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Image Analysis to Automatically Quantify Gender Bias in Movies
Many commercial films worldwide continue to express womanhood in a stereotypical manner, a recent study using image analysis showed. A KAIST research team developed a novel image analysis method for automatically quantifying the degree of gender bias in films.
The ‘Bechdel Test’ has been the most representative and general method of evaluating gender bias in films. This test indicates the degree of gender bias in a film by measuring how active the presence of women is in a film. A film passes the Bechdel Test if the film (1) has at least two female characters, (2) who talk to each other, and (3) their conversation is not related to the male characters.
However, the Bechdel Test has fundamental limitations regarding the accuracy and practicality of the evaluation. Firstly, the Bechdel Test requires considerable human resources, as it is performed subjectively by a person. More importantly, the Bechdel Test analyzes only a single aspect of the film, the dialogues between characters in the script, and provides only a dichotomous result of passing the test, neglecting the fact that a film is a visual art form reflecting multi-layered and complicated gender bias phenomena. It is also difficult to fully represent today’s various discourse on gender bias, which is much more diverse than in 1985 when the Bechdel Test was first presented.
Inspired by these limitations, a KAIST research team led by Professor Byungjoo Lee from the Graduate School of Culture Technology proposed an advanced system that uses computer vision technology to automatically analyzes the visual information of each frame of the film. This allows the system to more accurately and practically evaluate the degree to which female and male characters are discriminatingly depicted in a film in quantitative terms, and further enables the revealing of gender bias that conventional analysis methods could not yet detect.
Professor Lee and his researchers Ji Yoon Jang and Sangyoon Lee analyzed 40 films from Hollywood and South Korea released between 2017 and 2018. They downsampled the films from 24 to 3 frames per second, and used Microsoft’s Face API facial recognition technology and object detection technology YOLO9000 to verify the details of the characters and their surrounding objects in the scenes.
Using the new system, the team computed eight quantitative indices that describe the representation of a particular gender in the films. They are: emotional diversity, spatial staticity, spatial occupancy, temporal occupancy, mean age, intellectual image, emphasis on appearance, and type and frequency of surrounding objects.
Figure 1. System Diagram
Figure 2. 40 Hollywood and Korean Films Analyzed in the Study
According to the emotional diversity index, the depicted women were found to be more prone to expressing passive emotions, such as sadness, fear, and surprise. In contrast, male characters in the same films were more likely to demonstrate active emotions, such as anger and hatred.
Figure 3. Difference in Emotional Diversity between Female and Male Characters
The type and frequency of surrounding objects index revealed that female characters and automobiles were tracked together only 55.7 % as much as that of male characters, while they were more likely to appear with furniture and in a household, with 123.9% probability.
In cases of temporal occupancy and mean age, female characters appeared less frequently in films than males at the rate of 56%, and were on average younger in 79.1% of the cases. These two indices were especially conspicuous in Korean films.
Professor Lee said, “Our research confirmed that many commercial films depict women from a stereotypical perspective. I hope this result promotes public awareness of the importance of taking prudence when filmmakers create characters in films.”
This study was supported by KAIST College of Liberal Arts and Convergence Science as part of the Venture Research Program for Master’s and PhD Students, and will be presented at the 22nd ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW) on November 11 to be held in Austin, Texas.
Publication:
Ji Yoon Jang, Sangyoon Lee, and Byungjoo Lee. 2019. Quantification of Gender Representation Bias in Commercial Films based on Image Analysis. In Proceedings of the 22nd ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW). ACM, New York, NY, USA, Article 198, 29 pages. https://doi.org/10.1145/3359300
Link to download the full-text paper:
https://files.cargocollective.com/611692/cscw198-jangA--1-.pdf
Profile: Prof. Byungjoo Lee, MD, PhD
byungjoo.lee@kaist.ac.kr
http://kiml.org/
Assistant Professor
Graduate School of Culture Technology (CT)
Korea Advanced Institute of Science and Technology (KAIST)
https://www.kaist.ac.kr Daejeon 34141, Korea
Profile: Ji Yoon Jang, M.S.
yoone3422@kaist.ac.kr
Interactive Media Lab
Graduate School of Culture Technology (CT)
Korea Advanced Institute of Science and Technology (KAIST)
https://www.kaist.ac.kr Daejeon 34141, Korea
Profile: Sangyoon Lee, M.S. Candidate
sl2820@kaist.ac.kr
Interactive Media Lab
Graduate School of Culture Technology (CT)
Korea Advanced Institute of Science and Technology (KAIST)
https://www.kaist.ac.kr Daejeon 34141, Korea
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2019.10.17 View 23990 -
A Mathematical Model Reveals Long-Distance Cell Communication Mechanism
How can tens of thousands of people in a large football stadium all clap together with the same beat even though they can only hear the people near them clapping?
A combination of a partial differential equation and a synthetic circuit in microbes answers this question. An interdisciplinary collaborative team of Professor Jae Kyoung Kim at KAIST, Professor Krešimir Josić at the University of Houston, and Professor Matt Bennett at Rice University has identified how a large community can communicate with each other almost simultaneously even with very short distance signaling. The research was reported at Nature Chemical Biology.
Cells often communicate using signaling molecules, which can travel only a short distance. Nevertheless, the cells can also communicate over large distances to spur collective action. The team revealed a cell communication mechanism that quickly forms a network of local interactions to spur collective action, even in large communities.
The research team used an engineered transcriptional circuit of combined positive and negative feedback loops in E. coli, which can periodically release two types of signaling molecules: activator and repressor. As the signaling molecules travel over a short distance, cells can only talk to their nearest neighbors. However, cell communities synchronize oscillatory gene expression in spatially extended systems as long as the transcriptional circuit contains a positive feedback loop for the activator.
Professor Kim said that analyzing and understanding such high-dimensional dynamics was extremely difficult. He explained, “That’s why we used high-dimensional partial differential equation to describe the system based on the interactions among various types of molecules.” Surprisingly, the mathematical model accurately simulates the synthesis of the signaling molecules in the cell and their spatial diffusion throughout the chamber and their effect on neighboring cells.
The team simplified the high-dimensional system into a one-dimensional orbit, noting that the system repeats periodically. This allowed them to discover that cells can make one voice when they lowered their own voice and listened to the others. “It turns out the positive feedback loop reduces the distance between moving points and finally makes them move all together. That’s why you clap louder when you hear applause from nearby neighbors and everyone eventually claps together at almost the same time,” said Professor Kim.
Professor Kim added, “Math is a powerful as it simplifies complex thing so that we can find an essential underlying property. This finding would not have been possible without the simplification of complex systems using mathematics."
The National Institutes of Health, the National Science Foundation, the Robert A. Welch Foundation, the Hamill Foundation, the National Research Foundation of Korea, and the T.J. Park Science Fellowship of POSCO supported the research.
(Figure: Complex molecular interactions among microbial consortia is simplified as interactions among points on a limit cycle (right).)
2019.10.15 View 25523 -
Two Professors Recognized for the National R&D Excellence 100
< Professor Haeng-Ki Lee (left) and Professor Jeong-Ho Lee (right) >
Two KAIST professors were listed among the 2019 National R&D Excellence 100 announced by the Ministry of Science and ICT and the Korea Institute of S&T Evaluation and Planning.
Professor Haeng-Ki Lee from the Department of Civil and Environmental Engineering was recognized in the field of mechanics and materials for his research on developing new construction materials through the convergence of nano- and biotechnologies.
In the field of life and marine science, Professor Jeong-Ho Lee from the Graduate School of Medical Science and Engineering was lauded for his research of diagnostic tools and therapies for glioblastoma and pediatric brain tumors.
A certificate from the Minister of Ministry of Science and ICT will be conferred to these two professors, and their names will be inscribed on a special 2019 National R&D Excellence 100 plaque to celebrate their achievements. The professors will also be given privileges during the process of new R&D project selection.
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2019.10.15 View 10638 -
Professor Byong-Guk Park Named Scientist of October
< Professor Byong-Guk Park >
Professor Byong-Guk Park from the Department of Materials Science and Engineering was selected as the ‘Scientist of the Month’ for October 2019 by the Ministry of Science and ICT and the National Research Foundation of Korea. Professor Park was recognized for his contributions to the advancement of spin-orbit torque (SOT)-based magnetic random access memory (MRAM) technology. He received 10 million KRW in prize money.
A next-generation, non-volatile memory device MRAM consists of thin magnetic films. It can be applied in “logic-in-memory” devices, in which logic and memory functionalities coexist, thus drastically improving the performance of complementary metal-oxide semiconductor (CMOS) processors. Conventional MRAM technology is limited in its ability to increase the operation speed of a memory device while maintaining a high density.
Professor Park tackled this challenge by introducing a new material, antiferromagnet (IrMn), that generates a sizable amount of SOT as well as an exchange-bias field, which makes successful data writing possible without an external magnetic field. This research outcome paved the way for the development of MRAM, which has a simple device structure but features high speeds and density.
Professor Park said, “I feel rewarded to have forwarded the feasibility and applicability of MRAM. I will continue devoting myself to studying further on the development of new materials that can help enhance the performance of memory devices."
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2019.10.10 View 8990 -
Object Identification and Interaction with a Smartphone Knock
(Professor Lee (far right) demonstrate 'Knocker' with his students.)
A KAIST team has featured a new technology, “Knocker”, which identifies objects and executes actions just by knocking on it with the smartphone. Software powered by machine learning of sounds, vibrations, and other reactions will perform the users’ directions.
What separates Knocker from existing technology is the sensor fusion of sound and motion. Previously, object identification used either computer vision technology with cameras or hardware such as RFID (Radio Frequency Identification) tags. These solutions all have their limitations. For computer vision technology, users need to take pictures of every item. Even worse, the technology will not work well in poor lighting situations. Using hardware leads to additional costs and labor burdens.
Knocker, on the other hand, can identify objects even in dark environments only with a smartphone, without requiring any specialized hardware or using a camera. Knocker utilizes the smartphone’s built-in sensors such as a microphone, an accelerometer, and a gyroscope to capture a unique set of responses generated when a smartphone is knocked against an object. Machine learning is used to analyze these responses and classify and identify objects.
The research team under Professor Sung-Ju Lee from the School of Computing confirmed the applicability of Knocker technology using 23 everyday objects such as books, laptop computers, water bottles, and bicycles. In noisy environments such as a busy café or on the side of a road, it achieved 83% identification accuracy. In a quiet indoor environment, the accuracy rose to 98%.
The team believes Knocker will open a new paradigm of object interaction. For instance, by knocking on an empty water bottle, a smartphone can automatically order new water bottles from a merchant app. When integrated with IoT devices, knocking on a bed’s headboard before going to sleep could turn off the lights and set an alarm. The team suggested and implemented 15 application cases in the paper, presented during the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2019) held in London last month.
Professor Sung-Ju Lee said, “This new technology does not require any specialized sensor or hardware. It simply uses the built-in sensors on smartphones and takes advantage of the power of machine learning. It’s a software solution that everyday smartphone users could immediately benefit from.” He continued, “This technology enables users to conveniently interact with their favorite objects.”
The research was supported in part by the Next-Generation Information Computing Development Program through the National Research Foundation of Korea funded by the Ministry of Science and ICT and an Institute for Information & Communications Technology Promotion (IITP) grant funded by the Ministry of Science and ICT.
Figure: An example knock on a bottle. Knocker identifies the object by analyzing a unique set of responses from the knock, and automatically launches a proper application or service.
2019.10.02 View 26531 -
Professor Ki-Jun Yoon selected as the 2019 SUHF Young Investigator
< Professor Ki-Jun Yoon >
Professor Ki-Jun Yoon from the Department of Biological Sciences was named one of four recipients of the 2019 Suh Kyung-Bae Science Foundation (SUHF) Young Investigator Awards.
The SUHF is a non-profit organization established in 2016 and funded by a personal donation of 300 billion KRW in shares from Chairman and CEO Kyung-Bae Suh of the Amorepacific Group. The primary purpose of the foundation is to serve as a platform to nurture and provide comprehensive long-term support for creative and passionate young Korean scientists committed to pursuing research in the field of life sciences. The SUHF selects three to five scientists through an open recruiting process every year, and grants each scientist a maximum of 2.5 billion KRW over a period of up to five years.
Since January this year, the foundation received 83 research proposals from scientists across the nation, especially from those who had less than five years of experience as professors, and selected the four recipients, including Professor Yoon.
Professor Yoon was recognized for his contributions to the advancement of research on how post-transcriptional mechanisms may modulate stem cell properties. His research project involves deciphering the molecular mechanisms controlling RNA metabolism in neural stem cells during normal development, and how alterations in RNA regulatory programs lead to human brain disorders.
< (From left) Professor Joo-Hong Park, Professor Yuree Lee, Chairman and CEO Kyung-Bae Suh, Professor Eunjung Lee, Professor Ki-Jun Yoon, ⓒ Amorepacific Group >
The other awards were given to Professor Joo-Hong Park and Professor Yuree Lee of Seoul National University, and Professor Eunjung Lee of Boston Children's Hospital and Harvard Medical School.
The awards ceremony was held on September 18 at the Amorepacific Headquarters in Seoul.
With these four new awardees, a total of 14 scientists have been named as SUHF Young Investigators to date.
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2019.09.23 View 8281 -
KAIST to Transfer Core Tech to Domestic Companies amid Japan's Export Curbs
< Associate Vice President Kyung-Cheol Choi of the Office of University-Industry Cooperation (OUIC) at KAIST >
KAIST will transfer four core technologies related to materials, parts, and equipment to domestic companies to help them combat the latest export curbs triggered by Korea’s removal from Japan’s ‘white list’ of preferential trade partners. In addition, KAIST’s five patented technologies in the field of artificial intelligence (AI) and materials and parts will also be transferred to the companies in order to reduce the reliance on Japan and achieve technological independence through the ‘localization’ of key technologies.
KAIST announced these university-industry cooperation promotion plans at the ‘2019 KAIST Core Tech Transfer Day Conference’ held in Seoul on September 17. More than 200 entrepreneurs and investors attended the briefing and on-site consulting sessions delivered by nine KAIST professors who led the development of the technologies.
The four technologies were presented at the conference as those that can replace Japanese technologies subject to the export curbs. They include:
1. ‘Transparent fluorinated polyimide with low thermal expansion’ developed by Professor Sang-Youl Kim of the Department of Chemistry
2. ‘A non-destructive electromagnetic performance testing system’ developed by Professor Jung-Ryul Lee of the Department of Aerospace Engineering
3. ‘A nanotechnology-based electrode material for use in advanced secondary batteries’ developed by Professor Do-Kyung Kim of the Department of Materials Science and Engineering
4. ‘A high-resolution photoresist’ developed by Professor Emeritus Jin-Baek Kim of the Department of Chemistry.
Of particular interest is the non-destructive electromagnetic performance testing system technology developed by Professor Jung-Ryul Lee. This new cost-effective technology enables tests that were impossible to carry out using conventional technologies and yields a cost reduction of more than 50 percent compared to foreign technologies.
By introducing Professor Do-Kyung Kim’s new electrode material technology, the efficiency of electric vehicles can be increased. As this technology uses relatively low-cost sodium ion batteries, industries can prepare for the possible jump from the more expensive lithium batteries currently being used.
Another five patented AI and materials and parts technologies disclosed at the conference include:
1. ‘Enhanced HTTP adaptive streaming with CNN-based super-resolution’ developed by Professor Dong-soo Han of the School of Electrical Engineering
2. ‘Method and apparatus of brain-computer interface design for estimating choice behavior and decision strategy’ developed by Professor Sang-Wan Lee of the Department of Bio and Brain Engineering
3. ‘Eco-friendly fabrication of metal oxide nanoparticles and fabrication of non-toxic polymer sunscreen ingredients by electron irradiation’ developed by Professor Sung-Oh Cho of the Department of Nuclear and Quantum Engineering
4. ‘High-density nanofiber yarn-based coloricmetric gas sensors’ developed by Professor Il-Doo Kim of the Department of Materials Science and Engineering
5. ‘Silicon-pocket energy storage electrode with high energy density and its manufacturing technology’ developed by Professor Jeung-Ku Kang of the Graduate school of EEWS.
The patented nanofiber-based coloricmetric gas sensor technology developed by Professor Il-Doo Kim allows for the diagnosis of diseases by only using the patient’s respiration. Due to its high productivity and processability, it is expected to be applied to various fields in the fast-growing disease diagnosis sensor market, which includes mobile devices and wearable sensors.
Moreover, Professor Dong-soo Han’s patented adaptive streaming technology attracted attention along with the ever-growing Over The Top (OTT) and Video On Demand (VOD) service markets, since it has significant potential for improving the streaming quality of videos and reducing costs for video providers.
Professor Kyung-Cheol Choi, the Associate Vice President of the Office of University-Industry Cooperation (OUIC) at KAIST, said, “KAIST OUIC and KAIST Advisors on Materials and Parts (KAMP) have been working tirelessly to help Korean companies cope with the recent Japanese export restrictions. KAIST’s efforts will enhance the competitiveness and growth of the Korean industry and economy, turning this national crisis into opportunity.”
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2019.09.20 View 6491 -
Sungjoon Park Named Google PhD Fellow
PhD candidate Sungjoon Park from the School of Computing was named a 2019 Google PhD Fellow in the field of natural language processing. The Google PhD fellowship program has recognized and supported outstanding graduate students in computer science and related fields since 2009. Park is one of three Korean students chosen as the recipients of Google Fellowships this year. A total of 54 students across the world in 12 fields were awarded this fellowship.
Park’s research on computational psychotherapy using natural language processing (NLP) powered by machine learning earned him this year’s fellowship. He presented of learning distributed representations in Korean and their interpretations during the 2017 Annual Conference of the Association for Computational Linguistics and the 2018 Conference on Empirical Methods in Natural Language Processing. He also applied machine learning-based natural language processing into computational psychotherapy so that a trained machine learning model could categorize client's verbal responses in a counseling dialogue. This was presented at the Annual Conference of the North American Chapter of the Association for Computational Linguistics.
More recently, he has been developing on neural response generation model and the prediction and extraction of complex emotion in text, and computational psychotherapy applications.
2019.09.17 View 7839 -
Algorithm Identifies Optimal Pairs for Composing Metal-Organic Frameworks
The integration of metal-organic frameworks (MOFs) and other metal nanoparticles has increasingly led to the creation of new multifunctional materials. Many researchers have integrated MOFs with other classes of materials to produce new structures with synergetic properties.
Despite there being over 70,000 collections of synthesized MOFs that can be used as building blocks, the precise nature of the interaction and the bonding at the interface between the two materials still remains unknown. The question is how to sort out the right matching pairs out of 70,000 MOFs.
An algorithmic study published in Nature Communications by a KAIST research team presents a clue for finding the perfect pairs. The team, led by Professor Ji-Han Kim from the Department of Chemical and Biomolecular Engineering, developed a joint computational and experimental approach to rationally design MOF@MOFs, a composite of MOFs where an MOF is grown on a different MOF.
Professor Kim’s team, in collaboration with UNIST, noted that the metal node of one MOF can coordinately bond with the linker of a different MOF and the precisely matched interface configurations at atomic and molecular levels can enhance the likelihood of synthesizing MOF@MOFs.
They screened thousands of MOFs and identified optimal MOF pairs that can seamlessly connect to one another by taking advantage of the fact that the metal node of one MOF can form coordination bonds with the linkers of the second MOF. Six pairs predicted from the computational algorithm successfully grew into single crystals.
This computational workflow can readily extend into other classes of materials and can lead to the rapid exploration of the composite MOFs arena for accelerated materials development. Even more, the workflow can enhance the likelihood of synthesizing MOF@MOFs in the form of large single crystals, and thereby demonstrated the utility of rationally designing the MOF@MOFs.
This study is the first algorithm for predicting the synthesis of composite MOFs, to the best of their knowledge. Professor Kim said, “The number of predicted pairs can increase even more with the more general 2D lattice matching, and it is worth investigating in the future.”
This study was supported by Samsung Research Funding & Incubation Center of Samsung Electronics.
(Figure: An example of a rationally synthesized MOF@MOFs (cubic HKUST-1@MOF-5 ))
2019.08.30 View 15847 -
Researchers Describe a Mechanism Inducing Self-Killing of Cancer Cells
(Professor Kim (left) and lead author Lee)
Researchers have described a new mechanism which induces the self-killing of cancer cells by perturbing ion homeostasis. A research team from the Department of Biochemical Engineering has developed helical polypeptide potassium ionophores that lead to the onset of programmed cell death. The ionophores increase the active oxygen concentration to stress endoplasmic reticulum to the point of cellular death.
The electrochemical gradient between extracellular and intracellular conditions plays an important role in cell growth and metabolism. When a cell’s ion homeostasis is disturbed, critical functions accelerating the activation of apoptosis are inhibited in the cell.
Although ionophores have been intensively used as an ion homeostasis disturber, the mechanisms of cell death have been unclear and the bio-applicability has been limited. In the study featured at Advanced Science, the team presented an alpha helical peptide-based anticancer agent that is capable of transporting potassium ions with water solubility. The cationic, hydrophilic, and potassium ionic groups were combined at the end of the peptide side chain to provide both ion transport and hydrophilic properties.
These peptide-based ionophores reduce the intracellular potassium concentration and at the same time increase the intracellular calcium concentration. Increased intracellular calcium concentrations produce intracellular reactive oxygen species, causing endoplasmic reticulum stress, and ultimately leading to apoptosis.
Anticancer effects were evaluated using tumor-bearing mice to confirm the therapeutic effect, even in animal models. It was found that tumor growth was strongly inhibited by endoplasmic stress-mediated apoptosis.
Lead author Dr. Dae-Yong Lee said, “A peptide-based ionophore is more effective than conventional chemotherapeutic agents because it induces apoptosis via elevated reactive oxygen species levels. Professor Yeu-Chun Kim said he expects this new mechanism to be widely used as a new chemotherapeutic strategy. This research was funded by the National Research Foundation.
2019.08.28 View 19171 -
Distinguished Professor Sukbok Chang Donates His Prize Money
The honoree of the 2019 Korea Best Scientist and Technologist Award, Distinguished Professor Sukbok Chang donated his prize money of one hundred million KRW to the Chemistry Department Scholarship Fund and the Lyu Keun-Chul Sports Complex Management Fund during a donation ceremony last week.
Professor Chang won the award last month in recognition of his pioneering achievements and lifetime contributions to the development of carbon-hydrogen activation strategies, especially for carbon-carbon, carbon-nitrogen, and carbon-oxygen formations. Professor Chang, a world renowned chemist, has been recognized for his highly selective catalytic systems, allowing the controlled defunctionalization of bio-derived platform substrates under mild conditions and opening a new avenue for the utilization of biomass-derived platform chemicals.
“All my achievements are the results of my students’ hard work and dedication. I feel very fortunate to have such talented team members. I want to express my sincere gratitude for such a great research environment that we have worked together in so far,” said Professor Chang at the ceremony.
KAIST President Sung-Chul Shin said, “Not only will Professor Chang’s donation make a significant contribution to the Department of Chemistry, but also to the improvement of the Lyu Keun-Chul Sports Complex’s management, which directly links to the health and welfare of the KAIST community.”
Professor Chang currently holds the position of distinguished professor at KAIST and director of the Center for Catalytic Hydrocarbon Functionalizations in the Institute for Basic Science (IBS). He previously received the Kyung-Ahm Academic Award in 2013 and the Korea Toray Science Award in 2018. All these prize money also went to the school.
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2019.08.26 View 7471 -
Highly Uniform and Low Hysteresis Pressure Sensor to Increase Practical Applicability
< Professor Steve Park (left) and the First Author Mr. Jinwon Oh (right) >
Researchers have designed a flexible pressure sensor that is expected to have a much wider applicability. A KAIST research team fabricated a piezoresistive pressure sensor of high uniformity with low hysteresis by chemically grafting a conductive polymer onto a porous elastomer template.
The team discovered that the uniformity of pore size and shape is directly related to the uniformity of the sensor. The team noted that by increasing pore size and shape variability, the variability of the sensor characteristics also increases.
Researchers led by Professor Steve Park from the Department of Materials Science and Engineering confirmed that compared to other sensors composed of randomly sized and shaped pores, which had a coefficient of variation in relative resistance change of 69.65%, their newly developed sensor exhibited much higher uniformity with a coefficient of variation of 2.43%. This study was reported in Small as the cover article on August 16.
Flexible pressure sensors have been actively researched and widely applied in electronic equipment such as touch screens, robots, wearable healthcare devices, electronic skin, and human-machine interfaces. In particular, piezoresistive pressure sensors based on elastomer‐conductive material composites hold significant potential due to their many advantages including a simple and low-cost fabrication process.
Various research results have been reported for ways to improve the performance of piezoresistive pressure sensors, most of which have been focused on increasing the sensitivity. Despite its significance, maximizing the sensitivity of composite-based piezoresistive pressure sensors is not necessary for many applications. On the other hand, sensor-to-sensor uniformity and hysteresis are two properties that are of critical importance to realize any application.
The importance of sensor-to-sensor uniformity is obvious. If the sensors manufactured under the same conditions have different properties, measurement reliability is compromised, and therefore the sensor cannot be used in a practical setting.
In addition, low hysteresis is also essential for improved measurement reliability. Hysteresis is a phenomenon in which the electrical readings differ depending on how fast or slow the sensor is being pressed, whether pressure is being released or applied, and how long and to what degree the sensor has been pressed. When a sensor has high hysteresis, the electrical readings will differ even under the same pressure, making the measurements unreliable.
Researchers said they observed a negligible hysteresis degree which was only 2%. This was attributed to the strong chemical bonding between the conductive polymer and the elastomer template, which prevents their relative sliding and displacement, and the porosity of the elastomer that enhances elastic behavior.
“This technology brings forth insight into how to address the two critical issues in pressure sensors: uniformity and hysteresis. We expect our technology to play an important role in increasing practical applications and the commercialization of pressure sensors in the near future,” said Professor Park.
This work was conducted as part of the KAIST‐funded Global Singularity Research Program for 2019, and also supported by the KUSTAR‐KAIST Institute.
Figure 1. Image of a porous elastomer template with uniform pore size and shape (left), Graph showing high uniformity in the sensors’ performance (right).
Figure 2. Hysteresis loops of the sensor at different pressure levels (left), and after a different number of cycles (right).
Figure 3. The cover page of Small Journal, Volume 15, Issue 33.
Publication:
Jinwon Oh, Jin‐Oh Kim, Yunjoo Kim, Han Byul Choi, Jun Chang Yang, Serin Lee, Mikhail Pyatykh, Jung Kim, Joo Yong Sim, and Steve Park. 2019. Highly Uniform and Low Hysteresis Piezoresistive Pressure Sensors Based on Chemical Grafting of Polypyrrole on Elastomer Template with Uniform Pore Size. Small. Wiley-VCH Verlag GmbH & Co. KgaA, Weinheim, Germany, Volume No. 15, Issue No. 33, Full Paper No. 201901744, 8 pages. https://doi.org/10.1002/smll.201901744
Profile: Prof. Steve Park, MS, PhD
stevepark@kaist.ac.kr
http://steveparklab.kaist.ac.kr/
Assistant Professor
Organic and Nano Electronics Laboratory
Department of Materials Science and Engineering
Korea Advanced Institute of Science and Technology (KAIST)
http://kaist.ac.kr
Daejeon 34141, Korea
Profile: Mr. Jinwon Oh, MS
jwoh1701@gmail.com
http://steveparklab.kaist.ac.kr/
Researcher
Organic and Nano Electronics Laboratory
Department of Materials Science and Engineering
Korea Advanced Institute of Science and Technology (KAIST)
http://kaist.ac.kr Daejeon 34141, Korea
Profile: Prof. Jung Kim, MS, PhD
jungkim@kaist.ac.kr
http://medev.kaist.ac.kr/
Professor
Biorobotics Laboratory
Department of Mechanical Engineering
Korea Advanced Institute of Science and Technology (KAIST)
http://kaist.ac.kr Daejeon 34141, Korea
Profile: Joo Yong Sim, PhD
jsim@etri.re.kr
Researcher
Bio-Medical IT Convergence Research Department
Electronics and Telecommunications Research Institute (ETRI)
https://www.etri.re.krDaejeon 34129, Korea
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2019.08.19 View 26676