원문정보
초록
영어
In this paper, a real-time experimental of Hand Gesture SEMG signal using Spectral Estimation and Linear Vector Quantization for Two-Wheel Vehicle Control is proposed. The raw SEMG signals been captured from SEMG amplifier, up to 4 channels of Auto Regressive (AR) power spectral density (PSD) responses data will be combined and a fine tuning step by using LVQ will then incorporate for pattern classification. The database then been build and use for real-time experimental control classification. Captured data will send through serial port and Two-Wheel Machine will receive and move accordingly. The detail of the experiment and simulation conducted described here to verify the differentiation and effectiveness of combined channels PSD method SEMG pattern classification of hand gesture for real-time control.
목차
1. Introduction
2. SEMG Measurement Tool
3 Two Wheel Vehicle System
4 Pattern Classification
4.1 Covariance Method
4.2 LVQ
5 Proposed Method
6 Experimental Result
7 Conclusion
References