Khung học chuyển đổi hai lớp cho nhận diện cử chỉ độc lập với người dùng dựa trên tín hiệu sEMG

Personal Technologies - Tập 26 - Trang 575-586 - 2020
Yingwei Zhang1,2, Yiqiang Chen1,2,3, Hanchao Yu1, Xiaodong Yang1,2, Wang Lu1,2
1Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academic of Sciences, Beijing, China
2University of Chinese Academy of Sciences, Beijing, China
3Pengcheng Laboratory Shenzhen, China

Tóm tắt

Trong vài năm qua, nhận diện cử chỉ dựa trên tín hiệu điện cơ bề mặt (sEMG) đã nhận được sự quan tâm đáng kể. Tuy nhiên, tín hiệu sEMG nhạy cảm với nhiều yếu tố phụ thuộc vào người dùng, chẳng hạn như điện trở bề mặt da và sức mạnh cơ bắp, điều này khiến cho các mô hình nhận diện cử chỉ hiện tại không phù hợp với những người dùng mới và độ chính xác giảm mạnh. Do đó, chúng tôi đề xuất một khung học chuyển đổi hai lớp, được gọi là dualTL, nhằm nhận diện cử chỉ độc lập với người dùng dựa trên tín hiệu sEMG. DualTL bao gồm hai lớp. Lớp đầu tiên của dualTL tận dụng các mối tương quan của tín hiệu sEMG giữa các người dùng khác nhau để gán nhãn cho một phần cử chỉ với độ tin cậy cao từ những người dùng mới. Sau đó, theo sự nhất quán của tín hiệu sEMG từ cùng một người dùng, những cử chỉ còn lại được gán nhãn trong lớp thứ hai. Chúng tôi so sánh phương pháp của mình với ba phương pháp học máy phổ quát, bảy phương pháp học chuyển đổi tiêu biểu, và hai phương pháp nhận diện cử chỉ sEMG dựa trên học sâu. Kết quả thực nghiệm cho thấy độ chính xác trung bình của dualTL là 80.17%. So với SMO, KNN, RF, PCA, TCA, STL và CWT, hiệu suất cải thiện khoảng 24.26%.

Từ khóa

#nhận diện cử chỉ #sEMG #học chuyển đổi #độc lập người dùng #khung hai lớp

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