Advancing Hand Gesture Recognition with High Resolution Electrical Impedance Tomography

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" summary

A wireless, battery-powered armband prototype uses electrical impedance tomography with four-pole sensing and up to 32 electrodes to image the wrist; custom hardware raises sampling from ~250 to ~3000 measurements/sec and runs a single-step MAP reconstructor in real time. Evaluation uses saline phantoms and a 10-person user study (11 gestures, 3,300 trials). Four-pole outperforms two-pole (roughly 84% vs 94.3% peak gesture accuracy at 32 electrodes), showing higher electrode counts and four-pole drive materially improve recognition.

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" chapters (19)

1. 0:00Intro
2. 0:20Tomography
3. 0:46Tomography Techniques
4. 2:00AIT
5. 2:41Tomo
6. 7:53New Hardware
7. 8:07Schematic Diagram
8. 8:40New Prototype
9. 9:04Image Reconstruction
10. 10:03Experiments
11. 10:47Results
12. 12:43RealTime Reconstruction
13. 13:47Gesture Accuracy
14. 14:07Data Collection
15. 14:20Machine Learning
16. 15:12Machine Learning Results
17. 15:39Future Work
18. 16:57EMG vs Sensing
19. 18:22Other Questions

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