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Electronic Skin to Feel "Pain": Detecting "Prick" and "Hot" Pain Sensations

Sim, Minkyung and Lee, Kyung Hwa and Shin, Kwon Sik and Shin, Jeong Hee and Choi, Ji-Woong and Choi, Hongsoo and Moon, Cheil and Kim, Hyun Sik and Cho, Yuljae and Cha, Seung Nam and Jung, Jae Eun and Sohn, Jung Inn and Jang, Jae Eun (2019) Electronic Skin to Feel "Pain": Detecting "Prick" and "Hot" Pain Sensations. Soft Robotics, 6 (6). pp. 745-759. ISSN 2169-5172. doi:10.1089/soro.2018.0049.

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An artificial tactile system has attracted tremendous interest and intensive study, since it can be applied as a new functional interface between humans and electronic devices. Unfortunately, most previous works focused on improving the sensitivity of sensors. However, humans also respond to psychological feelings for sensations such as pain, softness, or roughness, which are important factors for interacting with others and objects. Here, we present an electronic skin concept that generates a “pain” warning signal, specifically, to sharp “prick” and “hot” sensations. To simplify the sensor structure for these two feelings, a single-body tactile sensor design is proposed. By exploiting “hot” feeling based on the Seebeck effect instead of the pyroelectric property, it is possible to distinguish points registering a “hot” feeling from those generating a “prick” feeling, which is based on the piezoelectric effect. The control of free carrier concentration in nanowire induced the appropriate level of Seebeck current, which enabled the sensor system to be more reliable. The first derivatives of the piezo and Seebeck output signals are the key factors for the signal processing of the “pain” feeling. The main idea can be applied to mimic other psychological tactile feelings.

Item Type:Article
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Additional Information:© 2019 Mary Ann Liebert, Inc., publishers. Online Ahead of Print: July 23, 2019.
Issue or Number:6
Record Number:CaltechAUTHORS:20190729-091522392
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Official Citation:Electronic Skin to Feel “Pain”: Detecting “Prick” and “Hot” Pain Sensations. Minkyung Sim, Kyung Hwa Lee, Kwon Sik Shin, Jeong Hee Shin, Ji-Woong Choi, Hongsoo Choi, Cheil Moon, Hyun Sik Kim, Yuljae Cho, Seung Nam Cha, Jae Eun Jung, Jung Inn Sohn, and Jae Eun Jang. Soft Robotics 2019 6:6, 745-759; doi: 10.1089/soro.2018.0049
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:97478
Deposited By: Tony Diaz
Deposited On:29 Jul 2019 17:00
Last Modified:16 Nov 2021 17:31

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