Skip to content

devsangho/Hand-Posture-Classification-based-on-Surface-Electromyography

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 
 
 

Repository files navigation

Hand Posture Classification based on Surface Electromyography

hand-postures

This project classify hand posture using sEMG signals.

1. Segmentation

  • Number of channel Number of class Sampling frequency: 12
  • Total experiment time (All classes): 17
  • Repetition (Session): 2,000 Hz
  • Time per repetition: 15 min (1,800,000 points) 6 sessions per class 3-5s
  • Duration per repetition : 3~5 s
  • Segment size : 200 ms

2. 통계적 수치 계산 (Time domain feature)

  • 1개의 신호 구간에서 36개의 통계적 수치를 계산한다. → [MAV, VAR, WL] x 12 (channels)

$$MAV = \frac{1}{N}\sum_{i=1}^{N} |x_{i}|$$

$$VAR = \frac{1}{N}\sum_{i=1}^{N} |x_{i}^{2}|$$

$$WL = \sum_{i=1}^{N} |x_{i+1} - x_{i}|$$

3. Train / Test

  • Repetition 1 ~ 4: train set
  • Repetition 5 ~ 6: test set

4. Result

  • Accuracy: 55%

Figure_2

Figure_1

About

classify hand posture using sEMG signals.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages