Anthony Fleury | Ecole des Mines de Douai (original) (raw)

Papers by Anthony Fleury

Technological advances in signal processing and in circuits integration offer numerous perspectiv... more Technological advances in signal processing and in circuits integration offer numerous perspectives in telemedicine and telemonitoring. Considering the increase of life expectancy, accurate and reliable assessement of modification and/or deterioration in the health status of a person is needed. One possible indicator is the ";activity index"; of a person. To compute such an index, previous studies have used accelerometers. Although these sensors are appropriate for the detection of postural transitions (e.g. Sit To Stand and Stand To Sit), they do not allow to detect changes of direction of a walking individual insofar as such activity occurs in a constant gravitation field. Within this context, the purpose of the present work is to investigate whether magnetometers can be used to monitor the changes of direction of a person.

One of the greatest challenges in Ambient Assisted Living is to design health smart homes that an... more One of the greatest challenges in Ambient Assisted Living is to design health smart homes that anticipate the needs of its inhabitant while maintaining their safety and comfort. It is thus essential to ease the interaction with the smart home through systems that naturally react to voice command using microphones rather than tactile interfaces. However, efficient audio analysis in such noisy environment is a challenging task. In this paper, a real-time audio analysis system, the AuditHIS system, devoted to audio analysis in smart home environment is presented. AuditHIS has been tested thought three experiments carried out in a smart home that are detailed. The results show the difficulty of the task and serve as basis to discuss the stakes and the challenges of this promising technology in the domain of AAL.

Life expectancy is nowadays increasing thanks to major improvements in medicine. Thus, modern soc... more 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.

Physiotherapy Theory and Practice, 2008

Considering the important role of the cervical joint position sense on control of human posture a... more Considering the important role of the cervical joint position sense on control of human posture and locomotion, accurate and reliable evaluation of neck proprioceptive abilities appears of great importance. Although the cervicocephalic relocation test (CRT) to the neutral head position (NHP) usually is used for both research and clinical purposes, its test-retest reliability has not been clearly established 15 yet. The purpose of the present experiment was to 1) evaluate the test-retest reliability of the CRT to NHP and 2) to determine the number of trial recordings required to ensure reliable measurements. To this aim, 40 young healthy adults performed the CRT to NHP on two separate occasions. Ten trials were performed for each rotation side. Absolute and variable errors, processed along their horizontal, vertical, and global components, were used to assess the cervical joint repositioning accuracy and 20 consistency, respectively. Mean difference between test and retest with 95% confidence interval, intraclass correlation coefficient, and Bland and Altman graphs with limits of agreement were used as statistical methods for assessing test-retest reliability. Results show that the CRT to NHP when executed in its original form (i.e., 10 trials) has a fair to excellent reliability (ICC ranged from 0.52 to 0.81 and from 0.49 to 0.77, for absolute and variable errors, respectively); the test-retest reliability of 25 this test increases as the number of trials used to establish subject's repositioning errors increases; and using the mean of eight trials is sufficient to ensure fair to excellent reliability of the measurements (ICC ranged from 0.39 to 0.78 and from 0.44 to 0.78, for absolute and variable errors, respectively). 30 45

Fall detection of the elderly is a major public health problem. Thus it has generated a wide rang... more Fall detection of the elderly is a major public health problem. Thus it has generated a wide range of applied research and prompted the development of telemonitoring systems to enable the early diagnosis of fall conditions. This article is a survey of systems, algorithms and sensors, for the automatic early detection of the fall of elderly persons. It points out the difficulty to compare the performances of the different systems due to the lack of a common framework. It then proposes a procedure for this evaluation.

Based on several years of experiments, we propose a model of information systems for residential ... more Based on several years of experiments, we propose a model of information systems for residential healthcare, and technical guide to select available hard and software technologies. An implementation is described, based on Emails. The system is under experimentation within the framework of the French national project AILISA

Because of the aging of the population, low-cost solutions are required to help people with loss ... more Because of the aging of the population, low-cost solutions are required to help people with loss of autonomy staying at home rather than in public health centers. One solution is to assist human operators with smart information systems. In this case, position and physiologic sensors already give important information, but there are few studies about the utility of sound in patient's habitation. However, sound classification and speech recognition may greatly increase the versatility of such a system: this will be provided by detecting short sentences or words that could characterize a distress situation for the patient. Moreover, analysis and classification of sounds emitted in patient's habitation may be useful for patient's activity monitoring. In this paper, we present a global speech and sound recognition system that can be set-up in a flat. Eight microphones were placed in the Health Smart Home of Grenoble (named HIS, a real living flat of 47m2) to automatically analyze and classify different sounds and speech utterances (e.g.: normal or distress French sentences). Sounds are clustered in eight classes but this aspect is not discussed in this paper. For speech signals, an input utterance is recognized and a subsequent process classifies it in normal or distress, by analysing the presence of distress keywords. An experimental protocol was defined and then this system has been evaluated in uncontrolled conditions in which heterogeneous speakers were asked to utter predetermined sentences in the HIS. The results of this experiment, where ten subjects were involved, are presented. The Global Error Rate was 15.6%. Moreover, noise suppression techniques were incorporated in the speech and sound recognition system in order to suppress the noise emitted by known sources like TV or radio. An experimental protocol was defined and tested by four speakers in real conditions inside a room. Finally, we discuss the results of this experiment as a function of the noise source: speech or music.

By 2050, about a third of the French population will be over 65. To face this modification of the... more By 2050, about a third of the French population will be over 65. To face this modification of the population, the current studies of our laboratory focus on the monitoring of elderly people at home. This aims at detect, as early as possible, a loss of autonomy by objectivizing criterions such as the international ADL or the French AGGIR scales implementing automatic classification of the different activities of daily living. A health smart home is used to achieve this goal. This flat includes different sensors. The data from the various sensors were used to classify each temporal frame into one of the activities of daily living that has been previously learnt (seven activities: hygiene, toilets, eating, resting, sleeping, communication and dressing/undressing). This is done using support vector machines. We performed an experimentation with 13 young and healthy subjects to learn the model of activities and then we tested the classification algorithm (cross-validation) on real data.

Humans deeply modified their relationship to their housings during the past centuries. Once a she... more Humans deeply modified their relationship to their housings during the past centuries. Once a shelter where humans could find protection and have rest, the living place successfully evolved to become the midpoint of the family, the expression of own culture and nowadays a more self centered place where individuals develop their own personal aspirations and express their social position. With the introduction of communication technologies, humans may become nomads again with the ability to stay connected with others in any place at any time but, as a paradox, we can observe a wide movement for “cocooning”. Among all the services a living place can bring to inhabitants, we may list comfort, security, wellness and also health services. Thus a new living place is to be invented, becoming the “witness” of our breath, perceiving the inhabitants rhythms of activities, habits, tastes and wishes. Eventually, the “smart home” become the “Health Smart Home” to enable the follow up of physical and health status and meet the new concepts of “Aging in place” and “citizen health care”. We listed some of the research projects in Health Smart Home, which were launched worldwide to discover they are mostly based on very basic sensors and simple algorithms. We experienced our own Health Smart Home to prove that temporal analysis of data output from simple presence sensors is already worthwhile. We first produced “ambulatograms”, a temporal representation of the daily activity gathered from the presence sensors, and then discovered regular patterns of activities which we named “circadian activity rhythms (car)”, the direct relationship between night and day level of activities and also the information contained in periods of inactivity. We now concentrate on the automatic recognition of the daily Activities with multiple sensor fusions methods.

The present paper reports a study on the daily activity of elderly people in a hospital suite, wi... more The present paper reports a study on the daily activity of elderly people in a hospital suite, with presence infrared sensors. It is an attempt to produce parameters and indicators for the predictive analysis of the daily activity of fragile persons. A relationship is proposed between well being of the patient and the night and day activities alternation.

Improvements in medicine increase life expectancy and the number of elderly persons, but the inst... more Improvements in medicine increase life expectancy and the number of elderly persons, but the institutions able to welcome them are not sufficient. A lot of projects work on ways allowing elderly persons to stay at home. This article describes the implementation of a sound classification and speech recognition system equipping a real flat. This system has been evaluated in uncontrolled conditions for distinguishing normal sentences from distress ones; these sentences are uttered by heterogeneous speakers. The detected signals are first classified as sound and speech. The sounds are clustered in eight classes (object fall, doors clap, phone ringing, steps, dishes, doors lock, screams and glass breaking). As for speech signals, an input utterance (in French) is recognized and a subsequent process classifies it in normal or distress, by analysing the presence of distress key words. In the same way, some sound classes are related to a possible distress situation. An experimental protocol was defined and tested in real conditions inside the flat. Finally, we discuss the results of this experiment, where ten subjects were involved.

Recent Advances in Biomedical Engineering 2 monitored person's autonomy. Therefore, activity reco... more Recent Advances in Biomedical Engineering 2 monitored person's autonomy. Therefore, activity recognition is an active research area but, despite this, it has still not reached a satisfactory performance nor led to a standard methodology. One reason is the high number of flat configurations and available sensors (e.g., infra-red sensors, contact doors, video cameras, RFID tags, etc.) which may not provide the necessary information for a robust identification of ADL. Furthermore, to reduce the cost of such an equipment and to enable interaction (i.e., assistance) the chosen sensors should serve not only to monitor but also to provide feedback and to permit direct orders. One of the modalities of choice is the audio channel. Indeed, audio processing can give information about the different sounds in the home (e.g., object falling, washing machine spinning, door opening, foot step . . . ) but also about the sentences that have been uttered (e.g., distress situations, voice commands). Moreover, speaking is the most natural way for communication. A person, who cannot move after a fall but being concious has still the possibility to call for assistance while a remote controller may be unreachable. In this chapter, we present AUDITHISa system that performs real-time sound and speech analysis from eight microphone channels -and its evaluation in different settings and experimental conditions. Before presenting the system, some background about health smart home projects and the Habitat Intelligent pour la Santé of Grenoble is given in section 2. The related work in the domain of sound and speech processing in Smart Home is introduced in section 3. The architecture of the AUDITHIS system is then detailed in section 4. Two experimentations performed in the field to validate the detection of distress keywords and the noise suppression are then summarised in section 5. AUDITHIS has been used in conjunction with other sensors to identify seven Activities of Daily Living. To determine the usefulness of the audio information for ADL recognition, a method based on feature selection techniques is presented in section 6. The evaluation has been performed on data recorded in the Health Smart Home of Grenoble. Both data and evaluation are detailed in section 7. Finally, the limits and the challenges of the approach in light of the evaluation results are discussed in section 8.

Improvements in medicine increase life expectancy in the world and create a new bottleneck at the... more Improvements in medicine increase life expectancy in the world and create a new bottleneck at the entrance of specialized and equipped institutions. To allow elderly people to stay at home, researchers work on ways to monitor them in their own environment, with non-invasive sensors. To meet this goal, smart homes, equipped with lots of sensors, deliver information on the activities of the person and can help detect distress situations. In this paper, we present a global speech and sound recognition system that can be set-up in a flat. We placed eight microphones in the Health Smart Home of Grenoble (a real living flat of 47m 2 ) and we automatically analyze and sort out the different sounds recorded in the flat and the speech uttered (to detect normal or distress french sentences). We introduce the methods for the sound and speech recognition, the post-processing of the data and finally the experimental results obtained in real conditions in the flat.

Constant growing of the mean age of the population and bottleneck created at the entry of institu... more Constant growing of the mean age of the population and bottleneck created at the entry of institutions makes telemedicine for elderly people an actual challenge largely explored. It requires recognizing the behavior and actions of a person inside his home with non-intrusive sensors and to process data to check his evolution. This paper presents the results of the study of prior introduction, in Support Vector Machine, to improve this automatic recognition of Activities of Daily Living. From a set of activity performed in a smart home in Grenoble, we obtained models for seven activities of Daily Living and test the performances of this classification and the introduction of spatial and temporal priors. Finally, we discuss the different results.

IEEE Transactions on Information Technology in Biomedicine, 2010

By 2050, about a third of the French population will be over 65. Our laboratory's current researc... more By 2050, about a third of the French population will be over 65. Our laboratory's current research focuses on the monitoring of elderly people at home, to detect a loss of autonomy as early as possible. Our aim is to quantify criteria such as the international ADL or the French AGGIR scales, by automatically classifying the different Activities of Daily Living performed by the subject during the day. A Health Smart Home is used for this. Our Health Smart Home includes, in a real flat, Infra-Red Presence Sensors (location), door contacts (to control the use of some facilities), temperature and hygrometry sensor in the bathroom, and microphones (sound classification and speech recognition). A wearable kinematic sensor also informs on postural transitions (using pattern recognition) and walk periods (frequency analysis). This data collected from the various sensors, is then used to classify each temporal frame into one of the activities of daily living that was previously acquired (seven activities: hygiene, toilet use, eating, resting, sleeping, communication, and dressing/undressing). This is done using Support Vector Machines. We performed a one-hour experimentation with 13 young and healthy subjects to determine the models of the different activities and then we tested the classification algorithm (cross-validation) with real data.

Elderly people can be monitored at home to detect autonomy issues in their behavior. In addition ... more Elderly people can be monitored at home to detect autonomy issues in their behavior. In addition to the environmental sensors (presence and movements in a room, temperature in the flat, light, etc.), we developed an inertial and magnetic based central of sensors to monitor the activity of the person. This article presents a wavelet-based pattern recognition algorithm that work on the data of this central to detect the postural transitions occurring in the daily life. We constructed four patterns: (1) for stand to sit, (2) for sit to stand, (3) for stand to lying down and (4) for lying down to stand. With this, we are able to detect theses changes, and to infer (as we consider that the subject is stand-up when the sensor is turned on) its posture. We also have, with these sensors, an idea of the activity of the person in each frame of time (immobile, moving, etc.). To test this algorithm and verify that the patterns are independent of the subject, we asked fifteen people to reproduce a scenario and we present, in the last section of this article, the results obtained. Results of an experiment are also given to show a mean good classification rate of 70% for this method.

Physiotherapy Theory and Practice, 2008

IEEE Transactions on Information Technology in Biomedicine, 2010