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Reading the Optical Fingerprint of Materials in Real-Time with AI
< (From Left) KAIST Dr. Jongchan Kim, Professor Sanghoo Park >
Just as every person has a unique fingerprint, every material has its own unique ‘optical fingerprint.’ Spectroscopy, which has identified materials without contact in fields ranging from semiconductor processes to environmental monitoring, disease diagnosis, and space research, has been called the ‘eyes of science.’ A KAIST research team has implemented spectroscopic analysis, which previously relied on the experience of experts, into AI-based automatic and real-time interpretation technology, greatly expanding its applicability in various industrial fields such as semiconductors, environment, and medicine.
The research team led by Professor Sanghoo Park of our university's Department of Nuclear and Quantum Engineering announced on the 3rd that they have developed ‘AI-based deep spectral interpretation technology’ that allows artificial intelligence to automatically interpret various spectral data in real-time, overcoming limitations such as noise, contamination, defects, and complex overlapping signals.
A spectrum is a graph that spreads out light emitted or absorbed by a material like a rainbow. Existing spectroscopic analysis had to manually analyze signals appearing as numbers in this spectrum by comparing them one by one with well-known reference data. Instead of this method, the research team enabled the artificial intelligence to recognize the entire spectrum as a single ‘image’ and learn its patterns.
< Deep learning-based spectrum technology >
As a result, even in situations where noise was mixed in the data or some parts were lost, the AI accurately identified material information as if it were recognizing an object in a photo. Furthermore, it equipped a function to self-check whether the prediction results are scientifically valid, significantly increasing the reliability of the analysis.
The research team verified this technology by applying it to absorption spectroscopy data widely used in atmospheric and plasma chemistry. As a result, they succeeded in predicting the concentrations of eight chemical substances, including ozone and nitrogen oxides, with very high accuracy even among complexly mixed signals. It was not only more accurate than existing manual analysis but also showed stable performance even in environments with poor data quality.
This research is expected to be a turning point in converting vast amounts of spectroscopic data, which were previously discarded due to the difficulty of analysis, into ‘immediately usable information.’ In particular, it has high potential for use in various high-tech industrial fields, such as improving yield in semiconductor plasma processes, stable control of nuclear fusion plasma, environmental monitoring in smart cities, and non-contact disease diagnosis.
< Research Image >
Professor Sanghoo Park said, “This technology is an achievement that significantly lowers the entry barrier for spectroscopic data analysis, which used to rely on the experience of experts,” and added, “It can be immediately applied to overall industries requiring spectral analysis, such as environmental monitoring, healthcare, and plasma diagnosis.”
In this study, doctoral students Jongchan Kim and Seong-Cheol Huh participated as co-first authors, and Jin Hee Bae and Su-Jin Shin also contributed to the research. The results were published online on January 12th in the prestigious international academic journal in the field of measurement and analytical chemistry, ‘Sensors and Actuators B: Chemical.’
※ Paper title: Deep spectral deconvolution for image-based broadband spectral data analysis DOI: https://doi.org/10.1016/j.snb.2025.139369
Meanwhile, this research was conducted with support from the Ministry of Science and ICT’s Global TOP Strategic Research Group Support Program, the KAIST Leap Research Project, and the Korea Institute of Materials Science (KIMS).
2026.02.03 View 3681 -
Accurate Real time ECG Measurement While Comfortably Lying Down at Home
< (From left) Professor Chul Kim of the Department of Bio and Brain Engineering, Ph.D. candidate Minjae Kim, researcher Premravee Teeravichayangoon >
KAIST's research team has developed a technology that can measure electrocardiogram (ECG) and heart rate variability (HRV) in real time by simply lying on a bed with clothes on, without having to go to the hospital. This technology is expected to evolve into a daily heart health monitoring platform in conjunction with remote healthcare, and further expand into various bio-healthcare fields such as sleep and stress analysis, contributing to personalized prevention and early diagnosis for patients.
KAIST announced on the 19th that Professor Chul Kim's research team from the Department of Bio and Brain Engineering has developed an 'in-bed cardiac monitoring on-device system'.
The research team manufactured a flexible substrate sensor that integrates the electronic circuit and electrodes into one to increase precision, and implemented an integrated system that can perform signal-noise separation, heart beat signal (R-peak) detection, and heart rate variability analysis in real time through on-device signal processing.
Existing ECG measurement had the inconvenience of visiting a hospital, taking off clothes, and attaching wet electrodes to the skin. Because of this, long-term monitoring was difficult, and it was not easy for the elderly or patients with chronic diseases to use it daily. Non-contact methods also had a technical limitation of being vulnerable to external noise.
To solve these problems, the research team applied a circuit that blocks external noise (active shielding) and a circuit that stably captures minute current changes in the human body (right-leg drive circuit). In addition, they implemented a mathematical transformation technique (wavelet transform) that extracts only the important parts from the heart beat signal and a calculation method (peak detection algorithm) that accurately identifies the moment of the heart's electrical beat (R-peak) as on-device signal processing techniques, allowing for precise real-time analysis of the signal.
As a result, users can obtain stable and accurate ECG signals even when lying on their backs with clothes on.
< Figure. Overall structural diagram of the developed non-contact in-bed cardiac monitoring on-device system, schematic diagram of the R-peak detection algorithm, real-time ECG and HRV measurement screen >
This research presents new possibilities for managing chronic cardiovascular diseases and supporting the health of the elderly, as it can be easily used not only in hospitals but also at home.
Professor Chul Kim said, "This system, which can extract signals in real time even in a noisy environment, can be used to easily check heart health in daily life," and added, "In the future, it will become the foundation of sleep health management by adding the measurement of various bio-signals."
This paper, in which Ph.D. candidate Minjae Kim and researcher Premravee Teeravichayangoon from the Department of Bio and Brain Engineering participated as co-first authors, was published online in the international journal 'Biosensors and Bioelectronics' on August 9, 2025.
※ Paper title: A homecare in-bed hardware system for precise real-time ECG and HRV monitoring with layered clothing. DOI: https://doi.org/10.1016/j.bios.2025.117838
※ Author information: Minjae Kim (KAIST Department of Bio and Brain Engineering, First Author), Premravee Teeravichayangoon (KAIST Department of Bio and Brain Engineering, First Author), Chul Kim (KAIST Department of Bio and Brain Engineering, Corresponding Author)
Meanwhile, this research was carried out with the support of the National Research Foundation of Korea's Basic Research Lab and Bio-medical Technology Development Project, and the KAIST-Ceragem Future Healthcare Research Center.
2025.09.19 View 4180 -
Low Cost and Simple Gene Analysis Technology Developed
Professor Park Hyun Kyu of the Department of Biology and Chemical Engineering has developed a ‘real time CPR’ using Methylene Blue (nucleic acid bonding molecule with Electro-Chemical property).
The current gene analysis being used in the field is the real time PCR (Polymerase Chain Reaction) which takes advantage of the luminescent property of the gene and therefore requires expensive machines and chemicals to run.
By contrast, the electro-chemical method is easy to use and low cost and, most importantly, it allows the machine to become small and portable.
Professor Park’s research team used the decrease in the electro-chemical signal when the Methylene Blue reacts with nucleic acid and applied this to PCR which allowed for the real time analysis of the nucleic acid amplification process.
With the result of the experiment as the basis, the team was able to perform a trial with Chlamydia trachomatis, a pathogen that causes sexually transmitted disease.
The result showed that the electro-chemical method showed the same performance level as the real time PCR, which proved that the technology can be applied to diagnosing various diseases and gene research.
2011.04.30 View 15071 -
Ju-pyeong Lee won the Best Paper Award from IEEE RTAS
Ju-pyeong Lee, doctoral student of the Dept. of Electrical Engineering of KAIST, received the Best Paper Award from the 11th Institute of Electrical and Electronics Engineers Real-Time and Embedded Technology and Applications Symposium (IEEE RTAS) sponsored by IEEE TC on Real Time System and supported from the U.S. National Science Foundation.
He is in the Computer Engineering laboratory, and won the honor by his research of technique of Delayed Locking Technique for Improving Real-Time Performance of Embedded Linux by Prediction of Timer Interrupt. His paper was selected to be the best because of its practicality. His research purposed the technique that can dramatically improve real time problem, which was indicated to be the big problem of Linux. Moreover, he presented the way to easily materialize this technique in the practical system.
Best Paper Award is the prize awarded by IEEE Computer Society in the recognition of outstanding achievement in the field of real time system and embedded technology.
IEEE RTAS is a symposium held annually by IEEE. In this year, the 11th symposium was held from March 7 to March 10, for four days, in San Francisco, United States. The purpose of this year symposium was to seek papers describing significant contributions both to state of the art and state of the practice in the broad field of embedded and open real-time computing, control, and communication. Therefore, it especially focused on online real-time and embedded applications ranging from industrial embedded applications such as aeronautics and automotive systems to open multimedia, telecommunication and mobile computing systems.
Approximately 200 related erudite from almost 20 countries including United States, England, France, Germany, Italy, and Sweden participated in this symposium. Total number of papers submitted to IEEE RTAS was 158, while only 53 of them were selected.
by Hye-jung Won / Staff ReporterApril, 2005 / The KAIST Herald
2005.04.12 View 27771