Contactless metabolism estimation of small animals using high-frequency millimeter-wave radar. Ono H et al.

Animals flexibly adapt to internal and external environmental changes by utilizing energy produced from oxygen as fuel. By non-invasively monitoring an animal's oxygen consumption, it becomes possible to understand an individual's metabolic state. Calorimeters are known for directly measuring oxygen consumption but come with the issue of high initial costs. Despite the development of non-invasive techniques for measuring vital signs—including respiration rate (RR), heart rate (HR), and body temperature (Tb)—as indicators of metabolism, conventional methods encounter difficulties in estimating oxygen consumption rate (VO2). In this study, we developed a system that estimates the oxygen consumption of small animals using signals obtained from millimeter wave (mm-wave) radar technology processed through machine learning. By identifying frequency bands within the mm-wave signals contributing to VO2, our system is capable of predicting oxygen consumption several minutes in advance. Our system enables contactless, low-cost and multiplexed measurements of oxygen consumption, presenting a significant advancement in the field.

Figure 1 | Experimental setup for metabolic measurement using mm-wave radar technology.
Figure 2 | Metabolism estimation using machine learning-based mm-wave radar technology.
Figure 3 | Visualization of informative features in MMM.
Figure 4 | Performance evaluation of future metabolic state estimation.

Raw data and codes in the following study.