AIMC Topic: Geriatric Assessment
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Determinants of Attitude to a Humanoid Social Robot in Care for Older Adults: A Post-Interaction Study.
Medical science monitor : international medical journal of experimental and clinical research
Sep 8, 2023
BACKGROUND While there is a growing body of research examining opinions on social robots in elderly care, there is a lack of comprehensive studies investigating the underlying factors influencing these opinions. The Godspeed Questionnaire Series (GQS...
Frailty Identification Using Heart Rate Dynamics: A Deep Learning Approach.
IEEE journal of biomedical and health informatics
Jul 1, 2022
Previous research showed that frailty can influence autonomic nervous system and consequently heart rate response to physical activities, which can ultimately influence the homeostatic state among older adults. While most studies have focused on rest...
An Automated Planning Model for HRI: Use Cases on Social Assistive Robotics.
Sensors (Basel, Switzerland)
Nov 14, 2020
Using Automated Planning for the high level control of robotic architectures is becoming very popular thanks mainly to its capability to define the tasks to perform in a declarative way. However, classical planning tasks, even in its basic standard P...
An Artificial Neural Network Model for Assessing Frailty-Associated Factors in the Thai Population.
International journal of environmental research and public health
Sep 18, 2020
Frailty, one of the major public health problems in the elderly, can result from multiple etiologic factors including biological and physical changes in the body which contribute to the reduction in the function of multiple bodily systems. A diagnosi...
Using Machine Learning to Predict Rehabilitation Outcomes in Postacute Hip Fracture Patients.
Archives of physical medicine and rehabilitation
Sep 16, 2020
OBJECTIVE: To use machine learning-based methods in designing a predictive model of rehabilitation outcomes for postacute hip fracture patients.
Development and validation of a robotic multifactorial fall-risk predictive model: A one-year prospective study in community-dwelling older adults.
PloS one
Jun 25, 2020
BACKGROUND: Falls in the elderly are a major public health concern because of their high incidence, the involvement of many risk factors, the considerable post-fall morbidity and mortality, and the health-related and social costs. Given that many fal...
Predicting hospital admission for older emergency department patients: Insights from machine learning.
International journal of medical informatics
May 16, 2020
BACKGROUND: Emergency departments (ED) are a portal of entry into the hospital and are uniquely positioned to influence the health care trajectories of older adults seeking medical attention. Older adults present to the ED with distinct needs and com...
Applying machine learning methods to develop a successful aging maintenance prediction model based on physical fitness tests.
Geriatrics & gerontology international
May 1, 2020
AIM: The purpose of this study was to develop a machine learning prediction model for successful aging (SA) based on physical fitness tests.
Healthy Aging
ROC Curve
Logistic Models
Follow-Up Studies
Decision Trees
Predictive Value of Tests
Humans
Geriatric Assessment
Machine Learning
Physical Fitness
Middle Aged
Female
Independent Living
Aged, 80 and over
Exercise
Aged
Sensitivity and Specificity
China
Male
Surveys and Questionnaires
Aging
A social robot intervention on depression, loneliness, and quality of life for Taiwanese older adults in long-term care.
International psychogeriatrics
Apr 14, 2020
OBJECTIVES: To investigate the effect of a social robot intervention on depression, loneliness, and quality of life of older adults in long-term care (LTC) and to explore participants' experiences and perceptions after the intervention.
Deep learning prediction of falls among nursing home residents with Alzheimer's disease.
Geriatrics & gerontology international
Apr 8, 2020
AIM: This study aimed to use a convolutional neural network (CNN) to investigate the associations between the time of falling and multiple complicating factors, including age, dementia severity, lower extremity strength and physical function, among n...
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