is a key element in the diagnosis and progress monitoring of conditions such as CA. Often such assessments are mostly based on the observations of the clinicians and hence, are inherently subjective. In this paper, we propose a system that consists of two automated assessment schemes which employ a depth camera and an inertial measurement unit (IMU) sensor for the quantification of upper limb ataxia in the treatment of CA. The assessment includes an automated finger chase in which the patients were asked to follow a target point on the screen using their index finger and another assessment in which the patients were asked to tap their finger continuously on a surface at a comfortable rate. The overall system was tested for 44 CA patients and 14 age matched healthy individuals. The combination of features of the two tests provided us with an objective measurement which identifies CA patients to a higher degree of accuracy (Quadratic Discriminant Analysis, 93.1%) in addition to providing a high correlation (r = 0.8, p <; 0.001) with the the Scale for the Assessment and Rating of Ataxia (SARA) based severity evaluation of patients.

Bioinformatics-Based Identification of Expanded Repeats: A Non-reference Intronic Pentamer Expansion in RFC1 Causes CANVAS

Genomic technologies such as next-generation sequencing (NGS) are revolutionizing molecular diagnostics and clinical medicine. However, these approaches have proven inefficient at identifying pathogenic repeat expansions. Here, we apply a collection of bioinformatics tools that can be utilized to identify either known or novel expanded repeat sequences in NGS data. We performed genetic studies of a cohort of 35 individuals from 22 families with a clinical diagnosis of cerebellar ataxia with neuropathy and bilateral vestibular areflexia syndrome (CANVAS). Analysis of whole-genome sequence (WGS) data with five independent algorithms identified a recessively inherited intronic repeat expansion [(AAGGG)exp] in the gene encoding Replication Factor C1 (RFC1). This motif, not reported in the reference sequence, localized to an Alu element and replaced the reference (AAAAG)11 short tandem repeat. Genetic analyses confirmed the pathogenic expansion in 18 of 22 CANVAS-affected families and identified a core ancestral haplotype, estimated to have arisen in Europe more than twenty-five thousand years ago. WGS of the four RFC1-negative CANVAS-affected families identified plausible variants in three, with genomic re-diagnosis of SCA3, spastic ataxia of the Charlevoix-Saguenay type, and SCA45. This study identified the genetic basis of CANVAS and demonstrated that these improved bioinformatics tools increase the diagnostic utility of WGS to determine the genetic basis of a heterogeneous group of clinically overlapping neurogenetic disorders.

Quantitative Evaluation of Cerebellar Ataxia Through Automated Assessment of Upper Limb Movements

Cerebellar damage can result in peripheral dysfunction manifesting as poor and inaccurate coordination, irregular movements, and tremors. Conventionally, the severity assessment of Cerebellar ataxia (CA) is primarily based on expert clinical opinion and hence likely to be subjective. In order to establish inter-rater concordance with enhanced reliability and effectiveness in the assessment of upper limb function, a novel automated system employing Microsoft Kinect^© is considered to capture the motion of the patient's finger for objective assessment. This essentially mimics the commonly used finger tracking task clinically assessed through subjective observation. A clinical trial was conducted involving 42 CA patients and 18 age-matched healthy subjects. The relevant kinematically diagnostic features of CA patients allowed a classification accuracy of 97% using the Bayesian Quadratic Discriminant Analysis (QDA). The correlation (severity) between the extracted features and the independent severity scores from expert clinicians were collated to achieve a high correlation ( r = 0.86 , ) with the Scale for the Assessment and Rating of Ataxia (SARA). The proposed system can efficiently generate objective information of severity as a result of features that are not necessarily observable during standard bedside clinical testing. Furthermore, the superior performance of the Ballistic (finger chase) test indeed supports the credence of the Ramp test redundancy that exists among the wider clinical community.

Quantitative assessment of cerebellar ataxia, through automated limb functional tests

Background

Cerebellar damage can often result in disabilities affecting the peripheral regions of the body. These include poor and inaccurate coordination, tremors and irregular movements that often manifest as disorders associated with balance, gait and speech. The severity assessment of Cerebellar ataxia (CA) is determined by expert opinion and is likely to be subjective in nature. This paper investigates automated versions of three commonly used tests: Finger to Nose test (FNT), test for upper limb Dysdiadochokinesia Test (DDK) and Heel to Shin Test (HST), in evaluating disability due to CA.

Methods

Limb movements associated with these tests are measured using Inertial Measurement Units (IMU) to capture the disability. Kinematic parameters such as acceleration, velocity and angle are considered in both time and frequency domain in three orthogonal axes to obtain relevant disability related information. The collective dominance in the data distributions of the underlying features were observed though the Principal Component Analysis (PCA). The dominant features were combined to substantiate the correlation with the expert clinical assessments through Linear Discriminant Analysis. Here, the Pearson correlation is used to examine the relationship between the objective assessments and the expert clinical scores while the performance was also verified by means of cross validation.

Results

The experimental results show that acceleration is a major feature in DDK and HST, whereas rotation is the main feature responsible for classification in FNT. Combining the features enhanced the correlations in each domain. The subject data was classified based on the severity information based on expert clinical scores.

Conclusion

For the predominantly translational movement in the upper limb FNT, the rotation captures disability and for the DDK test with predominantly rotational movements, the linear acceleration captures the disability but cannot be extended to the lower limb HST. The orthogonal direction manifestation of ataxia attributed to sensory measurements was determined for each test.

Trial registration

Human Research and Ethics Committee, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia (HREC Reference Number: 11/994H/16).

Electronic supplementary material

The online version of this article (10.1186/s12984-019-0490-3) contains supplementary material, which is available to authorized users.

Proposed diagnostic criteria for cerebellar ataxia with neuropathy and vestibular areflexia syndrome (CANVAS)

PURPOSE OF REVIEW

Diagnosis of ataxic disorders is an important clinical challenge upon which prognostication, management, patient solace, and, above all, the hope of future treatment all rely. Heritable diseases and the possibility of affected offspring carry the added burden of portending adverse health, social and financial ramifications.

RECENT FINDINGS

Cerebellar ataxia with neuropathy and vestibular areflexia syndrome (CANVAS) is an inherited multisystem ataxia compromising cerebellar, vestibular, and sensory function. It is not uncommon, but despite early attempts the genetic defect is yet to be identified. As the search for the causative gene continues, we have found it useful to further define this syndrome in terms of its likely phenotype.

SUMMARY

We propose staged diagnostic criteria based on the identified pathology in CANVAS. We envisage that these criteria will aid the clinician in diagnosing CANVAS and the researcher in further elucidating this complex disorder.

CANVAS an update: clinical presentation, investigation and management

BACKGROUND

Cerebellar Ataxia with Neuropathy and bilateral Vestibular Areflexia Syndrome (CANVAS) is a multi-system ataxia which results in cerebellar ataxia, a bilateral vestibulopathy and a somatosensory deficit. This sensory deficit has recently been shown to be a neuronopathy, with marked dorsal root ganglia neuronal loss. The characteristic oculomotor clinical sign is an abnormal visually enhanced vestibulo-ocular reflex.

OBJECTIVE

To outline the expanding understanding of the pathology in this condition, as well as diagnostic and management issues encountered in clinical practice.

METHODS

Retrospective data on 80 CANVAS patients is reviewed.

RESULTS

In addition to the triad of cerebellar impairment, bilateral vestibulopathy and a somatosensory deficit, CANVAS patients may also present with orthostatic hypotension, a chronic cough and neuropathic pain. Management of falls risk and dysphagia is a major clinical priority.

CONCLUSIONS

CANVAS is an increasingly recognised cause of late-onset ataxia and disequilibrium, and is likely to be a recessive disorder.