EEG-based Brain-computer Interface Database for Motor Rehabilitation

Deep Dictionaries for Feature Extraction in Context of Sparse Data for Electroencephalographic Signals from Brain-computer Interfaces

The human brain, as a processing center, controls bodily, cognitive, emotional and social functions, enabling perception, signal analysis and decision making. However, these functions can be affected by acquired brain injury (ABI), resulting from traumatic (blows to the head) or non-traumatic factors (tumors, strokes, infections, among others). Annually, about 55 million new cases of ABI are reported, with sequelae that can affect the quality of life of patients and their families. This scenario has driven research into tools to mitigate and recover lost capabilities. The Center for Rehabilitation Engineering and Neuromuscular and Sensory Research (CIRINS) of the Faculty of Engineering of the National University of Entre Ríos in Argentina has developed neuromuscular and sensory rehabilitation systems, with a focus on the innovation of motor rehabilitation tools using EEG-based brain-computer interfaces (BCI). These BCIs stand out for their economy and versatility, showing significant effects in the rehabilitation of motor functions. Challenges in BCI include signal complexity, artifacts, and inter-person variability, making it difficult to estimate user intent and extending calibration time. To mitigate these problems, strategies based on Deep Learning and dictionary learning have been proposed, which allow for sparse representations of data, being robust to noise and missing data, but with challenges in classification. The study proposes to develop a database of electroencephalographic signals applicable in the development of new algorithms for processing and feature extraction of this type of signals, contributing to the development of technology that supports rehabilitation processes.

Study Overview

• Status: Completed
• Conditions: Healthy Adults

• Study Type: Observational
• Enrollment (Actual): 30

Contacts and Locations

Study Locations

• Argentina
  • Entre Ríos
    • Oro Verde, Entre Ríos, Argentina, 3100
      • Faculty of Engineering, National University of Entre Ríos

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study Population

Volunteers of legal age and under 60 years of age, of any gender and without a history of neurological diseases

Description

Inclusion Criteria:

• Willingness and ability to fully understand the purpose and scope of the experiment and to comply with the experiment instructions.
• Ability to easily distinguish visually the figures in the study.
• Ability to perform tasks that demand sustained concentration.

Exclusion Criteria:

• History of neurological diseases.
• Suffering from any type of musculoskeletal disorder that limits the motor skills necessary for the experiment.
• Having a significant hearing loss that prevents him/her from hearing the study instructions.
• Pregnancy.
• Lack of cooperation.

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort
Healthly Volunteer

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Sensory motor rhythms power bands	The volunteer performs a movement task after a cue. A 32-channel EEG records signals following the 10-20 system and measures sensory-motor rhythm power bands.	Day 1

Collaborators and Investigators

• Sponsor: Jaime Alejandro Quiroga Forero

Publications and helpful links

Helpful Links

• Publication about EEG Sensorimotor Rhythms
• Motor Intention in EEG-Based BCI

Study record dates

Study Major Dates

• Study Start (Actual): September 2, 2024
• Primary Completion (Actual): December 1, 2024
• Study Completion (Actual): December 1, 2024

Study Registration Dates

• First Submitted: February 24, 2025
• First Submitted That Met QC Criteria: February 28, 2025
• First Posted (Actual): March 25, 2025

Study Record Updates

• Last Update Posted (Actual): March 25, 2025
• Last Update Submitted That Met QC Criteria: February 28, 2025
• Last Verified: February 1, 2025

More Information

Terms related to this study

• Keywords: BCI; EEG Signals Database; Effective Motor Activity
• Other Study ID Numbers: IS004678

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: The study will focus on electroencephalography signals, therefore for now it is not considered relevant to include data from individual participants (IPD).

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No