Recently, fall risk assessment has been a main focus in fall-related research. Wearable sensors have been used to increase the objectivity of this assessment, building on the traditional use of oversimplified questionnaires. However, it is necessary to define standard procedures that will us enable to acknowledge the multifactorial causes behind fall events while tackling the heterogeneity of the currently developed systems. Thus, it is necessary to identify the different specifications and demands of each fall risk assessment method. Hence, this manuscript provides a narrative review on the fall risk assessment methods performed in the scientific literature using wearable sensors. For each identified method, a comprehensive analysis has been carried out in order to find trends regarding the most used sensors and its characteristics, activities performed in the experimental protocol, and algorithms used to classify the fall risk. We also verified how studies performed the validation process of the developed fall risk assessment systems. The identification of trends for each fall risk assessment method would help researchers in the design of standard innovative solutions and enhance the reliability of this assessment towards a homogeneous benchmark solution.
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http://dx.doi.org/10.3390/s22030984 | DOI Listing |
Otol Neurotol
February 2025
Department of Otolaryngology-Head and Neck Surgery.
Objective: To compare fall risk scores of hearing aids embedded with inertial measurement units (IMU-HAs) and powered by artificial intelligence (AI) algorithms with scores by trained observers.
Study Design: Prospective, double-blinded, observational study of fall risk scores between trained observers and those of IMU-HAs.
Setting: Tertiary referral center.
J Occup Health
January 2025
Panasonic Corporation, Department Electric Works Company/Engineering Division, Osaka, Japan.
Background: Falls are among the most prevalent workplace accidents, necessitating thorough screening for susceptibility to falls and customization of individualized fall prevention programs. The aim of this study was to develop and validate a high fall risk prediction model using machine learning (ML) and video-based first three steps in middle-aged workers.
Methods: Train data (n=190, age 54.
BMC Geriatr
January 2025
Physical Therapy Department, Prince Sultan Military College of Health Sciences, Dhahran, Saudi Arabia.
Background: Chronic nonspecific neck pain (CNSNP) is a common musculoskeletal disorder, particularly in the elderly, leading to reduced cervical muscle strength, impaired functional balance, and decreased postural stability. This study investigated the correlation between cervical muscle strength, functional balance, and limits of stability (LOS) in elderly individuals with CNSNP. Additionally, it assessed the moderating effect of pain severity on the relationship between cervical muscle strength and these balance outcomes.
View Article and Find Full Text PDFJ Trauma Acute Care Surg
January 2025
From the Department of Surgery (J.H., K.S., G.S.C., C.T., L.R., G.B.); School of Public Health (A.B., O.H., A.S., S.M.); Hennepin Healthcare (S.K.); Department of Emergency Medicine (S.K., M.A.P.); and Hennepin Healthcare, Department of Emergency Medicine (M.A.P.), Minneapolis, Minnesota.
Background: There is conflicting evidence regarding emergency medical service (EMS) provider level of training and outcomes in trauma. We hypothesized that advanced life support (ALS) provider transport is associated with lower mortality compared with basic life support transport.
Methods: We performed secondary analysis of a combined prehospital and in-hospital database of trauma patients utilizing ESO electronic medical records from 2018 to 2022.
Alzheimers Dement
December 2024
Augusta University, Augusta, GA, USA
Background: People living with dementia (PWD) have upregulated inflammatory pathways, exaggerated metabolic aging, and cellular aging. They also have declines in physical function and heightened fall‐risk. Understanding the physiologic factors that influence physical decline and fall‐risk in PWD is vital to assess and prevent adverse health outcomes, such as future falls.
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