Evidence map›Paper›PMID 38575842›Full record

ArticleActa neurologica Belgica2024

Quantifying abnormal writing kinematics in writer's cramp using a novel software platform.

Kavadisseril Vivekanandan Vysakha, Vineeth Radhakrishnan, Praveen James, B Suresh Kumar, Ashish Anand Susvirkar, Gangadhara Sarma, Ajith Cherian, K P Divya, Syam Krishnan Nair, Asha Kishore

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Article in Acta neurologica Belgica, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 30% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Review
  2. Dystonic tremor in Writer's cramp Mimicking primary handwriting tremor.Clinical parkinsonism & related disorders · 2025
    Article
4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 1 institution in 1 country.

Kavadisseril Vivekanandan VysakhaDepartment of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, 695011, India.
Vineeth RadhakrishnanDepartment of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, 695011, India.
Praveen JamesDepartment of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, 695011, India.
B Suresh KumarDepartment Computer Division, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India.
Ashish Anand SusvirkarDepartment of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, 695011, India.
Gangadhara SarmaDepartment of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, 695011, India.
Ajith CherianDepartment of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, 695011, India.
K P DivyaDepartment of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, 695011, India. drdivyakp01@gmail.com.ORCID http://orcid.org/0000-0002-4695-8842
Syam Krishnan NairDepartment of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, 695011, India.
Asha KishoreDepartment of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, 695011, India.
Sree Chitra Thirunal Institute for Medical Sciences and Technology · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWriter's cramp is a task-specific focal hand dystonia, which is diagnosed clinically. Quantification of defect in WC is done using clinical scales, while digitized platforms are lacking.

objectiveTo design and test a platform that can differentiate and quantify the abnormal kinematics of writing using a software interface and to validate it in adult-onset isolated writer's cramp (WC).

methodsA native platform was designed using Java and Wacom Intuos pro tablet and the data analyzed using a MATLAB-based platform called Large Data-Based Evaluation of Kinematics in Handwriting (LEKH). We standardized this new platform by comparing the handwriting between patients with WC and age, and gender and education-matched healthy controls, using standard tasks to assess the kinematics.

resultsComparison of the writing of right-handed WC patients (N = 21) and 39 healthy controls (N = 39) showed that patients differed from controls in the frequency of strokes (P < 0.001), number of inversions of velocity (P < 0.001), number of breaks (P = 0.02), air time and paper time (P < 0.001).

conclusionsUsing the LEKH platform, the kinematic profile of patients with WC could be differentiated from healthy controls. Studies in larger samples will be needed to derive statistical models that can differentiate the flexion and extension types of WC which can help in muscle selection and to quantify the effects of treatment.

Indexed as

Dystonic DisordersHandwritingSoftwareAdultAgedBiomechanical PhenomenaFemaleHumansMaleMiddle AgedAir timeKinematicsNumber of inversions of velocityPressure parametersWriter’s cramp

Identifiers

PMID38575842
OpenAlexW4393929947

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.