Traditional assessments of children’s health and behavioral issues primarily rely on subjective evaluation by adult raters, which imposes major costs in time and human resource to the school system. This pilot study investigates the utilization of millimeter-wave radar coupled with machine learning for the objective and semi-automatic detection and classification of children’s activity levels, defined as restlessness, within a real classroom environment. Two objectives are pursued: confirming the feasibility of restlessness detection using millimeter-wave radar and proposing an algorithm for restlessness classification through machine learning. The experiment involves a nine-day observational study, using two radar systems to monitor the activities of 14 children in a primary school. Radar data analysis involves the extraction of distinctive features for restlessness detection and classification. Results indicate the successful detection of restlessness using millimeter-wave radar, demonstrating its potential to capture nuanced body movements in a privacy-protected manner. Machine learning models trained on radar data achieve a classification accuracy of 100%, outperforming other methods in terms of non-invasiveness, lack of body restraint, multi-target applications, and privacy protection. The study’s contributions extend to children, parents, and educational practitioners, emphasizing non-invasiveness, privacy protection, and evidence-based support. Despite limitations such as a short monitoring duration and a small sample size, this pilot study lays the foundation for future research in non-invasive restlessness detection using non-contact monitoring technologies. The integration of millimeter-wave radar and machine learning offers a promising avenue for efficient and ethical trait assessments in real-world educational environments, contributing to the advancement of child psychology and education. This work supports efforts for non-contact monitoring of children’s activity holding promise such as non-invasive, privacy protection, multi-targets, objective evaluation, and computer-aided screening.

This study presents a novel approach to monitoring respiration rate using frequency modulated continuous wave (FMCW) mm-wave radar, aiming to overcome the limitations of traditional non-contact method. 14 participants were involved in an experiment involving alternating periods of stillness and left-right continuous body shaking. Data analysis involved non-negative matrix factorization (NMF) and template matching techniques. Respiration measured by radar were compared with ground truth measurements. Results demonstrated accurate respiration detection even during continuous body movement, with significant correlation observed between radar-based and ground truth measurements. This study pioneers radar-based respiration monitoring under continuous body movement conditions, offering promising implications for practical applications.

Hiesho, or cold sensation, predominantly affects females, presenting significant health concerns. Despite its prevalence, screening methods remain controversial, often relying on subjective assessments. Quantitative approaches are urgently needed. This study investigates foot skin temperature recovery rate after cooling test as a novel biomarker for Hiesho. 62 young females participated, undergoing a cooling test followed by foot temperature measurements. Participants completed the Terasawa Hiesho Questionnaire. Biomarker analysis involves receiver operating characteristic (ROC) curve and statistical tests. Thirty-one participants were classified with Hiesho. Significant temperature recovery rate differences were found between Hiesho and no-Hiesho groups, particularly at specific foot points and time intervals. The ROC curve identified optimal biomarkers, with the highest diagnostic performance observed in temperature recovery rate at the medial metatarsal 15 minutes after cooling test. A temperature recovery rate of ≤ 44.68% was suggested as a screening criterion. The study highlights significant temperature recovery rate differences between Hiesho and healthy individuals, supporting its potential as a biomarker. Physiological mechanisms underlying 1 Hiesho, including hormonal influences and genetic factors, were discussed. Foot skin temperature recovery rate post-cooling test shows promise as a biomarker for Hiesho screening in young females. Despite limitations, its potential warrants further investigation, offering a quantitative approach to Hiesho assessment.

A document by Tianyi Wang . Click on the document to view its contents.

design, multi-material printing, 3D printing, additive manufacturing, wearable heating system

Purpose: Build new musician-listener interaction using smart watch for online music. Tools: Smart Watch, Kinect, Touchdesigner This work has been accepted in Frontiers in Computer Science 2023: Wang T and Okada S (2023) Heart fire for online live-streamed concerts: a pilot study of a smartwatch-based musician-listener interaction system. Front. Comput. Sci. 5:1150348. doi: 10.3389/fcomp.2023.1150348