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Tarek Nasser El Harake

Bio: Tarek Nasser El Harake is an academic researcher from Carleton University. The author has contributed to research in topics: Video processing. The author has an hindex of 2, co-authored 2 publications receiving 29 citations.

Papers
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Proceedings ArticleDOI
14 May 2018
TL;DR: Early results show that an off the shelf system targeted for residential security and home automation applications based on low-cost sensors supported with automated analysis and classification has the potential to be used to assist caregivers and dementia patients.
Abstract: The measurement and detection of overnight wandering is a significant issue for dementia patients and their caregivers such as a spouse The wandering places the patient at risk of injury or even death if they fall or leave their residence without being detected While it also causes stress and reduced sleep for the caregiver as they try to remain alert to the actions of their partner This paper presents initial data for the first participant from an ongoing study of dementia patients where a wander detection and diversion system based on low-cost commercial sensors has been deployed into the residence The paper shows that over a 3-week period, the analysis and classification of the sensor data is able to measure the behavior of the patient In this period, the patient only used the washroom overnight and did not wander into other parts of the residence These early results show that an off the shelf system targeted for residential security and home automation applications based on low-cost sensors supported with automated analysis and classification has the potential to be used to assist caregivers and dementia patients

22 citations

Journal ArticleDOI
TL;DR: The potential of thermal video in conjunction with adaptive EVM methods to extract a signal representative of facial perfusion rate is demonstrated, and the need for more research on thermal video and adaptiveEVM is illustrated.
Abstract: The use of spatiotemporal video processing to extract biosignals is an emerging technique. This paper aims to build upon current work through robust experimentation and analysis. A blood flow simulation model was captured by thermal and optical cameras, while hot water was pumped through the system. Additionally, five subjects were recruited to perform two experimental trials: a facial perfusion trial and an arm blood occlusion trial, for which subjects sat quietly, while video data were captured using thermal and optical cameras. Each video was subjected to region of interest selection and adaptive Eulerian video magnification (EVM); the iterative application of EVM, first with a wide temporal bandpass filter and low amplification factor and again with a narrower, targeted temporal bandpass filter and higher amplification factor. The results from the simulation experiments indicated that thermal video in conjunction with adaptive EVM processing can reveal variations in temperature indicative of pulse rate in a controlled system of known variables. This process helped to better characterize Eulerian signal enhancement versus Eulerian noise enhancement. The results from the facial perfusion experiments suggest that the adaptive EVM processing of thermal video results in signals representative of facial perfusion rate. The results from the blood occlusion experiments revealed an occlusion temperature pattern, but not a perfusion rate. This paper therefore further demonstrated the potential of thermal video in conjunction with adaptive EVM methods to extract a signal representative of facial perfusion rate, and illustrated the need for more research on thermal video and adaptive EVM.

20 citations


Cited by
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Journal ArticleDOI
TL;DR: From this review, it emerges that automatic multiple regions of interest (ROIs) selection, removal of noise artefacts caused by both illumination variations and motion artefacts, simultaneous multiple person monitoring, long distance detection, multi-camera fusion and accepted publicly available datasets are topics that still require research to enable the technology to mature into many real-world applications.
Abstract: Techniques for noncontact measurement of vital signs using camera imaging technologies have been attracting increasing attention. For noncontact physiological assessments, computer vision-based methods appear to be an advantageous approach that could be robust, hygienic, reliable, safe, cost effective and suitable for long distance and long-term monitoring. In addition, video techniques allow measurements from multiple individuals opportunistically and simultaneously in groups. This paper aims to explore the progress of the technology from controlled clinical scenarios with fixed monitoring installations and controlled lighting, towards uncontrolled environments, crowds and moving sensor platforms. We focus on the diversity of applications and scenarios being studied in this topic. From this review it emerges that automatic multiple regions of interest (ROIs) selection, removal of noise artefacts caused by both illumination variations and motion artefacts, simultaneous multiple person monitoring, long distance detection, multi-camera fusion and accepted publicly available datasets are topics that still require research to enable the technology to mature into many real-world applications.

57 citations

Journal ArticleDOI
TL;DR: It is proved that investing the effort into acquiring appropriate training data and adapting competitive algorithms is not only a viable approach in analysing thermal infrared images but can also allow outperforming specific task-designed solutions.
Abstract: Thermal infrared imaging is an emerging modality that has gained increasing interest in recent years, mostly due to technical advances resulting in the availability of affordable microbolometer-based IR imaging sensors. However, while sensors are widely available, algorithms for thermal image processing still lack robustness and accuracy when compared to their RGB counterparts. Current methods developed for RGB data make use of machine learning algorithms that require large amounts of labeled images which are currently not available for the thermal domain. In this paper, we address the question whether providing a large number of labeled images would allow the application of current image processing methods on the example of solving challenging face analysis tasks. We introduce a high-resolution thermal facial image database with extensive manual annotations and explore how it can be used to adapt methods from the visual domain for infrared images. In addition, we extend existing approaches for infrared landmark detection with a head pose estimation for improved robustness and analyze the performance of a deep learning method on this task. An evaluation of algorithm performance shows that learning algorithms either outperform available solutions or allow completely new applications that could previously not be addressed. As a conclusion, we prove that investing the effort into acquiring appropriate training data and adapting competitive algorithms is not only a viable approach in analysing thermal infrared images but can also allow outperforming specific task-designed solutions. The database is freely available for academic use at https://github.com/marcinkopaczka/thermalfaceproject .

53 citations

Journal ArticleDOI
TL;DR: The main features and details the operating principles of MIMO technology are described and the state-of-the-art of the available solutions are summarized with the purpose of fueling the research activities on this hot topic.
Abstract: This paper reports a thorough overview on the last developments concerning the vital sign detection and the human localization employing the multiple-input-multiple-output (MIMO) technology. The wireless motion and vital sign detection represents an outstanding research area aimed at monitoring the health conditions of human subjects and at detecting their presence in different environments with minimal concern. MIMO radars exhibit several interesting advantages over conventional single-input-single-output architectures mainly related to their angle detection capabilities and enhanced signal-to-noise ratio. This paper describes the main features and details the operating principles of MIMO technology. Thereafter, it summarizes the state-of-the-art of the available solutions with the purpose of fueling the research activities on this hot topic.

38 citations

Journal ArticleDOI
21 Sep 2020
TL;DR: The Night-time Wandering Detection and Diversion system allows caregivers to rest peacefully in the night, as it detects when the person with dementia gets out of bed and automatically provides cue lighting to guide them safely to the washroom.
Abstract: IntroductionMore than half of persons with dementia will experience night-time wandering, increasing their risk of falls and unattended home exits. This is a major predictor of caregiver burnout an...

23 citations

Proceedings ArticleDOI
08 Jul 2019
TL;DR: The study investigates existing ICT solutions to improve the self-management ability of PwCl at different stages of cognitive impairment and proposes a modular and integrated platform for PwCI to self-manage various activities including nutrition, physical activities, social life, cognitive training.
Abstract: This paper reports the technologies and workplan of the AAL RESILIEN-T project. Focused on assistive technologies, RESILIEN-T aims to improve, through self-management, the autonomy, participation in social life, and skills, of older Persons with Cognitive Impairment (PwCI) who are too often considered as “objects” of research, rather than “partners”. The study investigates existing ICT solutions to improve the self-management ability of PwCl at different stages of cognitive impairment. Sensors, devices and apps to reduce the progression of the disease are analyzed. To increase sensor capability, innovative data management, i.e. Artificial Intelligence and Machine Learning algorithms, are considered to extract significant information from the data and optimize the sensor network. Moreover, approaches to involve end-users in the development are also investigated to enhance the final outputs. The study proposes a modular and integrated platform for PwCI to self-manage various activities including nutrition, physical activities, social life, cognitive training. The choice of offering an open API to integrate wearable devices and lifestyle monitoring systems from different suppliers makes available a customable and modular product. Considering that functional decline is part of the normal aging process, it might be challenging to individuate three levels of modular architecture to increase the accuracy of the monitoring with the decline of the cognitive capabilities.

13 citations