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Algorithm for Human Fall Detection Based on Acceleration Measurement
2020 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA), 2020According to the World Health Organization, a fall is defined as an unexpected event in which participant comes to rest on the ground, floor, or lower level. Falls are one of the most serious life-threatening events. Automatic detection of a fall can reduce the time of an arrival of medical attention and consequences of prolonged lying after a fall.In ...
Barbara Wilk +2 more
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Detecting Human Falls: A Vision-FSM Approach
2015In this paper, we present a computer vision based system able to detect human falls. We show in detail all the stages of our system and the considerations taken for the provided results. We propose a simple scheme for detection and tracking followed by a Finite State Machine (FSM).
Roger Trullo, Duber Martinez
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Human Fall Detection Using Kinect Sensor
2013Falls are major causes of mortality and morbidity in the elderly. The existing CCD-camera based solutions require time for installation, camera calibration and are not generally cheap. In this paper we show how to achieve automatic fall detection using Kinect sensor. The person is segmented on the basis of the updated depth reference images. Afterwards,
Michal Kepski, Bogdan Kwolek
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Human fall detection using slow feature analysis
Multimedia Tools and Applications, 2018Falls are reported to be the leading causes of accidental deaths among elderly people. Automatic detection of falls from video sequences is an assistant technology for low-cost health care systems. In this paper, we present a novel slow feature analysis based framework for fall detection in a house care environment.
Kaibo Fan, Ping Wang 0015, Shuo Zhuang
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A Novel Approach for Human Fall Detection and Fall Risk Assessment
2020There are several studies concerned in providing quality health care services to all people. Among them, human fall detection systems play an important role, because fall is the main obstacle for elderly people to live independently and it is also a major health concern due to aging population.
Yoosuf Nizam, M. Mahadi Abdul Jamil
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A Fall Detection System Based on Human Body Silhouette
2013 Ninth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2013Elderly care system is one among the most popular research topics in biomedical health-care system design as aging has emerged in different countries. We present a biologically-motivated system to detect unexpected falls in real-time video sequences. The system employs event-based temporal difference image between video sequences as input and extracts ...
Bor-Shing Lin +3 more
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Human fall detection in surveillance video based on PCANet
Multimedia Tools and Applications, 2015Fall incidents have been reported as the second most common cause of death, especially for elderly people. Human fall detection is necessary in smart home healthcare systems. Recently various fall detection approaches have been proposed., among which computer vision based approaches offer a promising and effective way.
Shengke Wang +4 more
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Human activity monitoring for falling detection. A realistic framework
2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2016During the last decades topics such as video analysis and image understanding techniques have experimented an important evolution due to its inclusion in applications such as surveillance, intelligent spaces and assisted living. In order to validate all related works different datasets have been distributed within the research community: CAVIAR, KTH ...
Marcos Baptista-Ríos +3 more
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Development of a wireless sensor network for human fall detection
2017 IEEE International Conference on Real-time Computing and Robotics (RCAR), 2017In this paper, we propose a simple methodology for human fall detection in an indoor environment by using a wireless sensor network. In the proposed methodology, two parallel layers at different heights of sensor nodes are deployed in the monitored environment.
Oo Oo Khin +2 more
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Detection of human fall in video using shadow information
2012 IEEE Biomedical Circuits and Systems Conference (BioCAS), 2012This paper presents a novel algorithm for detecting human fall incidents in video clips. This algorithm can effectively differentiate between fall-down and fall-like incidents such as sitting and squatting. Normally, complex 3-D models are required to solve this issue.
Yie-Tarng Chen +2 more
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