For the preliminary testing measurement, three types of shape are considered for analysis and they are
circle, square and triangle. A gait system was developed using MATLAB software to trace the motion path
back and present it in animated visualization form.
Results were shown in Figure 3, 3(a), 3(c) and 3(e) is circle, square and triangle shape mapping by left
hand motion while 3(b), 3(d) and 3(f) is for right hand motion. From observation, shapes drawn by right hand
are well presented and neat compared with left hand. Subjects from the study are all right-handed and
therefore, every single movement performed by right hand is agile and lively. The animation of the tracking
for path mapping is presented starting from the first stroke until the end, thus every sequence or order of a
drawing from movement is delivered by the GUI.
Accelerometer, gyroscope and compass data of the experiments were plotted in best 2D view. Principle
component analysis (PCA) was used to process and realign the plotting to a best 2D view. PCA is able to
reduce the number of variables in order to reduce the complexity of processing.
For the preliminary testing measurement, three types of shape are considered for analysis and they arecircle, square and triangle. A gait system was developed using MATLAB software to trace the motion pathback and present it in animated visualization form.Results were shown in Figure 3, 3(a), 3(c) and 3(e) is circle, square and triangle shape mapping by lefthand motion while 3(b), 3(d) and 3(f) is for right hand motion. From observation, shapes drawn by right handare well presented and neat compared with left hand. Subjects from the study are all right-handed andtherefore, every single movement performed by right hand is agile and lively. The animation of the trackingfor path mapping is presented starting from the first stroke until the end, thus every sequence or order of adrawing from movement is delivered by the GUI.Accelerometer, gyroscope and compass data of the experiments were plotted in best 2D view. Principlecomponent analysis (PCA) was used to process and realign the plotting to a best 2D view. PCA is able toreduce the number of variables in order to reduce the complexity of processing.
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