MRS Meetings and Events

 

SB08.04.05 2023 MRS Spring Meeting

A Self-Powered, Single Sensor for Both Dynamic and Static Pressure by Mimicking the Sensory Adaptation Behavior of Skin

When and Where

Apr 12, 2023
9:15am - 9:30am

Moscone West, Level 2, Room 2012

Presenter

Co-Author(s)

Ey-In Lee1,Jin-Woo Park1

Yonsei University1

Abstract

Ey-In Lee1,Jin-Woo Park1

Yonsei University1
The tactile sensor can be applied to various technical fields like electronic-skin technology, human-machine interface, prosthetics, and robotics. Particularly, the technology with feedback systems like haptic interfaces necessitates a sensitive, multimodal, flexible sensor for an actuator to give elaborate tactile sensations to the users. Pressure, one of the most important stimuli that the haptic interfaces should acquire, can be divided into two concepts: dynamic pressure and static pressure. To elaborately sense and apply the sensations of the pressure, it is crucial to detect the moment of the pressure application and whether the pressure application is continued. Like as mechanoreceptors of the human skin are divided into fast-adapting mechanoreceptors (Meissner corpuscle, Pacinian corpuscle) and slow-adapting mechanoreceptors (Merkel disc, Ruffini corpuscle), researchers integrate two sensors that detect dynamic and static pressure each into a single platform to discriminate the dynamic and static pressure. However, the integrated sensing system is inconsistent with the direction of the tactile sensing-related technology development that continues to develop as a system containing the sensing ability of various stimuli generated by the humans or external environment and the feedback control to interact with humans. While wearability and implantability of the system are developed for high compatibility with humans, a conventional integrated sensing system with batteries and signal processors is bulky, limits continuous operation with a fixed energy capacity, and restricts practical usage due to frequent charging. Accordingly, the integrated sensing system with energy issues and the volumetric problem is inadequate for human-linked technology. In this work, we propose a self-powered, single sensor with a compact structure using piezoelectricity and ionics as sensing mechanisms with mimicry of the sensory adaptation behavior of the human skin. Piezoelectricity is responsible for detecting dynamic pressure, and ionics is responsible for detecting static pressure and expressing the sensory adaptation behavior. Since the piezoelectric materials can only respond to dynamic pressure, we introduced the ions slower than the piezoelectric charges to sense the static pressure. Since the ions can hold the piezoelectric charges from moving to the electrode, they delay the charges from being measured by the instrument. The static pressure can be detected by analyzing a prolonged piezoelectric voltage output achieved from the introduction of the ions. We utilized the piezoelectric polymer, poly(vinylidene fluoride-<i>co</i>-trifluoroethylene) (P(VDF-TrFE)), and ionic liquid, 1-Ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([EMIM][TFSI]) to achieve intrinsic mechanical flexibility and non-volatility of the sensing layer. Electrochemical impedance spectroscopy verified the stable sensor fabrication and the equivalent electrical circuit of the tactile sensor. Emulated systems based on EIS data proved the sensing mechanism and sensory adaptation behavior quantified by the decay constant. With sensory adaptation behavior, the sensitivity of the dynamic pressure increased about 4.4 times, and the sensitivity of the static pressure increased about 4 times. The tactile sensor with sensory adaptation behavior can detect the overlapped stimulus upon sustained pressure with higher sensitivity. The tactile sensor that can elaborately analyze the pressure and sense the overlapped stimulus is vital in a stimuli-flourishing environment where it is more important to detect newly applied stimulus than sustained one.

Symposium Organizers

Matteo Bianchi, University of Pisa
Charles Dhong, University of Delaware
Marcia O'Malley, William Marsh Rice University
Tristan Trutna, Facebook Reality Labs

Publishing Alliance

MRS publishes with Springer Nature