A Framework for Estimating Hand Strength from Grip and Tremor
Human fingers supported by palm area act as interfaces to perform various actions with real world. Grip and tremor are physiological phenomena associated with the human hand that exhibit dependence on various health issues. In this paper, Electro Tactile Gram (ETG) is proposed as sensory setup capab...
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Published in | 2024 3rd International Conference on Artificial Intelligence For Internet of Things (AIIoT) pp. 1 - 6 |
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Main Authors | , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
03.05.2024
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Subjects | |
Online Access | Get full text |
DOI | 10.1109/AIIoT58432.2024.10574664 |
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Summary: | Human fingers supported by palm area act as interfaces to perform various actions with real world. Grip and tremor are physiological phenomena associated with the human hand that exhibit dependence on various health issues. In this paper, Electro Tactile Gram (ETG) is proposed as sensory setup capable of measuring grip and tremor. It comprises of piezo sensor discs mounted on mouse shaped substrate that is referred to as Clinical Mouse (CM). Five sensors are fixed on CM surface by pegging finger-tip locations acquired from different hand sizes. The CM acquires static voltage measurement for grip and dynamic voltage measurement for tremor. Experiments performed with 8 healthy users depict noticeable difference between tight and hold postures for grip, when fingers are placed one at a time on pegged locations on the CM. Likewise, we formulate tremor in terms of features such as max-min variation of voltage and frequency by applying one finger at a time on CM. The grip statistics is estimated from 8 users and covers max, min and average for hold and tight postures. All chosen test subjects are healthy men in age group of 30 - 40 years, who use their hands to perform light job such as data entry from keyboard. Similarly, max, min trends of peak - to - peak voltage and frequency are also observed for tremor data from 4 healthy users. The proposed ETG framework offers first of its kind, robust and low-cost setup conjectured for use in clinical applications based on hand strength. |
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DOI: | 10.1109/AIIoT58432.2024.10574664 |