Human hands are the most sophisticated and functional organ. The human hands are, therefore, the most effective and powerful tool to do operations with various hand devices. One of the most common hand devices in the present day would be a smartphone,...
Human hands are the most sophisticated and functional organ. The human hands are, therefore, the most effective and powerful tool to do operations with various hand devices. One of the most common hand devices in the present day would be a smartphone, which is a handheld-sized touchscreen device. The previous studies on the handheld touchscreen devices focused on the thumb operations or reach zones by measuring individual muscle or joint angle. However, they were limited to thumb operations and did not consider grasping. They also did not explain hand motion in the aspect of motor control, which coordinates muscles and joint angles simultaneously.
As one of the predominant theoretical frameworks for motor control, dynamic systems theory suggests human motion in the following perspective; a motion is produced from the interaction of subsystems within individuals, tasks, and the environment. According to the theory, physical/anthropometrical properties of the human can be one of constraints that limit the movements and the human motion is explained by a concept called “synergy” which is a coordination of muscle activities or joint angles.
The purpose of this dissertation was to analyze the hand motions including grasping the handheld touchscreen devices and the thumb operations during performing the representative interactions. Anthropometrical characteristics of hands, as one of the constraints of the hand motion, were considered in the motion analysis.
In order to achieve the goal of this dissertation, firstly, the hand was classified after selecting hand dimensions which were related to the use of the devices. After dimension reduction, three common clustering methods, k-means, fuzzy c-means and latent profile analysis were applied and the results were compared to each other. The hand types were defined based on the result of cluster analysis.
Secondly, to analyze grasping the handheld touchscreen device, it was required to compare the grasp of the device to other grasps in the existing grasp taxonomy. In order to achieve this goal, the followings were accomplished: 1) defining muscular and postural synergies through dimension reduction technique, 2) identifying the grasp in the existing taxonomy in terms of the synergies, 3) attempting to allocate the grasp of the handheld touchscreen device to the taxonomy and 4) figuring out the difference between the hand types defined from the previous part.
Thirdly, the thumb operations and the grasp were investigated in terms of the muscular and postural synergies. Two tasks, dragging and tapping tasks which were the most frequently used interactions for the touchscreen devices, were involved in the experiment.
Analyzing human motion is helpful to understand motor control strategies. The expected contributions of the research are: better understanding of hand motions for using handheld touchscreen devices, designing better interactions for a smartphone or other small touchscreen devices and applying the synergies defined in this dissertation to design robot hands or prosthetic hands dealing with a problem of degree of freedom redundancy.