Mely Ruiz-Aquino¹, Viter Gerson Carlos Trinidad^1,2, Aldo Alvarez-Risco³, Jaime A. Yáñez^4,5,*

International Journal of Mental Health Promotion, Vol.24, No.6, pp. 959-974, 2022, DOI:10.32604/ijmhp.2022.021172

Abstract The general objective of this article was to construct and describe the psychometric properties of a scale of selfcare behaviors against COVID-19. It was a descriptive, cross-sectional, psychometric validation study of a scale created to measure self-care behaviors in relation to COVID-19 in a total sample of 333 probabilistically selected. Qualitative validity was evaluated by a review of 10 experts and quantitative validity by means of exploratory factor analysis using the principal components method. Internal consistency was measured with Cronbach’s alpha twice and the test-retest was evaluated by calculating the intraclass coefficient. The final scale consisted of 29 items. The… More >

Mouazma Batool¹, Yazeed Yasin Ghadi², Suliman A. Alsuhibany³, Tamara al Shloul⁴, Ahmad Jalal¹, Jeongmin Park^5,*

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1747-1764, 2022, DOI:10.32604/cmc.2022.025112

Abstract Nowadays, activities of daily living (ADL) recognition system has been considered an important field of computer vision. Wearable and optical sensors are widely used to assess the daily living activities in healthy people and people with certain disorders. Although conventional ADL utilizes RGB optical sensors but an RGB-D camera with features of identifying depth (distance information) and visual cues has greatly enhanced the performance of activity recognition. In this paper, an RGB-D-based ADL recognition system has been presented. Initially, human silhouette has been extracted from the noisy background of RGB and depth images to track human movement in a scene.… More >