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Fall-related injuries of elderly people have become a major public-health burden resulting in direct physical, physiological and financial costs to the surfer and indirect societal costs. Automated fall detectors play a central role in reducing these damages and in supporting safety and independency of the seniors. Typically, automated fall detection devices can send real time notifications to the...
This paper proposes a hardware/software co-design approach using the Zynq platform for the implementation of an electronic nose (EN) system based on principal component analysis (PCA) as a dimensionality reduction technique and decision tree (DT) as a classification algorithm using a 4x4 in-house fabricated sensor. The system was successfully trained and simulated in MATLAB environment prior to the...
Falling can cause significant injury, where quick medical response and fall information are critical to providing aid. In this paper we present a wearable wireless fall detection system utilising a Shimmer accelerometer device, where important additional information is obtained, such as direction and strength of the occurred fall instance. Discrete Wavelet Transforms and multiresolution wavelet analysis...
Fall detection is a major problem in healthcare systems, especially for elderly people who are the most vulnerable. It is important to design and implement not only an accurate fall detection system (FDS) but also a system with a real-time response. The achievement of high accuracy and fast response time together allows the development of a system that helps saving lives, time and money in healthcare...
Long-time cycle wireless monitoring of patients with health concerns is highly required. The quality of care, ability of fall detection and prevention is tremendously increased through enabling continous remote human movement monitoring. The aim of this paper is twofold. Firstly, to propose a real-time energy-aware wireless fall detection system based on emerging compresive sensing (CS). Secondly,...
In this paper, an energy aware real-time wireless fall detection system based on the multi-scale analysis is proposed. Furthermore, an efficient feature extraction and compression algorithm for high accuracy fall recognition is presented. The proposed algorithm is carried out on the low-power Shimmer sensing platform. The developed method aims to reduce the amount of 3D acceleration data for energy...
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