Hand gesture recognition (HGR) is used in a numerous applications,including medical health-care, industrial purpose and sports detection.We have developed a real-time hand gesture recognition system using inertialsens...Hand gesture recognition (HGR) is used in a numerous applications,including medical health-care, industrial purpose and sports detection.We have developed a real-time hand gesture recognition system using inertialsensors for the smart home application. Developing such a model facilitatesthe medical health field (elders or disabled ones). Home automation has alsobeen proven to be a tremendous benefit for the elderly and disabled. Residentsare admitted to smart homes for comfort, luxury, improved quality of life,and protection against intrusion and burglars. This paper proposes a novelsystem that uses principal component analysis, linear discrimination analysisfeature extraction, and random forest as a classifier to improveHGRaccuracy.We have achieved an accuracy of 94% over the publicly benchmarked HGRdataset. The proposed system can be used to detect hand gestures in thehealthcare industry as well as in the industrial and educational sectors.展开更多
There is a rapidly growing demand to use silicon and silicon nitride（Si3N4） integrated photonics for sensing applications, ranging from refractive index to spectroscopic sensing. By making use of advanced CMOS techn...There is a rapidly growing demand to use silicon and silicon nitride（Si3N4） integrated photonics for sensing applications, ranging from refractive index to spectroscopic sensing. By making use of advanced CMOS technology,complex miniaturized circuits can be easily realized on a large scale and at a low cost covering visible to mid-IR wavelengths. In this paper we present our recent work on the development of silicon and Si3N4-based photonic integrated circuits for various spectroscopic sensing applications. We report our findings on waveguide-based absorption, and Raman and surface enhanced Raman spectroscopy. Finally we report on-chip spectrometers and on-chip broadband light sources covering very near-IR to mid-IR wavelengths to realize fully integrated spectroscopic systems on a chip.展开更多
基金supported by a grant (2021R1F1A1063634)of the Basic Science Research Program through the National Research Foundation (NRF)funded by the Ministry of Education,Republic of Korea.
文摘Hand gesture recognition (HGR) is used in a numerous applications,including medical health-care, industrial purpose and sports detection.We have developed a real-time hand gesture recognition system using inertialsensors for the smart home application. Developing such a model facilitatesthe medical health field (elders or disabled ones). Home automation has alsobeen proven to be a tremendous benefit for the elderly and disabled. Residentsare admitted to smart homes for comfort, luxury, improved quality of life,and protection against intrusion and burglars. This paper proposes a novelsystem that uses principal component analysis, linear discrimination analysisfeature extraction, and random forest as a classifier to improveHGRaccuracy.We have achieved an accuracy of 94% over the publicly benchmarked HGRdataset. The proposed system can be used to detect hand gestures in thehealthcare industry as well as in the industrial and educational sectors.
基金ERC-In Spectra Advanced Grant, ERC-MIRACLE, ERC-ULPPIC and Methusalem (Smart Photonics Chips) for their supportfunding agencies IWT and FWO that helped in carrying out various parts of the work presented in the paper
文摘There is a rapidly growing demand to use silicon and silicon nitride（Si3N4） integrated photonics for sensing applications, ranging from refractive index to spectroscopic sensing. By making use of advanced CMOS technology,complex miniaturized circuits can be easily realized on a large scale and at a low cost covering visible to mid-IR wavelengths. In this paper we present our recent work on the development of silicon and Si3N4-based photonic integrated circuits for various spectroscopic sensing applications. We report our findings on waveguide-based absorption, and Raman and surface enhanced Raman spectroscopy. Finally we report on-chip spectrometers and on-chip broadband light sources covering very near-IR to mid-IR wavelengths to realize fully integrated spectroscopic systems on a chip.
