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METHODS AND APPARATUS FOR UNSUPERVISED ONE-SHOT MACHINE LEARNING FOR CLASSIFICATION OF HUMAN GESTURES AND ESTIMATION OF APPLIED FORCES
专利权人:
Facebook Technologies; LLC
发明人:
Alexandre Barachant
申请号:
US16288880
公开号:
US20200275895A1
申请日:
2019.02.28
申请国别(地区):
US
年份:
2020
代理人:
摘要:
Methods and apparatus for training a classification model and using the trained classification model to recognize gestures performed by a user. An apparatus comprises a processor that is programmed to: receive, via a plurality of neuromuscular sensors, a first plurality of neuromuscular signals from a user as the user performs a first single act of a gesture; train a classification model based on the first plurality of neuromuscular signals, the training including: deriving value(s) from the first plurality of neuromuscular signals, the value(s) indicative of distinctive features of the gesture including at least one feature that linearly varies with a force applied during performance of the gesture; and generating a first categorical representation of the gesture in the classification model based on the value(s); and determine that the user performed a second single act of the gesture, based on the trained classification model and a second plurality of neuromuscular signals.
来源网站:
中国工程科技知识中心
来源网址:
http://www.ckcest.cn/home/

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