An Adaptive Tracker for Assisted Living

Artificial vision provides an incomparable good sensor when developing video care applications. They are not too intrusive and also supply a great amount of information, besides they are quite cheap. A video care application must work in real time providing tools for agile management of images. Furthermore, images only give us two-dimensional data but the most part of useful information is three-dimensional, so we must be able to extract it from them. In this article we introduce an application for elder persons care using only visual information. The system allows detecting problems such as a faint, a fall to the ground or reaching a window. The automatic monitoring of these people can provide them with a greater level of autonomy.

IEEE Pervasive Computing, 2004

Proceedings of the 1st …, 2008

This paper presents our approach in understanding the behavior of humans moving on a plane using multiple cameras. This approach is appropriate for monitoring people in an assistive enivronment for the purpose of issuing alerts in cases of abnormal behavior. We perform camera registration based on homography estimation and we extract position on 2D projection map. We use the output of multiple classifiers to model and extract abnormal behaviour from both the target trajectory and the target short term activity (i.e., walking, running, abrupt motion etc). The proposed approach is verified experimentally in an indoor environment. The experiments are performed with a single moving target, however the method can be generalised to multiple moving targets, which may occlude each other, due to the use of multiple cameras.

2017 IEEE/ACS 14th International Conference on Computer Systems and Applications (AICCSA), 2017

Recently, Ambient Intelligence Systems (AmI) in particular Ambient Assisted Living (AAL) are attracting intensive research due to a large variety of application scenarios and an urgent need for elderly in-home assistance. AAL is an emerging multidisciplinary paradigm aiming at exploiting information and communication technologies in personal healthcare and telehealth systems for countering the effects of growing elderly population. AAL systems are developed to help elderly people living independently by monitoring their health status and providing caregivers with useful information. However, strong contributions are yet to be made on context binding of newly discovered sensors for providing dynamic or/and adaptive UI for caregivers, as the existing solutions (including framework, systems and platforms) are mainly focused on checking user operation history, browser history and applications that are most used by a user for prediction and display of the applications to an individual user. The aim of this paper is to propose a framework for making the adaptive UI from context information (real-time and historical data) that is collected from caregivers (primary user) and elderly people (secondary user). The collected data is processed to produce the contextual information in order to provide assistive services to each individual caregiver. To achieve this, the proposed framework collects the data and it uses a set of techniques (including system learning, decision making) and approaches (including ontology, user profiling) to integrate assistive services at runtime and enable their bindings to specific caregivers, in so doing improving the adaptability parameter of UI for the AAL.

Universal Access in …, 2009

Ambient Assisted Living (AAL) is currently one of the important research and development areas, where software engineering aspects play a significant role. The goal of AAL solutions is to apply ambient intelligence technologies to enable people with specific needs to continue to live in their preferred environments. This paper presents an approach and several evaluations for emergency monitoring applications. Experiments in a laboratory setting were performed to evaluate the accuracy of recognizing Activities of Daily Living (ADL). The results show that it is possible to detect ADLs with an accuracy of 92% on average. Hence, we conclude that it is possible to support elderly people in staying longer in their homes by autonomously detecting emergencies on the basis of ADL recognition.

One of the common problems face by elderly people is Dementia, and the people affected by this Disease is escalating as compared to the past. People suffering from Dementia and Alzheimer's face many challenges in their day to day routine and their families and caretakers face major difficulty to monitor them. The Dementia patient has symptoms like loss of memory, change in behavior, and change in character, forgets to do their everyday tasks and forgets their environment and they will not even respond to their name being called. This survey mainly focuses on the methods and techniques used for monitoring Dementia Patients. This paper includes a survey on how the different types of methods are used to monitor Dementia patients. This paper also includes the location tracking of the Dementia Patients if they are lost, and using different techniques like Bluetooth device, GPS, Hardware Devices using which the patients can be tracked, So that the patient can be tracked quickly and safely. There are many devices available to monitor the Dementia and Alzheimer's disease and this paper includes the different types of devices, algorithms and techniques used for monitoring the patients.

Soft Computing Models …, 2011

Monitoring and tracking of elderly people using vision algorithms is an strategy gaining relevance to detect anomalous and potentially dangerous situations and react immediately. In general vision algorithms for monitoring and tracking are very costly and take a lot of time to respond, which is highly inconvenient since many applications can require action to be taken in real time. A multi-agent system (MAS) can establish a social model to automate the tasks carried out by the human experts during the process of analyzing images obtained by cameras. This study presents a detector agent integrated in a MAS that can process stereoscopic images to detect and classify situations and states of elderly people in geriatric residences by combining a series of novel techniques. We will talk in details about the combination of techniques used to perform the detection process, subdivided into human detection, human tracking ,and human behavior understanding, and where there is a case-based reasoning (CBR) model that allows the system to add reasoning capabilities.

The Smart Computing Review, 2012

This paper is an overview of our ongoing project that proposes a monitoring system based on various sensors to detect risky situations for the elderly. From the standpoint of the enduser, a video surveillance system equipped with many other sensors can relieve caregivers from the need to keep a vigilant eye on each patient's movements, while such technology can be effectively used for monitoring elderly people with dementia. Since a camera surveillance system has limits to classify complex human actions, this project aims to design an intelligent healthcare surveillance system, which extends the conventional automated video surveillance system with various additional sensors, to improve the performance of surveillance. The main contributions of our proposed system will be to: (i) minimize human intervention; (ii) detect more complex activities and situations using various sensors and improved sensor fusion techniques; and (iii) design a novel classifier that identifies risky situations with the collected information.

2016 IEEE 12th International Conference on Intelligent Computer Communication and Processing (ICCP), 2016

Wearable and handheld devices, such smart phones, have come a long way in a very short time as they are capable of providing an extremely vast number of services simply at the click of a button, or even automatically. The diversity of the different embedded sensors (accelerometer, light sensors, etc.) lay the required foundation for the emergence of specialized applications that are capable of serving all kinds of purposes. By taking advantage of this specialized hardware found in smart phones, not only it has become feasible to constantly sense and gather information from the device's environment, but it has also become an effortless task to transmit the collected data to any individual or organization in a plethora of forms. This paper serves as an evaluation method for a location based Android application, SeniorTracker, by presenting a comparison between two applications that are both used for tracking down a device. While both have quite a similar purpose, the way they go about it as well as the ways the application itself can be utilized, drastically differs. SeniorTracker's main purpose lies in the retrieval of the coordinates of a device in case it is located somewhere it is not expected to be, allowing monitoring of persons that potentially will be lost, otherwise. The comparison was mainly focused on the performance of both applications when it comes to location retrieval and energy consumption while keeping in mind the respective tasks that each of them were designed to fulfill.

2010