Abstract—We have been developing diverse promising and radical analysis systems to address various agricultural challenges in our sequential studies. One purpose of this prospective research was to verify and demonstrate the accuracy and utility of our kinematic visual analysis system, which was based on the recent Scilab series platform for Windows 10 OS, and to present qualitative and quantitative differences of unique parameters between groups of experienced and inexperienced agricultural workers. We used the latest Scilab PC program libraries and packages to investigate, select, and execute both 2D and 3D timeline wavelet analyses, including SURF 3D expressions with accumulated fundamental data from our subjects. From these results, we were able to show various charts and a range of differences between experienced and inexperienced subjects. Our target field was situated in a common outdoor farm in Japan, and the target work was common tilling (cultivating) using a general hoe, i.e., one of the most common movements worldwide. These visual methods of analyzing digital data could be of practical use in providing important indicators concerning the improvement of the users’ working movements and habits in outdoor fields.
 

Index Terms—wavelet analysis, Scilab, SURF 3D expression, indicators for agricultural workers, time-line acceleration data

Cite: Shinji Kawakura and Ryosuke Shibasaki, "3D Wavelet Analysis of Movement Acceleration Data in Agricultural Workers Using a Hoe," Journal of Advanced Agricultural Technologies, Vol. 5, No. 1, pp. 78-85, March 2018. Doi: 10.18178/joaat.5.1.78-85