Preclinical Trial of Noncontact Anthropometric Measurement Using IR-UWB Radar

Abstract

Anthropometric profiles are important indices for the assessment of medical conditions, including malnutrition, obesity, andgrowth disorders. Noncontact methods for estimating those parameters could have considerable value in many practicalsituations, such as the assessment of young, uncooperative infants or children and the prevention of infectious diseasetransmission. The purpose of this study is to investigate the feasibility of obtaining noncontact anthropometric measurementsusing the impulse-radio ultrawideband (IR-UWB) radar sensor technique. A total of 45 healthy adults were enrolled, and aconvolutional neural network (CNN) algorithm was implemented to analyze data extracted from IR-UWB radar. The differences(root-mean-square error, RMSE) between values from the radar and bioelectrical impedance analysis (BIA) as a reference inthe measurement of height, weight, and body mass index (BMI) were 2.78, 5.31, and 2.25, respectively; predicted data fromthe radar highly agreed with those from the BIA. The intraclass correlation coefficients (ICCs) were 0.93, 0.94, and 0.83.In conclusion, IR-UWB radar can provide accurate estimates of anthropometric parameters in a noncontact manner; this studyis thus the first supporting the radar sensor as an applicable method in clinical situations.