Bayesian Deep Learning for Motor Imagery Classificatio
- Registration Number
- TCTR20211027006
- Lead Sponsor
- ational Electronics and Computer Technology Center: NECTEC
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Pending (Not yet recruiting)
- Sex
- All
- Target Recruitment
- 15
1. Active ageing
2. No weakness or numbness of upper limb.
3. Sit upright with the back of a chair for 60 minutes or more.
4. Agree to participate in the trial
1. Have a history of diseases that weaken the arm, such as a stroke .
2. Have shoulder and elbow articular attachment. The arm can be raised less than 90 degrees forward, and the elbow is less than -20 degrees, and the elbow is flexed less than 130 degrees.
3. Have communication or intellectual problems that they are unable to follow or cooperate in the experiment .
4. Have shoulder or elbow pain with a visual analog scale of 4 or greater in the tested arm.
5. Vision after editing could not be clearly seen the screen in the experiment at a distance of approximately 1 meter.
Study & Design
- Study Type
- Interventional
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method classification accuracy after 4th session classification accuracy
- Secondary Outcome Measures
Name Time Method classification accuracy after 4th session classification accuracy