Improved childhood asthma control after exposure reduction interventions for desert dust and anthropogenic air pollution: the MEDEA randomised controlled trial.

INTRODUCTION: Elevated particulate matter (PM) concentrations of anthropogenic and/or desert dust origin are associated with increased morbidity among children with asthma. OBJECTIVE: The Mitigating the Health Effects of Desert Dust Storms Using Exposure-Reduction Approaches randomised controlled trial assessed the impact of exposure reduction recommendations, including indoor air filtration, on childhood asthma control during high desert dust storms (DDS) season in Cyprus and Greece. DESIGN, PARTICIPANTS, INTERVENTIONS AND SETTING: Primary school children with asthma were randomised into three parallel groups: (a) no intervention (controls); (b) outdoor intervention (early alerts notifications, recommendations to stay indoors and limit outdoor physical activity during DDS) and (c) combined intervention (same as (b) combined with indoor air purification with high efficiency particulate air filters in children's homes and school classrooms. Asthma symptom control was assessed using the childhood Asthma Control Test (c-ACT), spirometry (forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC)) and fractional exhaled nitric oxide (FeNO). RESULTS: In total, 182 children with asthma (age; mean=9.5, SD=1.63) were evaluated during 2019 and 2021. After three follow-up months, the combined intervention group demonstrated a significant improvement in c-ACT in comparison to controls (ß=2.63, 95% CI 0.72 to 4.54, p=0.007), which was more profound among atopic children (ß=3.56, 95% CI 0.04 to 7.07, p=0.047). Similarly, FEV1% predicted (ß=4.26, 95% CI 0.54 to 7.99, p=0.025), the need for any asthma medication and unscheduled clinician visits, but not FVC% and FeNO, were significantly improved in the combined intervention compared with controls. CONCLUSION: Recommendations to reduce exposure and use of indoor air filtration in areas with high PM pollution may improve symptom control and lung function in children with asthma. TRIAL REGISTRATION NUMBER: NCT03503812.

Automatic emotion recognition based on body movement analysis: a survey.

Humans are emotional beings, and their feelings influence how they perform and interact with computers. One of the most expressive modalities for humans is body posture and movement, which researchers have recently started exploiting for emotion recognition. This survey describes emerging techniques and modalities related to emotion recognition based on body movement, as well as recent advances in automatic emotion recognition. It also describes application areas and notation systems and explains the importance of movement segmentation. It then discusses unsolved problems and provides promising directions for future research. The Web extra (a PDF file) contains tables with additional information related to the article.