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NCT06861517
EEG-based Brain-computer Interface Database for Motor Rehabilitation
trial in Healthy Adults in 30 participants. Completed in 1 December 2024.
1 December 2024
Quick facts
| Lead sponsor | Jaime Alejandro Quiroga Forero |
|---|---|
| Status | Completed |
| Study type | OBSERVATIONAL |
| Enrollment | 30 |
| Start date | 2 September 2024 |
| Primary completion | 1 December 2024 |
| Estimated completion | 1 December 2024 |
| Sites | 1 location across Argentina |
Conditions studied
- Healthy Adults — all drugs for Healthy Adults →
Sponsor
Jaime Alejandro Quiroga Forero
Who can join
Adults 18 to 60, any sex, with Healthy Adults. Patients with the condition only — healthy volunteers not accepted.
Sponsor's own description
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.
Publications & conference data
No peer-reviewed publications indexed yet for this trial. Completed trials usually publish results within 12-18 months.
Verify or expand the search:
- PubMed search for NCT06861517
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Verify against primary sources
- ClinicalTrials.gov — authoritative US registry record
- WHO ICTRP — international registry index
- EU Clinical Trials Register
- Sponsor press releases (Google)
- Trial protocol + status: ClinicalTrials.gov NCT06861517 (US National Library of Medicine, public domain)
- Drug + disease cross-links: matched in real time against Drug Landscape's normalised drug + company + condition tables
- Sponsor: as reported to ClinicalTrials.gov by Jaime Alejandro Quiroga Forero
- Last refreshed: 6 March 2025
Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT06861517.
Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing