Dataset Information

Quantified assessment of hyperactivity in ADHD youth using IR-UWB radar.

ABSTRACT: Research on the quantification of hyperactivity in youth with attention-deficit/hyperactivity disorder (ADHD) has been limited and inconsistent. The purpose of this study was to test the discriminative value of impulse-radio ultra-wideband (IR-UWB) radar for monitoring hyperactive individuals with ADHD and healthy controls (HCs). A total of 10 ADHD patients and 15 HCs underwent hyperactivity assessment using IR-UWB radar during a 22-min continuous performance test. We applied functional ANOVA to compare the mean functions of activity level between the 2 groups. We found that the mean function of activity over time was significantly different and that the activity level of the ADHD group slightly increased over time with high dispersion after approximately 7 min, which means that the difference in activity level between the two groups became evident at this period. Further studies with larger sample sizes and longer test times are warranted to investigate the effect of age, sex, and ADHD subtype on activity level function.

SUBMITTER: Lee WH

PROVIDER: S-EPMC8100299 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Quantified assessment of hyperactivity in ADHD youth using IR-UWB radar.

Lee Won Hyuk WH Kim Johanna Inhyang JI Kwon Amy M AM Cha Jong Ho JH Yim Daehyeon D Lim Young-Hyo YH Cho Seok-Hyun SH Cho Sung Ho SH Park Hyun-Kyung HK

Scientific reports 20210505 1

Research on the quantification of hyperactivity in youth with attention-deficit/hyperactivity disorder (ADHD) has been limited and inconsistent. The purpose of this study was to test the discriminative value of impulse-radio ultra-wideband (IR-UWB) radar for monitoring hyperactive individuals with ADHD and healthy controls (HCs). A total of 10 ADHD patients and 15 HCs underwent hyperactivity assessment using IR-UWB radar during a 22-min continuous performance test. We applied functional ANOVA to ...[more]

PMID: 33953298

Similar Datasets

Project description:As the size of the radar hardware platform becomes smaller and smaller, the cost becomes lower and lower. The application of indoor radar-based human motion recognition has become a reality, which can be realized in a low-cost device with simple architecture. Compared with narrow-band radar (such as continuous wave radar, etc.), the human motion echo signal of the carrier-free ultra-wideband (UWB) radar contains more abundant characteristic information of human motion, which is helpful for identifying different types of human motion. In this paper, a novel feature extraction method by two-dimensional variational mode decomposition (2D-VMD) algorithm is proposed. And it is used for extracting the primary features of human motion. The 2D-VMD algorithm is an adaptive non-recursive multiscale decomposition method for nonlinear and nonstationary signals. Firstly, the original 2D radar echo signals are decomposed by the 2D-VMD algorithm to capture several 2D intrinsic mode function (BIMFs) which represent different groups of central frequency components of a certain type of human motion. Secondly, original echo signals are reconstructed according to the several BIMFs, which not only have a certain inhibitory effect on the clutter in the echo signal, but can also further demonstrate that the BIMFs obtained by the 2D-VMD algorithm can represent the original 2D echo signal well. Finally, based on the measured ten different types of UWB radar human motion 2D echo analysis signals, the characteristics of these different types of human motion are extracted and the original echo signal are reconstructed. Then, the three indicators of the PCC, UQI, and PSNR between the original echo signals and extraction/reconstruction 2D signals are analyzed, which illustrate the effectiveness of 2D-VMD algorithm to extract feature of human motion 2D echo signals of the carrier-free UWB radar. Experimental results show that BIMFs by 2D-VMD algorithm can well represent the echo signal characteristics of this type of human motion, which is a very effective tool for human motion radar echo signal feature extraction.

Dataset Information

Quantified assessment of hyperactivity in ADHD youth using IR-UWB radar.

Publications

Quantified assessment of hyperactivity in ADHD youth using IR-UWB radar.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets