Dynamic Fall Risk Assessment Framework for Construction Workers Based on Dynamic Bayesian Network and Computer Vision

Author(s):  
Yanmei Piao ◽  
Wenpei Xu ◽  
Ting-Kwei Wang ◽  
Jieh-Haur Chen
2016 ◽  
Vol 34 (1) ◽  
pp. 42-53
Author(s):  
Kyung-Wan Seo ◽  
Jeong-Ok Lee ◽  
Sun-Young Choi ◽  
Min-Jung Park

Author(s):  
Francisco José Ariza-Zafra ◽  
Rita P. Romero-Galisteo ◽  
María Ruiz-Muñoz ◽  
Antonio I. Cuesta-Vargas ◽  
Manuel González-Sánchez

2021 ◽  
pp. 1-9
Author(s):  
Victoire Leroy ◽  
Yaohua Chen ◽  
Naiara Demnitz ◽  
Florence Pasquier ◽  
Pierre Krolak-Salmon ◽  
...  

Background: Falls are a major health problem in older persons but are still under-diagnosed and challenging to prevent. Current guidelines do not target high-risk populations, especially people living with dementia. In France, people with neurocognitive disorders are mainly referred to memory clinics (MCs). Objective: We aimed to survey the routine practice of physicians working in MCs regarding fall risk assessment. Methods: We conducted a cross-sectional survey in France from January to May 2019 among physicians working in MCs, through an anonymous online questionnaire: twenty-seven questions about the physician’s background and their practice of fall risk assessment, especially use of clinical and paraclinical tools. We compared the results according to the age and the specialty of the physician. Results: We obtained 171 responses with a majority of women (60%) and geriatricians (78%). All age classes and all French regions were represented. Most of respondents (98.8%) stated that they address gait and/or falls in outpatient clinic and 95.9%in day hospitals. When asked about how they assess fall risk, fall history (83%) and gait examination (68.4%) were the most widely used, while orthostatic hypotension (24%) and clinical standardized tests (25.7%) were less common. Among standardized tests, One-leg Balance, Timed Up and Go Test, and gait speed measurements were the most used. Geriatricians had more complete fall risk assessment than neurologists (e.g., 56%versus 13%for use of standardized tests, p <  0.0001). Conclusion: Almost all physicians addressed the question of fall in MC, but practices are widely heterogeneous. Further investigations are needed to standardize fall risk assessment in MCs.


Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1338
Author(s):  
Wojciech Tylman ◽  
Rafał Kotas ◽  
Marek Kamiński ◽  
Paweł Marciniak ◽  
Sebastian Woźniak ◽  
...  

This paper presents a fall risk assessment approach based on a fast mobility test, automatically evaluated using a low-cost, scalable system for the recording and analysis of body movement. This mobility test has never before been investigated as a sole source of data for fall risk assessment. It can be performed in a very limited space and needs only minimal additional equipment, yet provides large amounts of information, as the presented system can obtain much more data than traditional observation by capturing minute details regarding body movement. The readings are provided wirelessly by one to seven low-cost micro-electro-mechanical inertial measurement units attached to the subject’s body segments. Combined with a body model, these allow segment rotations and translations to be computed and for body movements to be recreated in software. The subject can then be automatically classified by an artificial neural network based on selected values in the test, and those with an elevated risk of falls can be identified. Results obtained from a group of 40 subjects of various ages, both healthy volunteers and patients with vestibular system impairment, are presented to demonstrate the combined capabilities of the test and system. Labelling of subjects as fallers and non-fallers was performed using an objective and precise sensory organization test; it is an important novelty as this approach to subject labelling has never before been used in the design and evaluation of fall risk assessment systems. The findings show a true-positive ratio of 85% and true-negative ratio of 63% for classifying subjects as fallers or non-fallers using the introduced fast mobility test, which are noticeably better than those obtained for the long-established Timed Up and Go test.


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