Smoothing of EMG and heart rate profile with spline function and forecasting with neural network

Autor:	Jun Usuki, Yoshimitsu Yokota, Masatoshi Kitaoka
Rok vydání:	1999
Předmět:	Engineering General Computer Science Artificial neural network business.industry Physics::Medical Physics General Engineering Pattern recognition body regions Spline (mathematics) Heart rate Waveform Artificial intelligence business Material handling Smoothing
Zdroj:	Computers & Industrial Engineering. 37:403-406
ISSN:	0360-8352
DOI:	10.1016/s0360-8352(99)00104-7
Popis:	This paper presents the method of forecasting what waveform is obtained from EMG and a heart rate depending on the weight of a product to be handled a handling distance, height or working frequency when doing manual material handling. The forecasting of a heart rate and EMG is used with spline function and neural network. Spline function can be smoothed extermely fluctuating biological signal.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::7bd0bc2d7600c0b483a6d1d3044aa17f https://doi.org/10.1016/s0360-8352(99)00104-7 Zobrazit plný text záznamu Full Text from ScienceDirect