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  • Open Access

    ARTICLE

    The Relationship between Psychological Vulnerability, Aging Attitudes and Life Meaning in Elderly Patients with Comorbidities

    Jiaojiao Wu1,#, Dou Fu2,#, Lili Zhang1,*, Xiangying Xie3, Xinmei Wang2, Xiangying Shen1, Shanshan Liu2, Xu Xu4, Hui Cheng5, Xiaojie Ma1, Doudou Lin1

    International Journal of Mental Health Promotion, Vol.26, No.11, pp. 897-904, 2024, DOI:10.32604/ijmhp.2024.056223 - 28 November 2024

    Abstract Background: With the rapid aging of China’s population and the increasing prevalence of comorbidities in the elderly, psychological crises have become more common. This study aims to investigate the present status of psychological vulnerability, aging attitudes, and life meaning in elderly patients with comorbidities. Methods: A total of 685 elderly inpatients and outpatients at Renmin Hospital of Wuhan University between July and December 2022 were selected using the simple random sampling method. Social demographic data were collected, and the Attitudes to aging Questionnaire (AAQ), the Chinese Life Meaning Questionnaire (C-MLQ), and the Psychological Vulnerability Scale… More >

  • Open Access

    ARTICLE

    LSTM Based Neural Network Model for Anomaly Event Detection in Care-Independent Smart Homes

    Brij B. Gupta1,2,3,*, Akshat Gaurav4, Razaz Waheeb Attar5, Varsha Arya6,7, Ahmed Alhomoud8, Kwok Tai Chui9

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2689-2706, 2024, DOI:10.32604/cmes.2024.050825 - 08 July 2024

    Abstract This study introduces a long-short-term memory (LSTM)-based neural network model developed for detecting anomaly events in care-independent smart homes, focusing on the critical application of elderly fall detection. It balances the dataset using the Synthetic Minority Over-sampling Technique (SMOTE), effectively neutralizing bias to address the challenge of unbalanced datasets prevalent in time-series classification tasks. The proposed LSTM model is trained on the enriched dataset, capturing the temporal dependencies essential for anomaly recognition. The model demonstrated a significant improvement in anomaly detection, with an accuracy of 84%. The results, detailed in the comprehensive classification and confusion More >

  • Open Access

    REVIEW

    Does young feces make the elderly live better? Application of fecal microbiota transplantation in healthy aging

    YUANYUAN LIAO1,2,3, XINSI LI2,3, QIAN LI2,3, YIZHONG WANG4, XIUJUN TAN1,2,3, TING GONG2,3,5,*

    BIOCELL, Vol.48, No.6, pp. 873-887, 2024, DOI:10.32604/biocell.2024.050324 - 10 June 2024

    Abstract As we are facing an aging society, anti-aging strategies have been pursued to reduce the negative impacts of aging and increase the health span of human beings. Gut microbiota has become a key factor in the anti-aging process. Modulation of gut microbiota by fecal microbiota transplantation (FMT) to prevent frailty and unhealthy aging has been a hot topic of research. This narrative review summarizes the benefits of FMT for health span and lifespan, brains, eyes, productive systems, bones, and others. The mechanisms of FMT in improving healthy aging are discussed. The increased beneficial bacteria and More >

  • Open Access

    ARTICLE

    A Clinical Study on the Effect of Group Nostalgia Therapy on Quality of Life and Cognitive Function in Elderly Patients with Depression

    Yan Huang1,*, Xiaoye Liao2, Fen Cai3

    International Journal of Mental Health Promotion, Vol.25, No.12, pp. 1313-1321, 2023, DOI:10.32604/ijmhp.2023.030558 - 29 December 2023

    Abstract Background: Elderly people with depression require special care and attention. However, nostalgia is a complex emotional situation for a person who recalls the missing past. To improve mental health, quality of life, and attitudes toward aging in institutional care, group nostalgia therapy can be a nursing intermediary for the elderly. This study aimed to analyze the effect of group nostalgia therapy on quality of life cognitive function in elderly patients with depression. Methods: A total of 89 participants were enrolled in this study, which was further categorized into a control (n = 40) and a… More >

  • Open Access

    ARTICLE

    The Effect of Sleep and Cognition Enhancement Multimodal Intervention for Mild Cognitive Impairment with Sleep Disturbance in the Community-Dwelling Elderly

    Eun Kyoung Han, Hae Kyoung Son*

    International Journal of Mental Health Promotion, Vol.25, No.11, pp. 1197-1208, 2023, DOI:10.32604/ijmhp.2023.041560 - 08 December 2023

    Abstract Dementia prevalence has soared due to population aging. In Mild Cognitive Impairment (MCI) as a pre-dementia stage, sleep disturbances have raised much interest as a factor in a bidirectional relationship with cognitive decline. Thus, this study developed the Sleep and Cognition Enhancement Multimodal Intervention (SCEMI) based on Lazarus’ multimodal approach and conducted a randomized controlled experiment to investigate the effects of the novel program on sleep and cognition in MCI elderly. The participants were 55 MCI elderly with sleep disturbances at two dementia care centers located in S-city, Gyeonggi-do, South Korea (n = 25 in… More >

  • Open Access

    ARTICLE

    Developed Fall Detection of Elderly Patients in Internet of Healthcare Things

    Omar Reyad1,2, Hazem Ibrahim Shehata1,3, Mohamed Esmail Karar1,4,*

    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 >

  • Open Access

    ARTICLE

    Reliability of Foot Intrinsic Muscle Strength Testing and Correlation with Corresponding Muscle Morphology in Elderly Adults

    Lulu Yin1,#, Kun Dong1,#, Zhangqi Lai2, Lin Wang1,*

    Molecular & Cellular Biomechanics, Vol.20, No.1, pp. 23-33, 2023, DOI:10.32604/mcb.2023.040788 - 20 June 2023

    Abstract Age-related loss of foot intrinsic muscle (FIM) strength may be associated with disability, falls, and inability to perform daily activities. Previous studies have determined the reliability of FIM strength testing and evaluated the relationship between FIM strength and corresponding muscle morphology in young adults. However, few studies have measured FIM strength in the older. Therefore, this study aimed to assess the intra- and inter-reliability of FIM strength tests and the relationship between FIM strength and FIM size in the older. A total of 61 participants aged 60–75 years were recruited, and 18 of them were… More > Graphic Abstract

    Reliability of Foot Intrinsic Muscle Strength Testing and Correlation with Corresponding Muscle Morphology in Elderly Adults

  • Open Access

    ARTICLE

    IoMT-Based Smart Healthcare of Elderly People Using Deep Extreme Learning Machine

    Muath Jarrah1, Hussam Al Hamadi4,*, Ahmed Abu-Khadrah2, Taher M. Ghazal1,3

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 19-33, 2023, DOI:10.32604/cmc.2023.032775 - 08 June 2023

    Abstract The Internet of Medical Things (IoMT) enables digital devices to gather, infer, and broadcast health data via the cloud platform. The phenomenal growth of the IoMT is fueled by many factors, including the widespread and growing availability of wearables and the ever-decreasing cost of sensor-based technology. There is a growing interest in providing solutions for elderly people living assistance in a world where the population is rising rapidly. The IoMT is a novel reality transforming our daily lives. It can renovate modern healthcare by delivering a more personalized, protective, and collaborative approach to care. However, More >

  • Open Access

    ARTICLE

    Do Child Characteristics Matter to Mitigate the Widowhood Effect on the Elderly’s Mental Health? Evidence from China

    Yuxin Wang*, Haoyue Ma, Lan Zheng

    International Journal of Mental Health Promotion, Vol.25, No.5, pp. 673-686, 2023, DOI:10.32604/ijmhp.2023.026394 - 28 April 2023

    Abstract This study empirically examines whether child characteristics mitigate the negative impact of widowhood on the elderly’s mental health using follow-up survey data from the China Health and Retirement Longitudinal Study (CHARLS). A total of 5,326 older adults aged 60 years and older are selected from three waves of panel data (2013, 2015, and 2018). The findings suggest that respondents who experienced widowhood exhibit an increase in depressive symptoms. However, the higher income of children and frequent face-to-face emotional interactions improve the mental health of the widowed elderly. Moreover, heterogeneity analyses show that the buffering effect… More >

  • Open Access

    ARTICLE

    Deep Forest-Based Fall Detection in Internet of Medical Things Environment

    Mohamed Esmail Karar1,2,*, Omar Reyad1,3, Hazem Ibrahim Shehata1,4

    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 >

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