Search results for "fall detection"

Fall Detection Based on the Instantaneous Doppler Frequency : A Machine Learning Approach

2019

Modern societies are facing an ageing problem which comes with increased cost of healthcare. A major share of this ever-increasing cost is due to fall related injuries, which urges the development of fall detection systems. In this context, this paper paves the way for building of a radio-frequency-based fall detection system. This paper presents an activity simulator that generates the complex channel gain of indoor channels in the presence of one person performing three different activities, namely, slow fall, fast fall, and walking. We built a machine learning framework for activity recognition based on the complex channel gain. We assess the recognition accuracy of three different class…

Fast prototyping of a SoC-based smart-camera: a real-time fall detection case study

2014

International audience; Smart camera, i.e. cameras that are able to acquire and process images in real-time, is a typical example of the new embedded computer vision systems. A key example of application is automatic fall detection, which can be useful for helping elderly people in daily life. In this paper, we propose a methodology for development and fast-prototyping of a fall detection system based on such a smart camera, which allows to reduce the development time compared to standard approaches. Founded on a supervised classification approach, we propose a HW/SW implementation to detect falls in a home environment using a single camera and an optimized descriptor adapted to real-time t…

A Machine Learning Approach for Fall Detection and Daily Living Activity Recognition

2019

The number of older people in western countries is constantly increasing. Most of them prefer to live independently and are susceptible to fall incidents. Falls often lead to serious or even fatal injuries which are the leading cause of death for elderlies. To address this problem, it is essential to develop robust fall detection systems. In this context, we develop a machine learning framework for fall detection and daily living activity recognition. We use acceleration and angular velocity data from two public databases to recognize seven different activities, including falls and activities of daily living. From the acceleration and angular velocity data, we extract time- and frequency-do…

A Machine Learning Approach for Fall Detection Based on the Instantaneous Doppler Frequency

2019

Modern societies are facing an ageing problem that is accompanied by increasing healthcare costs. A major share of this ever-increasing cost is due to fall-related injuries, which urges the development of fall detection systems. In this context, this paper paves the way for the development of radio-frequency-based fall detection systems, which do not require the user to wear any device and can detect falls without compromising the user's privacy. For the design of such systems, we present an activity simulator that generates the complex path gain of indoor channels in the presence of one person performing three different activities: slow fall, fast fall, and walking. We have developed a mac…

WiseEye: A Platform to Manage and Experiment on Smart Camera Networks

2016

International audience; Embedded vision is probably at the edge of phenomenal expansion. The smart cameras are embedding some processing units which are more and more powerful. Last decade, high-speed image processing can be implemented on specifically designed architectures [1] nevertheless the designing time of such systems was quite high and time to market therefore as well. Since, powerful chips (i.e System On Chip) and quick prototyping methodologies are contently emerging [2],[3],[4] and enable more complex algorithms to be implemented faster. Moreover, smart cameras which are embedding flexible and powerful multi-core processors or Graphic Processors Unit (GPU) are now available and …

Robust spatio-temporal descriptors for real-time SVM-based fall detection

2014

Time-Frequency Characteristics of In-Home Radio Channels Influenced by Activities of the Home Occupant

2019

While aging is a serious global concern, in-home healthcare monitoring solutions are limited to context-aware systems and wearable sensors, which may easily be forgotten or ignored for privacy and comfort reasons. An emerging non-wearable fall detection approach is based on processing radio waves reflected off the body, who has no active interaction with the system. This paper reports on an indoor radio channel measurement campaign at 5.9 GHz, which has been conducted to study the impact of fall incidents and some daily life activities on the temporal and spectral properties of the indoor channel under both line-of-sight (LOS) and obstructed-LOS (OLOS) propagation conditions. The time-frequ…

Human Activity Signatures Captured under Different Directions Using SISO and MIMO Radar Systems

2022

In this paper, we highlight and resolve the shortcomings of single-input single-output (SISO) millimeter wave (mm-Wave) radar systems for human activity recognition (HAR). A 2×2 distributed multiple-input multiple-output (MIMO) radar framework is presented to capture human activity signatures under realistic conditions in indoor environments. We propose to distribute the two pairs of collocated transmitter–receiver antennas in order to illuminate the indoor environment from different perspectives. For the proposed MIMO system, we measure the time-variant (TV) radial velocity distribution and TV mean radial velocity to observe the signatures of human activities. We deploy the Anc…

Definition and performance evaluation of a robust SVM based fall dectection system

2012

International audience

Usability and acceptability of a fall monitoring system

2017

Falls and injurious falls affect one third of the older people. Those experiencing a fall might be unable to call for help remaining unattended for a long time. Pain, hypothermia and dehydration are common consequences. Additionally, ensuing fear of falling may reduce physical activity leading to functional decline and possibly institutionalization. Monitoring fall events the CONFIDENCE system could summon emergency assistance automatically thus reducing the negative consequences of falls. This thesis is part of the European FP7 project “Ubiquitous care system to support independent living” (CONFIDENCE) which developed a fall monitoring system based on three-dimensional (3D) localization of…