Using electrical impedance tomography (EIT), researchers have developed a system using a flexible tactile sensor for objective evaluation of fine finger movements. Demonstrating high accuracy in classifying diverse pinching motions, with discrimination rates surpassing 90 percent, this innovation holds potential in cognitive development and automated medical research.

Fine motor skills play a crucial role in human cognition, influencing everything from daily activities to the development of advanced tool-based civilizations. Yet, quantifying and evaluating these skills objectively has been a challenge. Conventional techniques like video coding, although efficient, are time-intensive and susceptible to coder bias. Additionally, existing technologies like marker less motion capture or hand-attached devices have limitations, especially when assessing infants’ finger movements.

The device, comprising four layers including a flexible tactile sensor based on EIT, has a cylindrical shape akin to the FDT pegboard (functional dexterity test). This setup enables precise measurement of pinching motions. Using a flexible printed circuit board with 16 electrodes and conductive materials, the sensor captured voltage data from different finger movements. (Image Credit: Hiroki Sato/SIT)

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Topics:
Data acquisition and handling Data exchange Flexible Sensors Human machine interface (HMI) Medical Medical, health and wellness Mental processes Psychiatry and psychology Research and development Sensors Sensors and actuators

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    This article first appeared in the July, 2024 issue of Medical Design Briefs Magazine (Vol. 14 No. 7).

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