http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
비접촉형 심박수 측정 정확도 향상을 위한 인공지능 기반 CW 레이더 신호처리
윤원열,권남규,Won Yeol Yoon,Nam Kyu Kwon 대한임베디드공학회 2023 대한임베디드공학회논문지 Vol.18 No.6
Vital signals provide essential information regarding the health status of individuals, thereby contributing to health management and medical research. Present monitoring methods, such as ECGs (Electrocardiograms) and smartwatches, demand proximity and fixed postures, which limit their applicability. To address this, Non-contact vital signal measurement methods, such as CW (Continuous-Wave) radar, have emerged as a solution. However, unwanted signal components and a stepwise processing approach lead to errors and limitations in heart rate detection. To overcome these issues, this study introduces an integrated neural network approach that combines noise removal, demodulation, and dominant-frequency detection into a unified process. The neural network employed for signal processing in this research adopts a MLP (Multi-Layer Perceptron) architecture, which analyzes the in-phase and quadrature signals collected within a specified time window, using two distinct input layers. The training of the neural network utilizes CW radar signals and reference heart rates obtained from the ECG. In the experimental evaluation, networks trained on different datasets were compared, and their performance was assessed based on loss and frequency accuracy. The proposed methodology exhibits substantial potential for achieving precise vital signals through non-contact measurements, effectively mitigating the limitations of existing methodologies.
자율 주행을 위한 영상 기반 차선 인식 및 조향 결정 알고리즘
홍진석(Jin Seok Hong),윤원열(Won Yeol Yoon),권남규(Nam Kyu Kwon) 대한전자공학회 2023 대한전자공학회 학술대회 Vol.2023 No.6
This paper proposes a lane detection-based autonomous driving algorithm using real time image processing suitable for embedded systems. Lanes are detected using image processing method such as edge detection, blob detection, and contour detection. The detected lanes are used to calculate the target steering angle. To verify the validity of the proposed method, we obtain the accuracy of the steering angle decision through four experiments. Experimental results guarantee the feasibility and reliability of the proposed method.