Lee Hak-Hoon, Shin Hyun-Chool
Department of Intelligent Semiconductors, Soongsil University, Seoul 06978, Republic of Korea.
Entropy (Basel). 2025 Jul 3;27(7):720. doi: 10.3390/e27070720.
Existing activity measurement methods, such as gas analyzers, activity trackers, and camera-based systems, have limitations in accuracy, convenience, and privacy. To address these issues, this study proposes an improved activity estimation algorithm using a 60 GHz Frequency-Modulated Continuous-Wave (FMCW) radar. Unlike conventional methods that rely solely on distance variations, the proposed method incorporates both distance and velocity information, enhancing measurement accuracy. The algorithm quantifies activity levels using Shannon entropy to reflect the spatial-temporal variation in range signatures. The proposed method was validated through experiments comparing estimated activity levels with motion sensor-based ground truth data. The results demonstrate that the proposed approach significantly improves accuracy, achieving a lower Root Mean Square Error (RMSE) and higher correlation with ground truth values than conventional methods. This study highlights the potential of FMCW radar for non-contact, unrestricted activity monitoring and suggests future research directions using multi-channel radar systems for enhanced motion analysis.
现有的活动测量方法，如气体分析仪、活动追踪器和基于摄像头的系统，在准确性、便利性和隐私性方面存在局限性。为了解决这些问题，本研究提出了一种使用60GHz调频连续波（FMCW）雷达的改进活动估计算法。与仅依赖距离变化的传统方法不同，该方法结合了距离和速度信息，提高了测量准确性。该算法使用香农熵对活动水平进行量化，以反映距离特征中的时空变化。通过将估计的活动水平与基于运动传感器的地面真值数据进行比较的实验，对所提出的方法进行了验证。结果表明，与传统方法相比，所提出的方法显著提高了准确性，实现了更低的均方根误差（RMSE）和与地面真值更高的相关性。本研究突出了FMCW雷达在非接触、无限制活动监测方面的潜力，并提出了使用多通道雷达系统进行增强运动分析的未来研究方向。
