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Plasma oligomeric beta-amyloid is associated with cerebral beta-amyloid deposition in cognitively normal older adults 认知正常老年人血浆低聚β淀粉样蛋白与大脑β淀粉样沉积相关
Q3 Nursing Pub Date : 2022-10-23 DOI: 10.4017/gt.2022.21.s.822.3.sp3
S. Wang, D. Kang, Y. Um, Nak-Young Kim, H. Lim
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引用次数: 0
Analysis of social value for nursing robots with the estimates of demand functions 基于需求函数估计的护理机器人社会价值分析
Q3 Nursing Pub Date : 2022-10-23 DOI: 10.4017/gt.2022.21.s.527.3.sp3
K. Park, H. Ryu, J. Kim, J. Lee, Y. Lee
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引用次数: 0
IoT based health monitoring system - Recent trends and directions 基于物联网的健康监测系统-最新趋势和方向
Q3 Nursing Pub Date : 2022-10-23 DOI: 10.4017/gt.2022.21.s.524.pp1
C. M. B. Ho, Jirka Hana, S. Park
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引用次数: 0
Evaluation method using muscle activation of resistance exercise with wearable robot 基于肌肉激活的可穿戴机器人阻力运动评价方法
Q3 Nursing Pub Date : 2022-10-23 DOI: 10.4017/gt.2022.21.s.793.5.sp2
B. Kang, C. Lee, S. Joo, J. Y. Kim, D. E. Kim, G. Kim, Y. M. Lim
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引用次数: 0
The effect of smart health care systems as remote monitoring on health-related quality of life in the elderly with chronic diseases 智能医疗保健系统作为远程监测对患有慢性病的老年人健康相关生活质量的影响
Q3 Nursing Pub Date : 2022-10-23 DOI: 10.4017/gt.2022.21.s.686.opp3
C. H. Oak, H. K. Choi, K. Y. Lee
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引用次数: 0
Biomechanical benefits of a mobile lift in reducing mechanical loads at the lower back during transfers 移动式举重在减少转移过程中下背部的机械负荷方面的生物力学优势
Q3 Nursing Pub Date : 2022-10-23 DOI: 10.4017/gt.2022.21.s.554.opp3
S. Lee, K. Lim, W. J. Choi
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引用次数: 0
An interactive guideline to mitigate the risks associated with getting lost among persons living with dementia 一份互动指南,以减轻痴呆症患者与迷路相关的风险
Q3 Nursing Pub Date : 2022-10-23 DOI: 10.4017/gt.2022.21.s.508.pp3
N. Neubauer, L. McLennan, E. Leung, C. Daum, L. Zhang-Kennedy, L. Liu
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引用次数: 0
A technology innovation to improve hypertension medication adherence for older adults 一项提高老年人高血压药物依从性的技术创新
Q3 Nursing Pub Date : 2022-10-23 DOI: 10.4017/gt.2022.21.s.593.3.sp3
J. K. Lee, K. Insel, J. Nicholas, R. F. L. Azevedo, W. Rogers
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引用次数: 0
Residents’ perception of the use of smart-home technologies in a retirement community 居民对退休社区使用智能家居技术的看法
Q3 Nursing Pub Date : 2022-10-23 DOI: 10.4017/gt.2022.21.s.769.opp1
A. Aguilera-Hermida
Purpose In the past, older adults had ambivalent attitudes regarding the use of technology (Pirzada et al., 2022). However, the pandemic has been a catalyst for the use of technology. The COVID-19 pandemic has forced individuals to change habits and increase their trust in technology (Umair et al., 2022). This is an opportunity for older adults in general, specifically long-term care communities can take advantage of this and adapt their living spaces with assistive technologies. Smart home technology includes automation, social connectivity, activity, and health monitoring, among others. The use of smart home technology will benefit not only older adults' quality of life but also may reduce costs and improve the quality of care within long-term facilities (Borelli et al., 2019). Therefore, this qualitative study explored the perception of residents living in a retirement community regarding the use of a portal that integrated smart-home technology. Method Qualitative data were collected through semi-structured interviews with nine residents. The interviewer asked about demographics, use of devices, and the internet. Also, residents expressed their experiences living in smart-cottages that had a responsive platform (portal). The portal allowed older adults to control domestic devices and appliances, and communicate with the retirement community using a tablet. The interviews were transcribed, coded, and organized in themes using NVivo software. Results and Discussion The findings are presented in Table 1. Residents indicated that the portal was a protected and supportive tool. Older adults felt a strong sense of being cared for because if something went wrong with home services (such as the furnace, air conditioner, or lights), maintenance was notified automatically through the portal. Also, the motion sensors notified the nursing staff if residents fell or if they stayed in bed too long. A resident said, "They keep track. To make sure we are alive”. Residents enjoyed scheduling services directly in the portal without contacting staff. Older adults chose what services they wanted to use. Some of them used the portal for communication with family members, but not with other residents because they preferred face-to-face communication. Residents associated the portal with safety, care, and support from the facility. The use of smart home technologies in retirement communities is perceived as a high-quality service by the residents. It increases technology literacy and improves residents' quality of life. Furthermore, the use of technology can save energy and reduce costs to the retirement community, increase customer satisfaction, and it can be a potential solution to the shortage of professionals in the aging field. Finally, the use of smart-home technologies can help residents to age in their cottages (aging in place) without moving to sections of the community that require a higher level of care such as assisted living or nursing homes. © 2022, G
过去,老年人对技术的使用持矛盾的态度(Pirzada et al., 2022)。然而,大流行已成为使用技术的催化剂。COVID-19大流行迫使个人改变习惯,增加对技术的信任(Umair等人,2022年)。一般来说,这对老年人来说是一个机会,特别是长期护理社区可以利用这一点,用辅助技术调整他们的生活空间。智能家居技术包括自动化、社交连接、活动和健康监测等。智能家居技术的使用不仅有利于老年人的生活质量,还可以降低成本,提高长期设施内的护理质量(Borelli et al., 2019)。因此,本定性研究探讨了居住在退休社区的居民对使用集成智能家居技术的门户网站的看法。方法采用半结构化访谈法对9名居民进行定性调查。采访者询问了人口统计、设备使用和互联网的情况。此外,居民们还表达了他们在拥有响应平台(门户)的智能别墅中的生活体验。该门户网站允许老年人控制家用设备和电器,并使用平板电脑与退休社区沟通。使用NVivo软件对访谈进行转录、编码和主题组织。研究结果见表1。居民表示,入口是一个受保护和支持的工具。老年人有一种被照顾的强烈感觉,因为如果家庭服务(如炉子、空调或灯)出现问题,维修人员会通过门户自动通知。此外,如果居民摔倒或躺在床上的时间过长,运动传感器会通知护理人员。一位居民说:“他们会记录。确保我们还活着。”居民可以直接在门户网站上安排服务,而无需联系工作人员。老年人选择他们想要使用的服务。他们中的一些人使用门户网站与家人交流,但不与其他居民交流,因为他们更喜欢面对面的交流。居民将门户与安全、护理和设施支持联系在一起。在退休社区中使用智能家居技术被居民视为一种高质量的服务。它提高了技术素养,提高了居民的生活质量。此外,技术的使用可以为退休社区节省能源和降低成本,提高客户满意度,并且可以成为解决老龄化领域专业人员短缺的潜在解决方案。最后,智能家居技术的使用可以帮助居民在自己的小屋里养老(原地养老),而无需搬到需要更高水平护理的社区,如辅助生活或养老院。©2022,Gerontechnology。版权所有。
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引用次数: 0
Improving the assessment of older adults using feature selection and machine learning models 使用特征选择和机器学习模型改进对老年人的评估
Q3 Nursing Pub Date : 2022-10-23 DOI: 10.4017/gt.2022.21.s.544.opp4
J. Rojo, J. García-Alonso, J. M. Murillo, S. Helal
Purpose The growing capacity of healthcare systems to digitize patient information is enabling the creation of large repositories of patient health data, facilitating the use of Artificial Intelligence techniques, especifically Machine Learning, to analyze this data for insights and discovery. Thanks to this, unprecedented predictions and accurate diagnosis of certain diseases are possible to achieve today. However, this increasing morass of information is a double-edged sword as it makes it difficult for health professionals to navigate and determine which information is most crucial to examine for a given pathology or health condition. Feature Selection techniques have been applied for years to help Machine Learning prediction models to determine which information is most relevant to diagnoses, as demonstrated in Remeseiro et al. (2019). Consequently, these techniques help reduce the amount of information that health professionals need to collect, reducing laborious work while making them aware of which factors are more important for the assessment in contrast with what they initially considered to be important or relevant
目的医疗保健系统数字化患者信息的能力不断增强,有助于创建大型患者健康数据存储库,促进使用人工智能技术,特别是机器学习,分析这些数据以获得见解和发现。正因为如此,今天才有可能实现对某些疾病前所未有的预测和准确诊断。然而,这种信息的不断增加是一把双刃剑,因为它使卫生专业人员很难导航和确定哪些信息对特定的病理学或健康状况最重要。多年来,特征选择技术一直被应用于帮助机器学习预测模型确定哪些信息与诊断最相关,如Remeseiro等人所述。(2019)。因此,这些技术有助于减少卫生专业人员需要收集的信息量,减少繁重的工作,同时让他们意识到与最初认为重要或相关的因素相比,哪些因素对评估更重要
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引用次数: 0
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Gerontechnology
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