System for the dynamic assessment of the upper limb

Authors

  • Oziel Román Cantú López Universitat Politècnica de Catalunya https://orcid.org/0009-0008-3162-2079
  • Elena Condominas Universitat Politècnica de Catalunya
  • Ferran Esquinas-Domínguez Universitat Politècnica de Catalunya
  • Marta Borràs Universitat Politècnica de Catalunya
  • Joan Francesc Alonso Universitat Politècnica de Catalunya
  • Mónica Rojas-Martínez Universitat Politècnica de Catalunya

DOI:

https://doi.org/10.17979/ja-cea.2026.47.13844

Keywords:

Biomedical signal measurement and processing, Clinical trial, Clinical validation, Decision support and control in medicine, Control of physiological and clinical variables, Rehabilitation engineering and healthcare delivery

Abstract

This paper describes the design of a system for the dynamic assessment of the upper limb in participants with neuromuscular disorders. The system is based on a circular structure for controlled movements with seven radial tracks and LED visual guidance, allowing the standardization of trajectories and movement speeds. The instrumentation integrates simultaneous recordings of EEG (64 channels), high-density surface electromyography (320 HD-sEMG channels), and infrared markers to track the upper limb position during movement. Synchronization between devices (LEDs, amplifier and motion tracking cameras) is managed via auxiliary signals controlled by an Arduino microcontroller. An ergonomic handle designed to compensate for spastic wrist conditions is included. The goal is to extract objective biomarkers, such as activation maps and cortico-muscular coherence, to quantify neuromuscular recovery and the interaction between central and peripheral components of voluntary motor activation.

References

Borràs, M., Romero, S., Serna, L. Y., Alonso, J. F., Bachiller, A., Mañanas, M. A., Rojas, M., 2025. Assessing Motor Cortical Activity: How Repetitions Impact Motor Execution and Imagery Analysis. Psychophysiology. DOI: 10.1111/psyp.15065

Brambilla, C., Pirovano, I., Mira, R. M., Rizzo, G., Scano, A., Mastropietro, A., 2021. Combined Use of EMG and EEG Techniques for Neuromotor Assessment in Rehabilitative Applications: A Systematic Review. Sensors 21, 7014. DOI: 10.3390/s21217014

Farina, D., Holobar, A., 2014. Human/Machine interfacing by decoding the surface electromyogram. IEEE Signal Processing Magazine 32, 115–120. DOI: 10.1109/MSP.2014.2359242

Garro, F., Chiappalone, M., Buccelli, S., De Michieli, L., Semprini, M., 2021. Neuromechanical Biomarkers for Robotic Neurorehabilitation. Frontiers in Neurorobotics 15, 742163. DOI: 10.3389/fnbot.2021.742163

Gonçalves, A., Silva, M. F., Mendonça, H., Rocha, C. D., 2025. A Review of Robotic Interfaces for Post-Stroke Upper-Limb Rehabilitation: Assistance Types, Actuation Methods, and Control Mechanisms. Robotics 14, 141. DOI: 10.3390/robotics14100141

Komi, H., Kurumadani, H., Kurauchi, K., Date, S., Sunagawa, T., 2025. Differences in muscle activity and intermuscular coordination between dominant and non-dominant hands during chopstick manipulation. Frontiers in Human Neuroscience 19, 1574002. DOI: 10.3389/fnhum.2025.1574002

Li, C., Xu, Y., Feng, T., Wang, M., Zhang, X., Zhang, L., Cheng, R., Chen, W., Chen, W., Zhang, S., 2025. Fusion of EEG and EMG signals for detecting pre-movement intention of sitting and standing in healthy individuals and patients with spinal cord injury. Frontiers in Neuroscience 19, 1532099. DOI: 10.3389/fnins.2025.1532099

Mira, R. M., Tosatti, L. M., Sacco, M., Scano, A., 2021. Detailed characterization of physiological EMG activations and directional tuning of upper-limb and trunk muscles in point-to-point reaching movements. Current Research in Physiology 4, 60–72. DOI: 10.1016/j.crphys.2021.02.005

Ogahara, K., Nakashima, A., Suzuki, T., Sugawara, K., Yoshida, N., Hatta, A., Moriuchi, T., Higashi, T., 2024. Comparing movement-related cortical potential between real and simulated movement tasks from an ecological validity perspective. Frontiers in Human Neuroscience 17, 1313835. DOI: 10.3389/fnhum.2023.1313835

Pichiorri, F., Toppi, J., de Seta, V., Colamarino, E., Masciullo, M., Tamburella, F., Lorusso, M., Cincotti, F., Mattia, D., 2023. Exploring high-density corticomuscular networks after stroke to enable a hybrid Brain-Computer Interface for hand motor rehabilitation. Journal of NeuroEngineering and Rehabilitation 20, 5. DOI: 10.1186/s12984-023-01127-6

Rasool, G., Afsharipour, B., Suresh, N. L., Rymer, W. Z., 2017. Spatial Analysis of Multichannel Surface EMG in Hemiplegic Stroke. IEEE Transactions on Neural Systems and Rehabilitation Engineering 25, 1802–1811. DOI: 10.1109/TNSRE.2017.2682298

Xu, Y., Zhang, S., Wang, M., Sawan, M., 2026. Corticomuscular coherence and its non-invasive modulation in stroke applications: a narrative review. Neuroimage: Reports 6, 100329. DOI: 10.1016/j.ynirp.2026.100329

Downloads

Published

2026-09-01

Issue

Section

Bioingeniería