首页|Reports from Virginia Polytechnic Institute and State University (Virginia Tech) Provide New Insights into Support Vector Machines (Use of a Wearable Electromyo graphy Armband To Detect Liftlower Tasks and Classify Hand Loads)
Reports from Virginia Polytechnic Institute and State University (Virginia Tech) Provide New Insights into Support Vector Machines (Use of a Wearable Electromyo graphy Armband To Detect Liftlower Tasks and Classify Hand Loads)
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 Daily News – Researchers detail new data in Support Vector Machines. According to news originatingfrom Blacksburg, Virginia, by Ne wsRx correspondents, research stated, “We used an armband withembedded surface electromyography (sEMG) electrodes, together with machinelearning (ML) models, t oautomatically detect lifting-lowering activities and classify hand loads. Nine healthy participants (4 maleand 5 female) completed simulated lifting-lowering tasks in various conditions and with two different handloads (2.3 and 6.8 kg). ”
BlacksburgVirginiaUnited StatesNor th and Central AmericaEmerging TechnologiesMachine LearningSupport Vector MachinesVector MachinesVirginia Polytechnic Institute and State University ( Virginia Tech)
NETL
NSTL
