首页|Sakarya University of Applied Sciences Reports Findings in Machine Learning (Met a-heuristic optimization algorithms based feature selection for joint moment pre diction of sit-to-stand movement using machine learning algorithms)
Sakarya University of Applied Sciences Reports Findings in Machine Learning (Met a-heuristic optimization algorithms based feature selection for joint moment pre diction of sit-to-stand movement using machine learning algorithms)
扫码查看
点击上方二维码区域,可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – New research on Machine Learning is the subject o f a report. According to news reportingoriginating in Sakarya, Turkey, by NewsR x journalists, research stated, “The sit-to-stand (STS) movementis fundamental in daily activities, involving coordinated motion of the lower extremities and t runk, whichleads to the generation of joint moments based on joint angles and l imb properties. Traditional methods fordetermining joint moments often involve sensors or complex mathematical approaches, posing limitationsin terms of movem ent restrictions or expertise requirements.”