1,721,002 research outputs found
การลดสัญญาณรบกวนในสัญญาณไฟฟ้ากล้ามเนื้อและการหาลักษณะเด่นที่เหมาะสม สำหรับการจำแนกรูปแบบการเคลื่อนไหวของแขนท่อนล่าง
No full textThesis (Ph.D, Electrical Engineering)--Prince of Songkla University, 201
An Investigation of Temporally Inspired Time Domain Features for Electromyographic Pattern Recognition
No full textEMG Pattern Recognition in the Era of Big Data and Deep Learning
No full textThe increasing amount of data in electromyographic (EMG) signal research has greatly increased the importance of developing advanced data analysis and machine learning techniques which are better able to handle “big data”. Consequently, more advanced applications of EMG pattern recognition have been developed. This paper begins with a brief introduction to the main factors that expand EMG data resources into the era of big data, followed by the recent progress of existing shared EMG data sets. Next, we provide a review of recent research and development in EMG pattern recognition methods that can be applied to big data analytics. These modern EMG signal analysis methods can be divided into two main categories: (1) methods based on feature engineering involving a promising big data exploration tool called topological data analysis; and (2) methods based on feature learning with a special emphasis on “deep learning”. Finally, directions for future research in EMG pattern recognition are outlined and discussed
The Relationship between Anthropometric Variables and Features of Electromyography Signal for Human–Computer Interface
No full text
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
EMG denoising estimation based on adaptive wavelet thresholding for multifunction myoelectric control
No full text- …
