Skip to content

Exoskeleton Robot Controls using Brain Signals

EEG-based Brain Signal Analysis for Exoskeleton Robot Controls

Status
Active, not recruiting
Phases
Phase 1
Study type
Interventional
Source
TCTR
Registry ID
TCTR20240512003
Enrollment
30
Registered
2024-05-12
Start date
2024-05-01
Completion date
Unknown
Last updated
2026-08-03

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Multimodal motor intention analysis using EEG and fNIRS signals is a concept for controlling exoskeleton robots in standing, sitting, and knee-bending positions, which can be controlled instantly (online) and with sufficient precision in the most intuitive way as much as possible, is extremely attractive and challenging. Brain-Machine Interface (BMI), Brain-Computer Interface (BCI), Functional near-infrared spectroscopy (fNIRS), Robot, Exoskeleton

Interventions

The research will be conducted in the form of Graz-BCI. The Motor Imagery Task defined in this research is the standing up position. sit-to-stand, stand-to-sit, and knee extension/flexion. Subjects h
Experimental Other
EEG-fNIRS

Sponsors

The National Science and Technology Development Agency (NSTDA)
Lead Sponsor

Eligibility

Sex/Gender
All
Age
20 Years to 60 Years

Inclusion criteria

Inclusion criteria: 1. Healthy volunteers aged between 20 and 60. 2. Can stand up and walk on his own. 3. No symptoms of weakness or numbness in the lower limbs. 4. Can follow instructions in at least 2 steps. 5. Sit balanced by leaning on the back of a chair for at least 60 minutes. 6. Consent to participate in the experiment.

Exclusion criteria

Exclusion criteria: 1. Have a history of disease that causes leg weakness, such as stroke. Nerve root herniation, etc., without recovery/healing to normal 2. Have adhesions in the knees and hips 3. Have communication or intellectual problems such that they cannot follow or cooperate in the test. 4. Knee pain has a Verbal rating scale of 4/10 or higher in the tested leg. 5. Visibility after editing The test display screen cannot be clearly seen at a distance of 1 meter. 6. Have a history of allergic reaction to gel/hair loss

Design outcomes

Primary

MeasureTime frame
EEG and fNIRS signals at 3-6 months after end of the intervention Classification accuracy

Secondary

MeasureTime frame
EEG and fNIRS signals at 3-6 months after end of the intervention Classification accuracy - Comparison of experimental sets and sessions

Countries

Thailand

Contacts

Public ContactArpa Suwannarat

The National Electronics and Computer Technology Center (NECTEC)

arpa.suw@nectec.or.th0895151552

Outcome results

None listed

Source: TCTR (via WHO ICTRP) · Data processed: Aug 9, 2026