Grasp Behavior Analysis Using Muscle and Postural Hand Synergies for Smartphones
| Autor: | Youngjin Na, Sanghyun Kwon, Myung Hwan Yun, Sung Hee Ahn |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
medicine.diagnostic_test Computer science Mechanical Engineering education GRASP Healthy subjects 02 engineering and technology Kinematics Electromyography Thumb Industrial and Manufacturing Engineering law.invention body regions 020303 mechanical engineering & transports 020901 industrial engineering & automation Touchscreen medicine.anatomical_structure 0203 mechanical engineering Human–computer interaction law medicine Electrical and Electronic Engineering Cluster analysis Mobile device |
| Zdroj: | International Journal of Precision Engineering and Manufacturing. 22:697-707 |
| ISSN: | 2005-4602 2234-7593 |
| Popis: | Smartphones are currently among the most common handheld devices. Previous studies on such handheld touchscreen devices focused on thumb operations or reach zones by measuring individual muscle or joint angles. However, they were limited to thumb operations and did not consider grasping. In this study, we investigated the grasp types of touchscreen devices and other objects included in an existing grasp taxonomy. To this end, principal component analysis and latent profile analysis clustering were used for extracting and grouping muscle and postural synergies. Fourteen healthy subjects performed up to 15 hand grasps, including that with a smartphone. Electromyography (EMG) data were measured on six muscles in the forearm and the hand, and joint angles were measured for 22 joints in the hand. The first two muscle synergies from the EMG data and the first three postural synergies from the kinematic data were found to account for over 60% of the overall grasping. In terms of the synergies, the grasp for handheld touchscreen devices showed unique characteristics in terms of muscle and postural synergies compared to other objects. The obtained results may aid in understanding of grasping behaviors for handheld touchscreen devices in various applications. |
| Databáze: | OpenAIRE |
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