Omar Reyad^1,2, Hazem Ibrahim Shehata^1,3, Mohamed Esmail Karar^1,4,*

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1689-1700, 2023, DOI:10.32604/cmc.2023.039084 - 30 August 2023

Abstract Falling is among the most harmful events older adults may encounter. With the continuous growth of the aging population in many societies, developing effective fall detection mechanisms empowered by machine learning technologies and easily integrable with existing healthcare systems becomes essential. This paper presents a new healthcare Internet of Health Things (IoHT) architecture built around an ensemble machine learning-based fall detection system (FDS) for older people. Compared to deep neural networks, the ensemble multi-stage random forest model allows the extraction of an optimal subset of fall detection features with minimal hyperparameters. The number of cascaded… More >

Mohamed Esmail Karar^1,2,*, Omar Reyad^1,3, Hazem Ibrahim Shehata^1,4

Computer Systems Science and Engineering, Vol.45, No.3, pp. 2377-2389, 2023, DOI:10.32604/csse.2023.032931 - 21 December 2022

Abstract This article introduces a new medical internet of things (IoT) framework for intelligent fall detection system of senior people based on our proposed deep forest model. The cascade multi-layer structure of deep forest classifier allows to generate new features at each level with minimal hyperparameters compared to deep neural networks. Moreover, the optimal number of the deep forest layers is automatically estimated based on the early stopping criteria of validation accuracy value at each generated layer. The suggested forest classifier was successfully tested and evaluated using a public SmartFall dataset, which is acquired from three-axis… More >

Frédéric Bloch¹, Bénédicte Charmeteau², Michael Tovey³, Jean-Franc¸ois Meritet⁴, Corinne Desaint^5,6, Odile Launay^4,5,6, Pierre Lebon⁴

European Cytokine Network, Vol.27, No.3, pp. 63-67, 2016, DOI:10.1684/ecn.2016.0378

Abstract Objective: To investigate the relationship between the response to influenza vaccination and the ability to produce proinflamatory cytokines in elderly subjects. Methods: Whole blood samples from 25 elderly subjects collected before influenza vaccination were stimulated with the influenza vaccine in order to evaluate the secretion of five specific cytokines: TNFα, IFNα, IFNγ, IL2 and IL10. The results were correlated with the increased HAI antibody titres two weeks after vaccination.Results:Only 30% of elderly individuals seroconverted after vaccination. Although 50 to 70% of the cohort did not produce TNFα, IFNα, IFNγ, IL2 or IL10, all of the More >