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

**Authors:** 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

PMC · DOI: 10.1186/s12984-025-01602-2 · Journal of NeuroEngineering and Rehabilitation · 2025-03-18

## TL;DR

This paper explores using inertial sensors to objectively assess upper limb movement in children with neuromuscular diseases, offering a more accurate alternative to traditional clinical scales.

## Contribution

The study introduces IMU-based kinematic analysis as a novel method for evaluating motor function in neuromuscular diseases.

## Key findings

- IMU metrics like workspace area and volume strongly correlate with clinical scores in DMD and SMA patients.
- Significant differences in movement patterns were found between healthy children and those with neuromuscular diseases.
- IMU data can distinguish between varying severity levels within patient groups.

## 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 \documentclass[12pt]{minimal}
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				\begin{document}$$>2$$\end{document}>2, respectively). The results were compared against a group of ten healthy children. The metrics showing the strongest correlation with the clinical score were the workspace area in the frontal and transverse plane (DMD: \documentclass[12pt]{minimal}
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				\begin{document}$$\rho$$\end{document}ρ = 0.81) and the workspace volume (DMD: \documentclass[12pt]{minimal}
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				\begin{document}$$\rho$$\end{document}ρ = 0.81). Additionally, statistically significant differences were found not only between healthy children and those with neuromuscular disease, but also across severity levels within the patient group. These results represent a first step toward validating IMU-based systems to helping clinicians to accurately quantify the motor status of children with neuromuscular diseases. Furthermore, data collected with inertial sensors can provide clinicians with additional information not available through subjective observation.

## Linked entities

- **Diseases:** Duchenne muscular dystrophy (MONDO:0010679), spinal muscular atrophy (MONDO:0001516)

## Full-text entities

- **Diseases:** SMA (MESH:D009134), muscle degeneration (MESH:D009410), weakness (MESH:D018908), neuromuscular disease (MESH:D009468), DMD (MESH:D020388)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

10 figures with captions in the complete paper: https://tomesphere.com/paper/PMC11921574/full.md

## References

1 references — full list in the complete paper: https://tomesphere.com/paper/PMC11921574/full.md

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Source: https://tomesphere.com/paper/PMC11921574