Instrumented finger-to-nose test classification in children with ataxia or developmental coordination disorder and controls

Martinez-Manzanera, Octavio; Lawerman, T.F.; Blok, H.J.; Lunsing, R.J.; Brandsma, R.; Sival, Deborah A; Maurits, Natasha M.

doi:10.1016/j.clinbiomech.2018.10.007

Cited by 18 publications

(49 citation statements)

References 17 publications

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“…24 Results indicated that EOA kinetic trajectories are more irregular, both within and between intentional movement trajectories, such as the finger-to-nose test. 24 The third validated standardized phenotypic EOA feature concerns the presence of a bow-shaped intentional movement trajectory in any spatial plane. 25,26 Application of these three features resulted in a higher phenotypic consensus regarding the separation of EOA and DCD phenotypes.…”

Section: Discussionmentioning

confidence: 99%

“…When considering the incomplete phenotypic separation between EOA and DCD phenotypes, we explored the effect of previously proven, standardized phenotypic EOA features on phenotypic homogeneity. One validated standardized phenotypic EOA feature is that patients with EOA are likely to reveal assembled SARA motor (sub)scores from different SARA domains, reflecting global cerebellar involvement .…”

Section: Discussionmentioning

confidence: 99%

“…The remaining underlying genetic and metabolic disorders are likely to induce global cerebellar dysfunction. The other validated standardized phenotypic EOA features are derived from previous machine learning research . To distinguish between EOA, DCD, and physiologically delayed motor behaviour, Martinez‐Manzanera et al used automatic random‐forest classifiers on quantitative inertial measurement unit data .…”

Section: Discussionmentioning

confidence: 99%

“…The other validated standardized phenotypic EOA features are derived from previous machine learning research . To distinguish between EOA, DCD, and physiologically delayed motor behaviour, Martinez‐Manzanera et al used automatic random‐forest classifiers on quantitative inertial measurement unit data . Results indicated that EOA kinetic trajectories are more irregular, both within and between intentional movement trajectories, such as the finger‐to‐nose test .…”

Section: Discussionmentioning

confidence: 99%

“…Since a DCD diagnosis depends on the exclusion of an underlying neurological disorder, further diagnostic testing could provide a different diagnosis in a proportion of DCD phenotypes. When considering the incomplete phenotypic separation between EOA and DCD phenotypes, we explored the effect of previously proven, 18,23,24 standardized phenotypic EOA features on phenotypic homogeneity. One validated standardized phenotypic EOA feature is that patients with EOA are likely to reveal assembled SARA motor (sub) scores from different SARA domains, reflecting global cerebellar involvement.…”

Section: Discussionmentioning

confidence: 99%

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Paediatric motor phenotypes in early‐onset ataxia, developmental coordination disorder, and central hypotonia

Lawerman

Brandsma

Maurits

et al. 2019

Develop Med Child Neuro

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AIMS To investigate the accuracy of phenotypic early-onset ataxia (EOA) recognition among developmental conditions, including developmental coordination disorder (DCD) and hypotonia of central nervous system origin, and the effect of scientifically validated EOA features on changing phenotypic consensus.METHOD We included 32 children (4-17y) diagnosed with EOA (n=11), DCD (n=10), and central hypotonia (n=11). Three paediatric neurologists independently assessed videotaped motor behaviour phenotypically and quantitatively (using the Scale for Assessment and Rating of Ataxia [SARA]). We determined: (1) phenotypic interobserver agreement and phenotypic homogeneity (percentage of phenotypes with full consensus by all three observers according to the underlying diagnosis); (2) SARA (sub)score profiles; and (3) the effect of three scientifically validated EOA features on phenotypic consensus. RESULTS Phenotypic homogeneity occurred in 8 out of 11, 2 out of 10, and 1 out of 11 patients with EOA, DCD, and central hypotonia respectively. Homogeneous phenotypic discrimination of EOA from DCD and central hypotonia occurred in 16 out of 21 and 22 out of 22 patients respectively. Inhomogeneously discriminated EOA and DCD phenotypes (5 out of 21) revealed overlapping SARA scores with different SARA subscore profiles. After phenotypic reassessment with scientifically validated EOA features, phenotypic homogeneity changed from 16 to 18 patients.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 3 more Smart Citations

Paediatric motor phenotypes in early‐onset ataxia, developmental coordination disorder, and central hypotonia

Lawerman

Brandsma

Maurits

et al. 2019

Develop Med Child Neuro

View full text Add to dashboard Cite

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Decomposition of Reaching Movements Enables Detection and Measurement of Ataxia

et al. 2021

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Technologies that enable frequent, objective, and precise measurement of ataxia severity would benefit clinical trials by lowering participation barriers and improving the ability to measure disease state and change. We hypothesized that analyzing characteristics of sub-second movement profiles obtained during a reaching task would be useful for objectively quantifying motor characteristics of ataxia. Participants with ataxia (N=88), participants with parkinsonism (N=44), and healthy controls (N=34) performed a computer tablet version of the finger-to-nose test while wearing inertial sensors on their wrists. Data features designed to capture signs of ataxia were extracted from participants’ decomposed wrist velocity time-series. A machine learning regression model was trained to estimate overall ataxia severity, as measured by the Brief Ataxia Rating Scale (BARS). Classification models were trained to distinguish between ataxia participants and controls and between ataxia and parkinsonism phenotypes. Movement decomposition revealed expected and novel characteristics of the ataxia phenotype. The distance, speed, duration, morphology, and temporal relationships of decomposed movements exhibited strong relationships with disease severity. The regression model estimated BARS with a root mean square error of 3.6 points, r2 = 0.69, and moderate-to-excellent reliability. Classification models distinguished between ataxia participants and controls and ataxia and parkinsonism phenotypes with areas under the receiver-operating curve of 0.96 and 0.89, respectively. Movement decomposition captures core features of ataxia and may be useful for objective, precise, and frequent assessment of ataxia in home and clinic environments.

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Free-Living Motor Activity Monitoring in Ataxia-Telangiectasia

et al. 2021

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With disease-modifying approaches under evaluation in ataxia-telangiectasia and other ataxias, there is a need for objective and reliable biomarkers of free-living motor function. In this study, we test the hypothesis that metrics derived from a single wrist sensor worn at home provide accurate, reliable, and interpretable information about neurological disease severity in children with A-T. A total of 15 children with A-T and 15 age- and sex-matched controls wore a sensor with a triaxial accelerometer on their dominant wrist for 1 week at home. Activity intensity measures, derived from the sensor data, were compared with in-person neurological evaluation on the Brief Ataxia Rating Scale (BARS) and performance on a validated computer mouse task. Children with A-T were inactive the same proportion of each day as controls but produced more low intensity movements ( p < 0.01; Cohen’s d = 1.48) and fewer high intensity movements ( p < 0.001; Cohen’s d = 1.71). The range of activity intensities was markedly reduced in A-T compared to controls ( p < 0.0001; Cohen’s d = 2.72). The activity metrics correlated strongly with arm, gait, and total clinical severity ( r : 0.71–0.87; p < 0.0001), correlated with specific computer task motor features ( r : 0.67–0.92; p < 0.01), demonstrated high reliability ( r : 0.86–0.93; p < 0.00001), and were not significantly influenced by age in the healthy control group. Motor activity metrics from a single, inexpensive wrist sensor during free-living behavior provide accurate and reliable information about diagnosis, neurological disease severity, and motor performance. These low-burden measurements are applicable independent of ambulatory status and are potential digital behavioral biomarkers in A-T.

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Instrumented finger-to-nose test classification in children with ataxia or developmental coordination disorder and controls

Cited by 18 publications

References 17 publications

Paediatric motor phenotypes in early‐onset ataxia, developmental coordination disorder, and central hypotonia

Paediatric motor phenotypes in early‐onset ataxia, developmental coordination disorder, and central hypotonia

Decomposition of Reaching Movements Enables Detection and Measurement of Ataxia

Free-Living Motor Activity Monitoring in Ataxia-Telangiectasia

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