Elderly People Telemonitoring in an Integrated Smart House Environment (original) (raw)
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A pervasive multi-sensor data fusion for smart home healthcare monitoring
IEEE International Conference on Fuzzy Systems, 2011
Today elderly people are the fastest growing segment of the population in developed countries, and they desire to live as independently as possible. But independent lifestyles come with risks and challenges. Medical in-home telemonitoring (and, more generally, telemedicine) is a solution to deal with these challenges and to ensure that elderly people can live safely and independently in their own homes for as long as possible. In this context we propose an automatic in-home healthcare monitoring system for several uses and to meet the needs identified above. The proposed telemonitoring system is a multimodal platform with several sensors that can be installed at home and enables us to have a full and tightly controlled universe of data sets. It integrates elderly physiological and behavioral data, the acoustical environment of the elderly, environmental conditions and medical knowledge. Each modality is processed and analyzed by specific algorithms. A data fusion approach based on fuzzy logic with a set of rules directed by medical recommendations, is used to fuse the various subsystem outputs. This multimodal fusion increases the reliability of the whole system by detecting several distress situations. In fact this fusion approach takes into account temporary sensor malfunction and increases the system reliability and the robustness in the case of environmental disturbances or material limits (Battery, RF range, etc.). The Fuzzy logic fusion methods brings high flexibility to the telemonitoring platform especially in combining modalities or adding other sensors. The proposed telemonitoring system will ensure pervasive in-home health monitoring for elderly people.
A Fuzzy Logic System For Home Elderly People Monitoring (EMUTEM
The purpose of this paper is to present a view of a telemonitoring system based on fuzzy logic for distress situations detection of elderly people living alone in the home environment. This system includes three different sensors: physiological sensors (cardiac frequency, activity or agitation, posture and fall detection sensor), microphones and infrared sensors. Taking into account the difficulty of the statistical modeling of abnormal situation and considering that the Fuzzy Logic has been actually used with success in the development of classifier and analysis of control systems, its use in the decision fusion module of our home elderly people monitoring system is presented and evaluated in this paper.
Comptes Rendus Biologies, 2002
We deal in this paper with the concept of health smart home (HSH) designed to follow dependent people at home in order to avoid the hospitalisation, limiting hospital sojourns to short acute care or fast specific diagnostic investigations. For elderly people the project of such a HSH has been called AISLE (Apartment with Intelligent Sensors for Longevity Effectiveness). For this purpose, system having three levels of automatic measuring (1) the circadian activity, (2) the vegetative state, and (3) some state variables specific of certain organs involved in precise diseases, has been developed within the framework of a 'Health Integrated Smart Home Information System' (HIS 2 ). HIS 2 is an experimental platform for technologic development and clinical evaluation, in order to ensure the medical security and quality of life for patients who need home based medical monitoring. Location sensors are placed in each room of the HIS 2 , allowing the monitoring of patient's successive daily activity phases within the patient's home environment. We proceed with a sampling in an hourly schedule to detect weak variations of the nycthemeral rhythms. Based on numerous measurements, we establish a mean value with confidence limits of activity variables in normal behaviour permitting to detect for example a sudden abnormal event (like a fall) as well as a chronic pathologic activity (like a pollakiuria), allowing us to define a canonical domain within which the patient's activity is qualified to be 'predictable'. Alerts are set off if the patient's activity deviates from a predictable canonical domain. Moreover, we can follow the cardio-respiratory state by measuring the intensity of the respiratory sinusal arrhythmia in order to quantify the integrity of the bulbar vegetative system, and we finally propose to carefully watch abnormal symptoms like arterial pressure or presence of plasma proteins in the expired air flow for early detecting respectively hypertension or pulmonary oedema.
Data fusion in health smart home : Primary results of individual evaluation of two sensors
Gerontechnology
Life expectancy is nowadays increasing thanks to major improvements in medicine. Thus, modern societies are facing the great challenge to care after a fast growing population of elderly people. For that reason, researchers work on solutions to maintain, as long as possible, elderly persons safely in their own home, with efficient systems to detect abnormal trends and to launch alarms. This project deals with the development of indicators to detect the loss of autonomy. A flat was equipped with different sensors to classify the activities of daily living of the patient in his own environment. This paper describes the installation of the different sensors and the results of the preliminary individual evaluation of two of them (a sound and speech recognition system and an inertial/magnetic kinematic sensor). The first system classifies the sounds produced in the flat in eight classes and differentiates the normal sentences with the distress sentences uttered by the subject. The second analyzes the signal from the accelerometers and magnetometers to identify the posture and the level of activity. The algorithms were tested with two scenarios performed by ten subjects.
Data Fusion in Health Smart Home: Preliminary Individual Evaluation of Two Families of Sensors
Life expectancy is nowadays increasing thanks to major improvements in medicine. Thus, modern societies are facing the great challenge to care after a fast growing population of elderly people. For that reason, researchers work on solutions to maintain, as long as possible, elderly persons safely in their own home, with efficient systems to detect abnormal trends and to launch alarms. This project deals with the development of indicators to detect the loss of autonomy. A flat was equipped with different sensors to classify the activities of daily living of the patient in his own environment. This paper describes the installation of the different sensors and the results of the preliminary individual evaluation of two of them (a sound and speech recognition system and an inertial/magnetic kinematic sensor). The first system classifies the sounds produced in the flat in eight classes and differentiates the normal sentences with the distress sentences uttered by the subject. The second analyzes the signal from the accelerometers and magnetometers to identify the posture and the level of activity. The algorithms were tested with two scenarios performed by ten subjects.
Data Integration in Multimodal Home Care Surveillance and Communication System
This paper presents the data capture methodology and design of a home care system for medical-based surveillance and man-machine communication. The proposed system consists of the video-based subject positioning, monitoring of the heart and brain electrical activity and eye tracking. The multimodal data are automatically interpreted and translated to tokens representing subject’s status or command. The circadian repetitive status time series (behavioral patterns) are a background for learning of the subject’s habits and for automatic detection of unusual behavior or emergency. Due to mutual compatibility of methods and data redundancy, the use of unified status description vouches for high reliability of the recognition despite the use of simplified measurements methods. This surveillance system is designed for everyday use in home care, by disabled or elderly people.
Multi-modal platform for in-home healthcare monitoring (emutem)
… Conference on Health …, 2009
This paper describes a multimodal platform dedicated to in-home healthcare monitoring. This platform consists in three heterogeneous and complementary systems which are designed to provide a sense of safety and connectedness for those being monitored. In this article we present a detailed description of the multiple sensors used to remotely monitor elderly or a patient health. These are: a set of microphones suitably placed in the home, a wearable device and a set of infrared sensors. This platform is remotely used by the medical staff in order to help them to take the right decision about the patient and/or elderly situation. It has a couple of great advantages. First, its good acceptance by the end-users since it is less intrusive than other healthcare systems. Second, it is reliable and robust since it performs the fusion of outputs of three complementary healthcare systems.
Deployment of a smart telecare system to carry out an intelligent health monitoring at home
2016
Information and Communication Technologies together appropriate reasoning tools can add value to current telecare systems, including smart tele-monitoring solutions to enhance the capability for identifying risk situations at home. Cooperation between Home Area Networks (HAN) and Body Area Networks (BAN) at home can provide smart systems to support effective health solutions for ageing people living alone, improving service quality and security to the users and relatives. This paper details the development of a reasoning platform to monitor situations of the person at home, and react in risk situations that demanding care support of remote careers. The system integrates BAN and HAN with intelligent agents, whose behavior is defined by ontologies and rules. The system manages environmental and user data to proactively detect risk situations, and dynamically adjust its behavior to trigger the adequate problem solve mechanisms. A development methodology was also adapted to sustain know...
Sensor data fusion to determine wellness of an elderly in intelligent home monitoring environment
2012 IEEE I2MTC - International Instrumentation and Measurement Technology Conference, Proceedings, 2012
In this paper, we present a novel mechanism to foresee the well-being of elderly through monitoring and functional assessment of the daily activities with the help of sensor data fusion. Two wellness indices are defined to determine the wellness of the elderly in performing their daily activities. Home monitoring system is targeted for the elderly people to provide a safe, secured, less cost and privacy system in assessing the ability to perform basic behaviours. Developed system was tested at various elderly homes instead of test bed and the results are encouraging.