SWEET-HOME ICT technologies for the assessment of elderly subjects

International audienceFunctional assessments are designed to ascertain a person's ability to perform activities of daily living (ADL) and provide valuable diagnostic as well as care-planning information. Currently, the gold-standard for the assessment of functional ability involves clinical rating scales however scales are often limited in their ability to provide objective and sensitive information. In contrast, information and communication technologies (ICT) may overcome these limitations by capturing more fully the functional, well as behavioural and cognitive disturbances associated with Alzheimer disease (AD)

Weighted Module Linear Regression Classifications for Partially-Occluded Face Recognition

Face images with partially-occluded areas create huge deteriorated problems for face recognition systems. Linear regression classification (LRC) is a simple and powerful approach for face recognition, of course, it cannot perform well under occlusion situations as well. By segmenting the face image into small subfaces, called modules, the LRC system could achieve some improvements by selecting the best non-occluded module for face classification. However, the recognition performance will be deteriorated due to the usage of the module, a small portion of the face image. We could further enhance the performance if we can properly identify the occluded modules and utilize all the non-occluded modules as many as possible. In this chapter, we first analyze the texture histogram (TH) of the module and then use the HT difference to measure its occlusion tendency. Thus, based on TH difference, we suggest a general concept of the weighted module face recognition to solve the occlusion problem. Thus, the weighted module linear regression classification method, called WMLRC-TH, is proposed for partially-occluded fact recognition. To evaluate the performances, the proposed WMLRC-TH method, which is tested on AR and FRGC2.0 face databases with several synthesized occlusions, is compared to the well-known face recognition methods and other robust face recognition methods. Experimental results show that the proposed method achieves the best performance for recognize occluded faces. Due to its simplicity in both training and testing phases, a face recognition system based on the WMLRC-TH method is realized on Android phones for fast recognition of occluded faces

First results from the SafEE project: Safe & Easy Environment for Alzheimer's

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Alzheimer's patient activity assessment using different sensors

International audiencePurpose: Older people population is expected to grow dramatically over the next 20 years (including Alzheimer's patients), while the number of people able to provide care will decrease. We present the development of medical and information and communication technologies to support the diagnosis and evaluation of dementia progress in early stage Alzheimer disease (AD) patients.Method: We compared video and accelerometers activity assessment for the estimation of older people performance in instrumental activities of daily living (IADL) and physical tests in the clinical protocol developed by the Memory Center of the Nice Hospital and the Department of Neurology at National Cheng Kung University Hospital - Taiwan. This clinical protocol defines a set of IADLs (e.g., preparing coffee, watching TV) that could provide objective information about dementia symptoms and be realistically achieved in the two sites observation room. Previous works studied accelerometers activity assessment for the detection of changes in older people gait patterns caused by dementia progress, or video-based event detection for personal self-care activities (ADLs)[1, 2, 3], but none has used both sensors for IADLs analysis. The proposed system uses a constraint-based ontology to model and detect events based on different sensors readings (e.g., 2D video stream data is converted to 3D geometric information that is combined with a priori semantic information, like defined spatial zones or posture estimations given by accelerometer). The ontology language is declarative and intuitive (as it uses natural terminology), allowing medical experts to define and modify the IADL models. The proposed system was tested with 44 participants (healthy=21, AD=23). A stride detection algorithm was developed by the Taiwanese team for the automatic acquisition of patients gait parameters (e.g., stride length, stride frequency) using a tri-axial accelerometer embedded in a wearable device. It was tested with 33 participants (healthy=17, Alzheimer = 16) during a 40 meters walking test. Results & Discussion: The proposed system detected the full set of activities of the first part of our clinical protocol (e.g., repeated transfer test, walking test) with a true positive rate of 96.9 % to 100%. Extracted gait parameters and automatically detected IADLs will be future analyzed for the evaluation of differences between Alzheimer patients at mild to moderate stages and healthy control participants, and for the monitoring of patients motor and cognitive abilities

Recommendations for ICT use in Alzheimer's Disease assessment: Monaco CTAD expert meeting

International audienceAlzheimer disease (AD) and other related dementia represent a major challenge for health care systems within the aging population. It is therefore important to develop better instruments for assessing disease severity and disease progression to optimize patient's care and support to care provide rs, and also provide better tools for clinical research. In this area, Information and Communication Technologies (ICT) are of particular interest. Such techniques enable accurate and standardized assessments of patients' performance and actions in real time and real life situations. The aim of this article is to provide basic recommendation concerning the development and the use of ICT for Alzheimer's disease and related disorders. During he ICT and Mental Health workshop (CTAD meeting held in Monaco on the 30th October 2012) an expert panel was set up to prepare the first recommendations for the use of ICT in dementia research. The expert panel included geriatrician, epidemiologist, neurologist, psychiatrist, psychologist, ICT engineers, representatives from the industry and patient association. The recommendations are divided into three sections corresponding to 1/ the clinical targets of interest for the use of ICT, 2/ the cond itions, the type of sensors and the outputs (scores) that could be used and obtained, 3/ finally the last section concerns specifically the use of ICT within clinical trials

A Hierarchical Estimator for Object Tracking

A closed-loop local-global integrated hierarchical estimator (CLGIHE) approach for object tracking using multiple cameras is proposed. The Kalman filter is used in both the local and global estimates. In contrast to existing approaches where the local and global estimations are performed independently, the proposed approach combines local and global estimates into one for mutual compensation. Consequently, the Kalman-filter-based data fusion optimally adjusts the fusion gain based on environment conditions derived from each local estimator. The global estimation outputs are included in the local estimation process. Closed-loop mutual compensation between the local and global estimations is thus achieved to obtain higher tracking accuracy. A set of image sequences from multiple views are applied to evaluate performance. Computer simulation and experimental results indicate that the proposed approach successfully tracks objects

A Hierarchical Estimator for Object Tracking

A closed-loop local-global integrated hierarchical estimator (CLGIHE) approach for object tracking using multiple cameras is proposed. The Kalman filter is used in both the local and global estimates. In contrast to existing approaches where the local and global estimations are performed independently, the proposed approach combines local and global estimates into one for mutual compensation. Consequently, the Kalman-filter-based data fusion optimally adjusts the fusion gain based on environment conditions derived from each local estimator. The global estimation outputs are included in the local estimation process. Closed-loop mutual compensation between the local and global estimations is thus achieved to obtain higher tracking accuracy. A set of image sequences from multiple views are applied to evaluate performance. Computer simulation and experimental results indicate that the proposed approach successfully tracks objects.</p

A novel mechanism for providing service differentiation over CATV network

[[abstract]]With the emersion of new types of applications on the Internet, the need of broadband access is unavoidable. It also makes the differentiation of services provided by the network necessary. One of the most competitive broadband access solutions is Cable TV network since it is a network now in widespread use with enough bandwidth. Among the protocols of digital data-over-cable, Multimedia Cable Network System (MCNS) Data-Over-Cable Service Interface Specifications (DOCSIS) is the most popular standard nowadays. Based on this standard, we proposed a novel mechanism that can provide service differentiation over cable network. We explain the detail operation and interaction of each part of the system in this paper. Simulation is used to find out the performance on two subjects. First, MAC protocol configurations and parameters are discussed. Second, we compare various scheduling methods for providing service differentiation in the headend. From the results, the proposed mechanism is applicable and the characteristics of key parameters are found. © 2002 Elsevier Science B.V. All rights reserved.[[incitationindex]]SCI[[incitationindex]]EI[[booktype]]紙