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Machine-learned wearable sensors for real-time hand-motion recognition: toward practical applications

National Science Review 2024年第2期11卷 231-263页

作者： Kyung Rok Pyun Kangkyu Kwon Myung Jin Yoo Kyun Kyu Kim Dohyeon Gong Woon-Hong Yeo seungyong han Seung Hwan Ko Department of Mechanical Engineering Seoul National University IEN Center for Human-Centric Interfaces and Engineering Institute for Electronics and NanotechnologyGeorgia Institute of Technology School of Electrical and Computer Engineering Georgia Institute of Technology Department of Chemical Engineering Stanford University Department of Mechanical Engineering Ajou University George W.Woodruff School of Mechanical Engineering Georgia Institute of Technology Institute of Advanced Machinery and Design(SNU-IAMD) Seoul National University

Soft electromechanical sensors have led to a new paradigm of electronic devices for novel motion-based wearable applications in our daily lives. However, the vast amount of random and unidentified signals generated by complex body motions has hindered the precise recognition and practical application of this technology. Recent advancements in artificial-intelligence technology have enabled significant strides in extracting features from massive and intricate data sets, thereby presenting a breakthrough in utilizing wearable sensors for practical applications. Beyond traditional machine-learning techniques for classifying simple gestures, advanced machine-learning algorithms have been developed to handle more complex and nuanced motion-based tasks with restricted training data sets. Machine-learning techniques have improved the ability to perceive, and thus machine-learned wearable soft sensors have enabled accurate and rapid human-gesture recognition, providing real-time feedback to users. This forms a crucial component of future wearable electronics, contributing to a robust human–machine interface. In this review, we provide a comprehensive summary covering materials, structures and machine-learning algorithms for hand-gesture recognition and possible practical applications through machine-learned wearable electromechanical sensors.

关键词： wearable sensor soft electronics artificial intelligence machine learning human–machine interfaces gesture recognition

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M1-polarized macrophage-derived cellular nanovesicle-coated lipid nanoparticles for enhanced cancer treatment through hybridization of gene therapy and cancer immunotherapy

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Acta Pharmaceutica Sinica B 2024年第7期14卷 3169-3183页

作者： Ha Eun Shin Jun-Hyeok han seungyong Shin Ga-Hyun Bae Boram Son Tae-Hyung Kim Hee Ho Park Chun Gwon Park Wooram Park Department of Integrative Biotechnology Sungkyunkwan University(SKKU)SuwonGyeonggi 16419Republic of Korea Deparment of Inteligent Precision Healthcare Convergence SKKUSuwonGyeonggi 16419Republic of Korea Department of MetaBioHealth SKKU Institute for ConvergenceSKKUSuwonGyeonggi 16419Republic of Korea Department of Bioengineering Hanyang UniversitySeoul 04763Republic of Korea Department of Integrative Engineering Chung-Ang UniversitySeoul 06974Republic of Korea Department of Biomedical Engineering SKKUSuwonGyeonggi 16419Republic of Korea Korea Institute of Science and Technology(KIST) Seoul 02792Republic of Korea

Optimum genetic delivery for modulating target genes to diseased tissue is a major obstacle for profitable gene *** nanoparticles(LNPs),considered a prospective vehicle for nucleic acid delivery,have demonstrated efficacy in human use during the COVID-19 *** study introduces a novel biomaterial-based platform,M1-polarized macrophage-derived cellular nanovesicle-coated LNPs(M1-C-LNPs),specifically engineered for a combined gene-immunotherapy approach against solid *** dual-function system of M1-C-LNPs encapsulates Bcl2-targeting siRNA within LNPs and immune-modulating cytokines within M1 macrophage-derived cellular nanovesicles(M1-NVs),effectively facilitating apoptosis in cancer cells without impacting T and NK cells,which activate the intratumoral immune response to promote granule-mediating killing for solid tumor *** retention within tumor was observed upon intratumoral administration of M1-C-LNPs,owing to the presence of adhesion molecules on M1-NVs,thereby contributing to superior tumor growth *** findings represent a promising strategy for the development of targeted and effective nanoparticle-based cancer genetic-immunotherapy,with significant implications for advancing biomaterial use in cancer therapeutics.

关键词： Genetic-immunotherapy M1 macrophage-derived cellular nanovesicles Lipid nanoparticles(LNPs) Gene therapy siRNA Cancer immunotherapy Solid tumor Tumor microenvironment(TME)

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Ultra-stable and tough bioinspired crack-based tactile sensor for small legged robots

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npj Flexible Electronics 2023年第1期7卷 339-350页

作者： Taewi Kim Insic Hong Minho Kim Sunghoon Im Yeonwook Roh Changhwan Kim Jongcheon Lim Dongjin Kim Jieun Park Seunggon Lee Daseul Lim Junggwang Cho Seokhaeng Huh Seung-Un Jo ChangHwan Kim Je-Sung Koh seungyong han Daeshik Kang Multiscale Bio-inspired Technology Lab Department of Mechanical EngineeringAjou University206 World cup-roYeongtong-guSuwon-siGyeonggi-do 16499South Korea Weldon School of Biomedical Engineering Purdue UniversityWest LafayetteINUSA LIG Nex1 333Pangyo-roBundang-guSeongnam-siGyeonggi-do 13488Republic of Korea Defense Industry Technology Center Agency for Defense Development61Yeouidaebang-roDongjak-guSeoulRepublic of Korea

For legged robots,collecting tactile information is essential for stable posture and efficient ***,mounting sensors on small robots weighing less than 1 kg remain challenges in terms of the sensor’s durability,flexibility,sensitivity,and *** sensors featuring ultra-sensitivity,small-size,and flexibility could be a promising candidate,but performance degradation due to crack growing by repeated use is a stumbling *** paper presents an ultra-stable and tough bio-inspired crack-based sensor by controlling the crack depth using silver nanowire(Ag NW)mesh as a crack stop *** Ag NW mesh inspired by skin collagen structure effectively mitigated crack *** sensor was very thin,lightweight,sensitive,and ultra-durable that maintains its sensitivity during 200,000 cycles of 0.5%*** demonstrate sensor’s feasibility by implementing the tactile sensation to bio-inspired robots,and propose statistical and deep learning-based analysis methods which successfully distinguished terrain type.

关键词： crack tough durability

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Spider-inspired tunable mechanosensor for biomedical applications

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npj Flexible Electronics 2023年第1期7卷 444-452页

作者： Taewi Kim Insic Hong Yeonwook Roh Dongjin Kim Sungwook Kim Sunghoon Im Changhwan Kim Kiwon Jang Seongyeon Kim Minho Kim Jieun Park Dohyeon Gong Kihyeon Ahn Jingoo Lee Gunhee Lee Hak-Seung Lee Jeehoon Kang Ji Man Hong Seungchul Lee Sungchul Seo Bon-Kwon Koo Je-sung Koh seungyong han Daeshik Kang Department of Mechanical Engineering Ajou UniversitySuwonKorea Department of Mechanical Engineering Pohang University of Science and TechnologyPohangKorea Department of Sustainable Environment Research Korea Institute of Machinery&MaterialsDaejeonKorea Department of Internal Medicine and Cardiovascular Center Seoul National University HospitalSeoulKorea Department of Neurology and Neurosurgery Ajou University School of MedicineSuwonKorea Department of Nano-chemical Biological and Environmental EngineeringSeokyeong UniversitySeoulKorea Institute on Aging Seoul National UniversitySeoulKorea

The recent advances of wearable sensors are remarkable but there are still limitations that they need to be refabricated to tune the sensor for target ***,biological sensory systems have the inherent potential to adjust their sensitivity according to the external environment,allowing for a broad and enhanced ***,we developed a Tunable,Ultrasensitive,Nature-inspired,Epidermal Sensor(TUNES)that the strain sensitivity was dramatically increased(GF~30k)and the pressure sensitivity could be tuned(10–254 kPa^(−1))by preset membrane *** sensor adjusts the sensitivity to the pressure regime by preset tension,so it can measure a wide range(0.05 Pa–25 kPa)with the best performance:from very small signals such as minute pulse to relatively large signals such as muscle contraction and *** verified its capabilities as a wearable health monitoring system by clinical trial comparing with pressure wire which is considered the current gold standard of blood pressure(r=0.96)and home health care system by binary classification of Old’s/Young’s pulse waves via machine learning(accuracy 95%).

关键词： Sensor adjust Spider

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Epidermal piezoresistive structure with deep learning-assisted data translation

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npj Flexible Electronics 2022年第1期6卷 672-680页

作者： Changrok So Jong Uk Kim Haiwen Luan Sang Uk Park Hyochan Kim seungyong han Doyoung Kim Changhwan Shin Tae-il Kim Wi Hyoung Lee Yoonseok Park Keun Heo Hyoung Won Baac Jong Hwan Ko Sang Min Won Department of Electrical and Computer Engineering Sungkyunkwan University(SKKU)Suwon 16419Republic of Korea School of Chemical Engineering Sungkyunkwan University(SKKU)Suwon 16419Republic of Korea Querrey Simpson Institute for Bioelectronics Northwestern UniversityEvanstonIL 60208USA Department of Mechanical Engineering Ajou UniversitySuwon 16499Republic of Korea School of Electrical Engineering Korea UniversitySeoul 02841Republic of Korea Biomedical Institute for Convergence(BICS) Sungkyunkwan University(SKKU)Suwon 16419Korea Department of Organic and Nano System Engineering Konkuk UniversitySeoul 05029Republic of Korea Department of Advanced Materials Engineering for Information and Electronics Kyung Hee UniversityYongin 17104Republic of Korea School of Semiconductor and Chemical Engineering Jeonbuk National UniversityJeonju 54896Republic of Korea

Continued research on the epidermal electronic sensor aims to develop sophisticated platforms that reproduce key multimodal responses in human skin,with the ability to sense various external stimuli,such as pressure,shear,torsion,and *** development of such applications utilizes algorithmic interpretations to analyze the complex stimulus shape,magnitude,and various moduli of the epidermis,requiring multiple complex equations for the attached *** this experiment,we integrate silicon piezoresistors with a customized deep learning data process to facilitate in the precise evaluation and assessment of various stimuli without the need for such *** the ability to surpass conventional vanilla deep regression models,the customized regression and classification model is capable of predicting the magnitude of the external force,epidermal hardness and object shape with an average mean absolute percentage error and accuracy of<15 and 96.9%,*** technical ability of the deep learning-aided sensor and the consequent accurate data process provide important foundations for the future sensory electronic system.

关键词： utilize attached precise

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ZnS Nano-Spheres Formed by the Aggregation of Small Crys- tallites and Their Photocatalytic Degradation of Eosin B

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Chinese Journal of Chemistry 2017年第2期35卷 159-164页

作者： Sovann Khan Joon Soo han seungyong Lee So-Hye Cho Materials Architecturing Research Center Korea Institute of Science and Technology 02792 Republic of Korea Department of Nanomaterial Science and Engineering Korea University of Science and Technology Daejeon 34113 Republic of Korea

Monodispersed ZnS nano-spheres were synthesized by a simple precipitation. By adjusting the concentration of Zn and S sources, the particle size and morphology were easily controlled. Careful examination of the obtained par- ticles suggested porous structures composed of building blocks of small crystallites, ca. 4-- 13.4 nm in diameter. A higher [S]/[Zn]-precursor ratio resulted in a bigger crystallite size but a smaller particle size, and vice versa, for the lower precursor ratio. However, an extreme [S]/[Zn] ratio of 20 provided no spherical aggregation, but a formation of amorphous aggregates. We consider the rate to nucleation and the diffusion-controlled aggregation of crystallites to be important parameters in determining particle sizes and size distributions. Size homogeneity of the obtained ZnS nano-spheres, especially with a [S]/[Zn]-precursor ratio of 5, afforded a photonic crystal array that can poten- tially benefit the photocatalytic activity. When the photocatalytic activities of the ZnS nano-spheres obtained via different conditions were compared, it was found that spherical aggregation and high surface areas have a positive effect on catalytic activity. Although using a [S]/[Zn] ratio of 20 provided the highest surface area, the amorphous aggregation and overly excessive use of S caused a detrimental influence on the catalytic activity.

关键词： ZnS nano-spheres photocatalysis aggregation eosin B

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