scholarly journals Fall Prevention Support for Elderly Persons at Home Needing Preventive Nursing Care—Effect of Foot Massage on Foot Function—

2021 ◽  
Vol 41 (0) ◽  
pp. 520-526
Author(s):  
Harumi Kohri
Keyword(s):  
Nursing Care ◽  
Fall Prevention ◽  
Elderly Persons ◽  
Foot Function ◽  
At Home

Smart technology-assisted Home Nursing Care Program for Persons with Dementia or Hip Fracture: Implementation Difficulties: Thematic Analysis (Preprint)

2020 ◽  
Author(s):  
Yea-Ing Shyu ◽  
Chung-Chih Lin ◽  
Ching-Tzu Yang ◽  
Pei-Ling Su ◽  
Jung-Ling Hsu
Keyword(s):  
Hip Fracture ◽  
Family Caregivers ◽  
Nursing Care ◽  
Care Program ◽  
Wearable Devices ◽  
Elderly Persons ◽  
Home Nursing ◽  
Smart Technology ◽  
Smart Clothing ◽  
Home Nursing Care

BACKGROUND Wearable devices have been developed and implemented to improve data collection in remote health care and smart care. Wearable devices have the advantage of always being with individuals, enabling easy detection of their movements. In this study, we developed and implemented a smart-care system using smart clothing for persons with dementia and with hip fracture. We conducted a preliminary study to understand family caregivers’ and care receivers’ experiences of receiving a smart technology-assisted (STA) home-nursing care program. OBJECTIVE This paper reports the difficulties we encountered and strategies we developed during the feasibility phase of studies on the effectiveness of our STA home-nursing care program for persons with dementia and hip fracture. METHODS Our care model, a STA home-nursing care program for persons with dementia and those with hip fracture included a remote-monitoring system for elderly persons wearing smart clothing was used to facilitate family caregivers’ detection of elderly persons’ movements. These movements included getting up at night, staying in the bathroom for more than 30 minutes, not moving more than 2 hours during the day, leaving the house, and daily activities. Participants included 13 families with 5 patients with hip fracture and 7 with dementia. Research nurses documented the difficulties they encountered during the process. RESULTS Difficulties encountered in this smart-care study were categorized into problems setting up the smart-care environment, problems running the system, and problems with participant acceptance/adherence. These difficulties caused participants to drop out, the system to not function or delayed function, inability to collect data, extra costs of manpower, and financial burden. Strategies to deal with these problems are also reported. CONCLUSIONS During the implementation of smart care at home for persons with dementia or hip fracture, different aspects of difficulties were found and strategies were taken. The findings of this study can provide a reference for future implementation of similar smart-home devices.

scholarly journals Identifying Fall Risk Predictors by Monitoring Daily Activities at Home Using a Depth Sensor Coupled to Machine Learning Algorithms

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1957
Author(s):  
Amandine Dubois ◽  
Titus Bihl ◽  
Jean-Pierre Bresciani
Keyword(s):  
Machine Learning ◽  
Fall Prevention ◽  
Fall Risk ◽  
Learning Algorithms ◽  
Step Length ◽  
Machine Learning Algorithms ◽  
Daily Activities ◽  
Sitting Time ◽  
Behavioral Parameters ◽  
At Home

Because of population ageing, fall prevention represents a human, economic, and social issue. Currently, fall-risk is assessed infrequently, and usually only after the first fall occurrence. Home monitoring could improve fall prevention. Our aim was to monitor daily activities at home in order to identify the behavioral parameters that best discriminate high fall risk from low fall risk individuals. Microsoft Kinect sensors were placed in the room of 30 patients temporarily residing in a rehabilitation center. The sensors captured the patients’ movements while they were going about their daily activities. Different behavioral parameters, such as speed to sit down, gait speed or total sitting time were extracted and analyzed combining statistical and machine learning algorithms. Our algorithms classified the patients according to their estimated fall risk. The automatic fall risk assessment performed by the algorithms was then benchmarked against fall risk assessments performed by clinicians using the Tinetti test and the Timed Up and Go test. Step length, sit-stand transition and total sitting time were the most discriminant parameters to classify patients according to their fall risk. Coupling step length to the speed required to stand up or the total sitting time gave rise to an error-less classification of the patients, i.e., to the same classification as that of the clinicians. A monitoring system extracting step length and sit-stand transitions at home could complement the clinicians’ assessment toolkit and improve fall prevention.

Gender-Related Differences in Scores of the Barthel Index and Frenchay Activities Index in Randomly Sampled Elderly Persons Living at Home in Japan

1999 ◽  
Vol 52 (11) ◽  
pp. 1089-1094 ◽  
Author(s):  
Kenji Hachisuka ◽  
Satoru Saeki ◽  
Yuka Tsutsui ◽  
Hiromi Chisaka ◽  
Hajime Ogata ◽  
...  
Keyword(s):  
Barthel Index ◽  
Elderly Persons ◽  
At Home

scholarly journals Factors related to the urination methods of elderly people with incontinence who require at-home nursing care

2016 ◽  
Vol 53 (2) ◽  
pp. 133-142
Author(s):  
Kumiko Tanaka ◽  
Keiko Takeda ◽  
Keiko Suyama ◽  
Akiko Kooka ◽  
Satsuki Nakamura
Keyword(s):  
Elderly People ◽  
Nursing Care ◽  
Home Nursing ◽  
Home Nursing Care ◽  
At Home

scholarly journals Nursing care related to fall prevention among hospitalized elderly people: an integrative review

2021 ◽  
Vol 74 (suppl 2) ◽  
Author(s):  
Adnairdes Cabral de Sena ◽  
Angela Maria Alvarez ◽  
Simony Fabíola Lopes Nunes ◽  
Nadia Pinheiro da Costa
Keyword(s):  
Risk Factors ◽  
Elderly People ◽  
Nursing Care ◽  
Fall Prevention ◽  
Fall Risk ◽  
Risk Prevention ◽  
Hospitalized Elderly ◽  
Clinical Nursing ◽  
Fall Risk Factors ◽  
Care Behavior

ABSTRACT Objective: to identify scientific productions on nursing care related to fall risk prevention among hospitalized elderly people. Methods: an integrative literature review from 2015 to 2019 in the PubMed/MEDLINE, Scopus, Web of Science, LILACS, BDENF, SciELO and CINAHL databases, in Portuguese, English and Spanish. The keywords were elderly, hospitalization, accidents due to falls, nursing care. Results: thirty-three publications were analyzed. The synthesis of the studies resulted in the categories: Clinical nursing assessments to prevent falls among hospitalized elderly people; Fall risk factors for elderly people; Fall risk prevention strategies for elderly people. Final considerations: it was found that the scientific knowledge produced on nursing care related to fall risk prevention for hospitalized elderly people evidences the clinical assessment, risk factors and strategies such as nursing care, contributing to foster self-care behavior and promotion security for elderly people.

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