Evidence map›Paper›PMID 40102886›Full record

ArticleJournal of neuroengineering and rehabilitation2025

Imu-based kinematic analysis to enhance upper limb motor function assessment in neuromuscular diseases.

Alessandra Favata, Roger Gallart-Agut, Luc van Noort, Jesica Exposito-Escudero, Julita Medina-Cantillo, Carme Torras, Daniel Natera-de Benito, Josep M Font-Llagunes, Rosa Pàmies-Vilà

Abstract read
In one paragraph

Article in Journal of neuroengineering and rehabilitation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

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

9 authors.

Alessandra FavataDepartment of Mechanical Engineering and Institute for Research and Innovation in Health (IRIS), Universitat Politècnica de Catalunya - BarcelonaTech (UPC), Barcelona, Spain. alessandra.favata@upc.edu.
Roger Gallart-AgutInstitut de Robòtica i Informàtica Industrial, CSIC-UPC, Llorens i Artigas 4-6, 08028, Barcelona, Spain.
Luc van NoortDepartment of Mechanical Engineering and Institute for Research and Innovation in Health (IRIS), Universitat Politècnica de Catalunya - BarcelonaTech (UPC), Barcelona, Spain.
Jesica Exposito-EscuderoNeuromuscular Unit, Department of Neurology, Hospital Sant Joan de Déu, Barcelona, Spain.
Julita Medina-CantilloApplied Research in Neuromuscular Diseases, Institut de Recerca Sant Joan de Déu, Barcelona, Spain.
Carme TorrasInstitut de Robòtica i Informàtica Industrial, CSIC-UPC, Llorens i Artigas 4-6, 08028, Barcelona, Spain.
Daniel Natera-de BenitoNeuromuscular Unit, Department of Neurology, Hospital Sant Joan de Déu, Barcelona, Spain.
Josep M Font-LlagunesDepartment of Mechanical Engineering and Institute for Research and Innovation in Health (IRIS), Universitat Politècnica de Catalunya - BarcelonaTech (UPC), Barcelona, Spain.
Rosa Pàmies-VilàDepartment of Mechanical Engineering and Institute for Research and Innovation in Health (IRIS), Universitat Politècnica de Catalunya - BarcelonaTech (UPC), Barcelona, Spain. rosa.pamies@upc.edu.

Funding

Agència de Gestió d'Ajuts Universitaris i de Recerca 2021 SGR 01052Fundació la Marató de TV3 202023-30Fundació la Marató de TV3 202023-31Fundació la Marató de TV3 202023-32
6 · The paper itself

Abstract

Duchenne muscular dystrophy (DMD) and spinal muscular atrophy (SMA) are neuromuscular diseases that lead to progressive muscle degeneration and weakness. Recent therapeutic advances for DMD and SMA highlight the need for accurate clinical evaluation. Traditionally, motor function of the upper limbs is assessed using motor function scales. However, these scales are influenced by clinician's interpretation and may lack accuracy. For this reason, clinicians are becoming interested in finding alternative solutions. In this context, Inertial Measurement Units (IMUs) have gained popularity, offering the possibility to quantitatively and objectively analyze motor function of patients to support clinicians' assessments. We analyzed upper limb kinematics of two groups of children with neuromuscular diseases, seventeen DMD patients and fifteen SMA patients, while performing the corresponding clinical assessment. These two groups were further subdivided into two categories (Category A and Category B), according to disease severity (Brooke scores

Indexed as

Muscular Atrophy, SpinalMuscular Dystrophy, DuchenneNeuromuscular DiseasesUpper ExtremityAdolescentBiomechanical PhenomenaChildChild, PreschoolFemaleHumansMaleIMU-based systemNeuromuscular diseasesPULRULMUpper limb kinematic

Identifiers

PMID40102886
PMCPMC11921574

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.