Improvement of fall detection using consecutive-frame voting

Poonsri, Arisa; Chiracharit, Werapon

doi:10.1109/iwait.2018.8369696

Cited by 24 publications

(10 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Based on current studies, fusion-based methods can be divided into homogeneous and heterogeneous-based approaches as listed in Table 7. For homogeneous fusion-based methods, they can be multiple threshold algorithms voting to determine falls as proposed by Poonsri et al [154]. Combination of machine learning methods can also be used to increase the accuracy of fall detection system as proposed by Cheng and Jhan [155].…”

Section: ) Fusion-based Fall Detection and Fall Preventionmentioning

confidence: 99%

Research of Fall Detection and Fall Prevention Technologies: A Systematic Review

2019

View full text Add to dashboard Cite

Falls are abnormal activity events that occur infrequently; however, they are serious health problems among elderly individuals. With the advancements of technologies, falls have been widely studied by scientific researchers to minimize serious consequences and negative impacts. Fall detection and fall prevention are two strategies to tackle fall issues with a variety of sensing techniques and classifier models. Currently, many reviews on fall-related technologies have been presented and analyzed; however, most of them give surveys on the subfield of fall-related systems, while others are not extensive and comprehensive reviews. In fact, the latest researches have a new trend of fusion-based methods to improve the performance of the fall-related systems based on a combination of different sensors or classifier models. Adaptive threshold and radio frequency-based systems are also researched and proposed recently, which are seldom mentioned in other reviews. Therefore, a global taxonomy for current fall-related studies from four aspects, including current literature reviews, fall detection, and prevention systems based on different sensor apparatus and analytic algorithm, low power techniques, and sensor placements for fall-related systems are conducted in this paper. Several research challenges and issues in the fall-related field are also discussed and analyzed. The objective of this review paper is to conclude and provide a good position of current fall-related studies to inspire researchers in this field. INDEX TERMSAdaptive algorithm, classification algorithms, fall detection, fall prevention, low power techniques, sensing techniques. LINGMEI REN received the Ph.D. degree from the

show abstract

Section: ) Fusion-based Fall Detection and Fall Preventionmentioning

confidence: 99%

Research of Fall Detection and Fall Prevention Technologies: A Systematic Review

2019

View full text Add to dashboard Cite

show abstract

“…They detected a fall by computing the distance between the top and mid center of the bounding box of a human. Poonsri et al [29] adopted a background subtraction and Gaussian mixture model to detect human objects. They then computed the orientation, aspect ratio, and area ratio to extract features and classify the postures.…”

Section: Image-based Methodsmentioning

confidence: 99%

An Image-Based Fall Detection System for the Elderly

Chu

2018

Applied Sciences

View full text Add to dashboard Cite

Due to advances in medical technology, the elderly population has continued to grow. Elderly healthcare issues have been widely discussed—especially fall accidents—because a fall can lead to a fracture and have serious consequences. Therefore, the effective detection of fall accidents is important for both elderly people and their caregivers. In this work, we designed an Image-based FAll Detection System (IFADS) for nursing homes, where public areas are usually equipped with surveillance cameras. Unlike existing fall detection algorithms, we mainly focused on falls that occur while sitting down and standing up from a chair, because the two activities together account for a higher proportion of falls than forward walking. IFADS first applies an object detection algorithm to identify people in a video frame. Then, a posture recognition method is used to keep tracking the status of the people by checking the relative positions of the chair and the people. An alarm is triggered when a fall is detected. In order to evaluate the effectiveness of IFADS, we not only simulated different fall scenarios, but also adopted YouTube and Giphy videos that captured real falls. Our experimental results showed that IFADS achieved an average accuracy of 95.96%. Therefore, IFADS can be used by nursing homes to improve the quality of residential care facilities.

show abstract

“…The results were compared with existing fall detection algorithms that are smartphone based, and it was found that the method achieved an acceptable false alarm rate. Fall detection was improved using consecutive-frame voting in this work [ 83 ]. The process starts with human detection using background subtraction.…”

Section: Research Publicationsmentioning

confidence: 99%

Pathway of Trends and Technologies in Fall Detection: A Systematic Review

Tanwar

Nandal²,

Zamani

et al. 2022

Healthcare

View full text Add to dashboard Cite

Falling is one of the most serious health risk problems throughout the world for elderly people. Considerable expenses are allocated for the treatment of after-fall injuries and emergency services after a fall. Fall risks and their effects would be substantially reduced if a fall is predicted or detected accurately on time and prevented by providing timely help. Various methods have been proposed to prevent or predict falls in elderly people. This paper systematically reviews all the publications, projects, and patents around the world in the field of fall prediction, fall detection, and fall prevention. The related works are categorized based on the methodology which they used, their types, and their achievements.

show abstract

Improvement of fall detection using consecutive-frame voting

Cited by 24 publications

References 5 publications

Research of Fall Detection and Fall Prevention Technologies: A Systematic Review

Research of Fall Detection and Fall Prevention Technologies: A Systematic Review

An Image-Based Fall Detection System for the Elderly

Pathway of Trends and Technologies in Fall Detection: A Systematic Review

Contact Info

Product

Resources

About