Smart sound sensor to detect the number of people in a room

International audienceAmbient sound monitoring is a widely used strategy to follow older adults, which could help them achieve healthy ageing with comfort and security. In a previous work, we have already developed a smart audio sensor able to recognize everyday life sounds in order to detect activities of daily living (ADL) and distress situations. In this paper, we propose to add a new functionality by analyzing the speech flow to detect the number of people in a room. The proposed algorithms are based on speaker diarization methods. This information can be used to better detect activities of daily life but also to know when the person is home alone. This functionality can also offer more comfort through light, heating and air conditioning adaptation to the number of people in an environment

HABITAT TELEMONITORING SYSTEM BASED ON THE SOUND SURVEILLANCE

International audienceThis paper presents a telemonitoring system in an habitat equipped with physiological sensors, position encoders of the person, and microphones. The originality of our approach consists in replacing the video camera monitoring, not well accepted by the patients, with microphones acquiring the sounds. The sounds are analyzed and not stored in order to maintain the person privacy. We present the entire telemonitoring system which makes the data fusion between medical information and sound information and particulary the sound processing algorithms to detect a distress situation. The first step of sound processing is the sound event detection in a noisy everyday life environment. Sound event detection is necessary to extract the significant sounds before initiating the classification step. Sound classification system and its performances are presented in this paper, too. Introduction Medical monitoring is more and more frequently used in order to reduce hospitalisation costs. There are many researches in telemedicine, but few of them are sound based. In this paper, we present a medical telemonitoring system with a smart audio sensor. The system we work on is designed for the surveillance of the elderly, convalescent persons or pregnant women [1]. Its main goal is to detect serious accidents as falls or faintness at any place in the apartment. It was noted that the elderly had difficulties in accepting the video camera monitoring, considering it a violation of their privacy. Thus, the originality of our approach consists in replacing the video camera by a system of multichannel sound acquisition. The system analyzes in real time the sound environment of the apartment and detects the abnormal sounds (falls of objects or patient) and the calls for help, that could indicate a distress situation in the habitat. Again, to respect privacy, no continuous recording or storage of the sound is made, since only the last 5s of the audio signal are kept in a buffer and sent to the alarm monitor if a sound event is detected. The sound information extractio

COMMUNICATION BETWEEN A MULTICHANNEL AUDIO ACQUISITION AND AN INFORMATION SYSTEM IN A HEALTH SMART HOME FOR DATA FUSION

International audienceThe Health Integrated Smart Home Information System (HIS²) has been developed in the TIMC laboratory for the remote monitoring of the health status of an elderly person during daily life at home. This aims at improving patients' life conditions and at reducing the costs of the long hospitalization. The design of this system is based on a CAN network linked to volumetric, physiological and environment sensors. In addition, a collaboration between the TIMC and the CLIPS laboratories permitted to replace the video camera, not well accepted by the patients by a system based on a multichannel Sound Acquisition. The coupling between both systems will enable to detect if the person is in a situation of distress or not. Both systems locally processe in real time the incoming data and communicate using a CAN network to display the health status. This article describes the system architecture of both systems, practical solutions for their communication and the evaluation results

Well-being and -ageing with chronical disease: the BV2 project

International audienceThe BV2 project aims to propose a monitoring system for wellbeing but also well-aging working on the prevention, detection and monitoring using a System of the Systems (SoS) approach. The project partner already uses the IoT technologies and the BV2 platform will combine the different developed systems. The main originality of the project consist s in the development of a virtual platform by combining the existing system

Détection et classification des sons : application aux sons de la vie courante et à la parole

- Depuis quelques années se développe le concept général d'espace perceptif (salle intelligente) qui répond de diverses façons aux besoins, demandes, attentes des acteurs humains. Un système d'extraction de l'information du son à trois étapes est proposé. La première étape, permet la détection et l'extraction des sons du flux sonore continu. L'algorithme de détection proposé est basé sur la transformée en ondelettes, il permet de s'affranchir du bruit et d'obtenir une bonne résolution temporelle. La deuxième étape utilise un mélange de distributions de Gauss (GMM) pour faire la classification du signal sonore entre parole et sons et aiguiller le signal sur le processus adapté : reconnaissance de la parole (non traitée dans l'article) ou classification des sons. La troisième étape, celle de classification des sons de la vie courante, est aussi réalisée avec un système à base de GMM. Les paramètres acoustiques sont étudiés étant donné qu'ils ont une influence essentielle sur le système de classification ; par ailleurs, de nouveaux paramètres issus de la transformée en ondelettes sont proposés. Chaque étape de l'étude est validée au moyen d'un corpus spécifique

Evaluation of a Real-Time Voice Order Recognition System from Multiple Audio Channels in a Home

International audienceThe SWEET-HOME project aims at providing audio-based interaction technology that lets the user have full control over their home environment, at detecting distress situations and at easing the social inclusion of the elderly and frail population. This paper presents an overview of the project focusing on the implemented techniques for speech and sound recognition as context-aware decision making with uncertainty. A user experiment in a smart home demonstrates the interest of this audio-based technology

Home monitoring for frailty detection through sound and speaker diarization analysis

As the French, European and worldwide populations are aging, there is a strong interest for new systems that guarantee a reliable and privacy preserving home monitoring for frailty prevention. This work is a part of a global environmental audio analysis system which aims to help identification of Activities of Daily Life (ADL) through human and everyday life sounds recognition, speech presence and number of speakers detection. The focus is made on the number of speakers detection. In this article, we present how recent advances in sound processing and speaker diarization can improve the existing embedded systems. We study the performances of two new methods and discuss the benefits of DNN based approaches which improve performances by about 100%.Comment: JETSAN, Jun 2023, Aubervilliers & Paris, Franc

Sound environment analysis in smart home

International audienceThis study aims at providing audio-based interaction technology that lets the users have full control over their home environment, at detecting distress situations and at easing the social inclusion of the elderly and frail population. The paper presents the sound and speech analysis system evaluated thanks to a corpus of data acquired in a real smart home environment. The 4 steps of analysis are signal detection, speech/sound discrimination, sound classification and speech recognition. The results are presented for each step and globally. The very first experiments show promising results be it for the modules evaluated independently or for the whole system

A Fuzzy Logic Approach for Remote Healthcare Monitoring by Learning and Recognizing Human Activities of Daily Living

Systems analysis & desig

Chapter A Fuzzy Logic Approach for Remote Healthcare Monitoring by Learning and Recognizing Human Activities of Daily Living

Systems analysis & desig