Identification of new behavioral parameters to assess odorant hedonic value in humans: A naturalistic approach.

Background: When you smell an odorant, your first reaction will certainly be either I like it or I dislike it. This primary reaction is a reflection of what is called the "hedonic value" of the odor. Very often, this hedonic value dominates the olfactory percept, more than olfactory identification or intensity.

Noninvasive Continuous Blood Pressure Estimation From Pulse Transit Time: A Review of the Calibration Models.

Noninvasive continuous blood pressure estimation is a promising alternative to minimally invasive blood pressure measurement using cuff and invasive catheter measurement, because it opens the way to both long-term and continuous blood pressure monitoring in ecological situation. The most current estimation algorithm is based on pulse transit time measurement where at least two measured signals need to be acquired. From the pulse transit time values, it is possible to estimate the continuous blood pressure for each cardiac cycle.

Regional lung viscoelastic properties in supine and prone position in a porcine model of acute respiratory distress syndrome.

Regional viscoelastic properties of thoracic tissues in acute respiratory distress syndrome (ARDS) and their change with position and positive end-expiratory pressure (PEEP) are unknown. In an experimental porcine ARDS, dorsal and ventral lung (R,L and E,L) and chest wall (R,cw and E,cw) viscoelastic resistive (R) and elastic (E) parameters were measured at 20, 15, 10, and 5 cmHO PEEP in supine and prone position. E and R were obtained by fitting the decay of pressure after end-inspiratory occlusion to the equation: P (t) =R e, where t is the length of occlusion and τ time constant.

Neural processing of the reward value of pleasant odorants.

Pleasant odorants are represented in the posterior olfactory bulb (pOB) in mice. How does this hedonic information generate odor-motivated behaviors? Using optogenetics, we report here that stimulating the representation of pleasant odorants in a sensory structure, the pOB, can be rewarding, self-motivating, and is accompanied by ventral tegmental area activation. To explore the underlying neural circuitry downstream of the olfactory bulb (OB), we use 3D high-resolution imaging and optogenetics and determine that the pOB preferentially projects to the olfactory tubercle, whose increased activity is related to odorant attraction.

Detection of collaborative activity with Kinect depth cameras.

The health status of elderly subjects is highly correlated to their activities together with their social interactions. Thus, the long term monitoring in home of their health status, shall also address the analysis of collaborative activities. This paper proposes a preliminary approach of such a system which can detect the simultaneous presence of several subjects in a common area using Kinect depth cameras.

Estimation of walked distance using inertial sensors under real conditions.

This paper focuses on the comparison of the three most cited algorithms for calculation of walked distance in human, from accelerations measured by inertial sensors placed near the center of mass of human body. The algorithms were tested in real conditions during short walk travels, up to 10 meters, which are typical distances inside the flat. We used two different sensors-one included in a smart phone and our own developed sensor.

Analysis and experimental simulation of blood pressure signal distortions observed on intensive care patients monitored by a catheter in radial artery.

The follow-up of patients with hemodynamic instability in intensive care units most often requires blood pressure measurement using a fluid-filled catheter in the radial artery and a fluid-filled tubing connected to a pressure transducer. However, in this usual setup major distortions frequently occur that may alter the pressure signal. Underdamping and overdamping have been well described whereas other types of distortions, including attenuations and varied envelopes of pulse pressure, have been less studied.

Biomechanical analysis of a fall: velocities at impact.

There are numerous research works focusing on falls of the elderly, proposing various technologies for its detection; however, few research works attempted to describe the mechanical phenomenon itself. In this study, we analyzed the kine(ma)tics of human falls with a simplified biomechanical model of human segments. We present some results based on data found in the literature and in our own laboratory experiments, to conclude that fall velocities at impact can reach values from 3.

Characterization of a multi-user indoor positioning system based on low cost depth vision (Kinect) for monitoring human activity in a smart home.

An increasing number of systems use indoor positioning for many scenarios such as asset tracking, health care, games, manufacturing, logistics, shopping, and security. Many technologies are available and the use of depth cameras is becoming more and more attractive as this kind of device becomes affordable and easy to handle. This paper contributes to the effort of creating an indoor positioning system based on low cost depth cameras (Kinect).

Objective evaluation of body displacements during activities using the wearable inertial system ActimedARM.

This paper presents an algorithm for the objective assessment of the motion of a body during health-evaluation physical tests using our inertial sensor, namely the ActimedARM. With the orientation quaternions provided by the sensor and integrating twice the calibrated acceleration measurements, we are able to compute the displacement of the sensor worn by a patient. To validate our data we have made measurements with both our sensor and a reference optical system.

Ambient intelligence might support increased longevity.

Several technologies entered our homes to change our lives. First electricity brought light and comfort, now communication technologies are transforming our living place into a connected place allowing new services to be invented, comfort, security, wellness and health services. The ICTs in homes can now help prolonge our longevity.

ActimedARM - design of a wearable system to monitor daily actimetry.

We developed a low power kinematic sensor, ActimedARM, incorporating three-axis accelerometer and magnetometer, a microcontroller ARM3, a ZigBee wireless communication and μSD memory storage. With embedded algorithms it can detect in real time the postures of the subject. A preliminary assessment conducted on 12 subjects reached a 97% correct classification rate.

Characterization of physical activity in COPD patients: validation of a robust algorithm for actigraphic measurements in living situations.

We have developed robust embedded algorithms for the real-time classification of activity detected by our wearable inertial device. We collected 224 h of accelerometric signals from 28 subjects [22 suffering from chronic obstructive pulmonary disease (COPD)] to develop and then evaluate our algorithms. We describe the process for determining the most robust parameters of the algorithms.

Building an index of activity of inhabitants from their activity on the residential electrical power line.

In the framework of context awareness within the home, our team is currently assessing the unobtrusive detection of inhabitants' activity through the monitoring of their use and consumption of electricity. The objective is to develop a system for the remote monitoring of large populations of elderly people living independently at home. To be readily deployable on the field, such a system must be minimally intrusive both for the home environment and for the field professionals (paramedics and social workers) visiting the patients at home.

SVM-based multimodal classification of activities of daily living in Health Smart Homes: sensors, algorithms, and first experimental results.

By 2050, about one 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 activities of daily living (ADL) or the French Autonomie Gerontologie Groupes Iso-Ressources (AGGIR) scales, by automatically classifying the different ADL performed by the subject during the day.

Supervised classification of Activities of Daily Living in Health Smart Homes using SVM.

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.

Evaluation of the autonomic nervous system for fall detection.

Studies show that the proportion of elderly will reach 30% of the total population by 2050 in developed countries, such as France. The elderly live generally alone, thus many health problems related to age are under reported. Falling is one of these problems and several devices have been developed recently, based on accelerometers, in order to detect it and alert carers.

Health smart home for elders - a tool for automatic recognition of activities of daily living.

Elders live preferently in their own home, but with aging comes the loss of autonomy and associated risks. In order to help them live longer in safe conditions, we need a tool to automatically detect their loss of autonomy by assessing the degree of performance of activities of daily living. This article presents an approach enabling the activities recognition of an elder living alone in a home equipped with noninvasive sensors.

User-based motion sensing and fuzzy logic for automated fall detection in older adults.

More than one third of community-dwelling older adults and up to 60% of nursing home residents fall each year, with 10-15% of fallers sustaining a serious injury. Reliable automated fall detection can increase confidence in people with fear of falling, promote active safe living for older adults, and reduce complications from falls. The performance of a 2-stage fall detection algorithm using impact magnitudes and changes in trunk angles derived from user-based motion sensors was evaluated under laboratory conditions.

Health smart home: towards an assistant tool for automatic assessment of the dependence of elders.

In order to help elders living alone to age in place independently and safely, it can be useful to have an assistant tool that can automatically assess their dependence and issue an alert if there is any loss of autonomy. The dependence can be assessed by the degree of performance, by the elders, of activities of daily living. This article presents an approach enabling the activity recognition for an elder living alone in a Health Smart Home equipped with noninvasive sensors.

Walk detection with a kinematic sensor: frequency and wavelet comparison.

This study is included in the framework of Health Smart Homes which monitor some physiological or not physiological parameters of elderly people living independently at home. In this study we will focus on the walk detection. Walk activity is one parameter to evaluate the health of patient.

Classification of daily physical activities from a single kinematic sensor.

This work was conducted in TIMC laboratory to develop methods able to monitor physical activities. In the framework of Health Smart Home, the purpose is to maintain and supervise elderly or fragile people at home. Activity and autonomy levels are important criteria to evaluate the health of the patient.

Preliminary results on the study of smart wearable antennas.

We report a study on the design, simulation and evaluation of wearable antennas. This work open the way to continuous and automatic monitoring with wearable devices.

A review of approaches to mobility telemonitoring of the elderly in their living environment.

Rapid technological advances have prompted the development of a wide range of telemonitoring systems to enable the prevention, early diagnosis and management, of chronic conditions. Remote monitoring can reduce the amount of recurring admissions to hospital, facilitate more efficient clinical visits with objective results, and may reduce the length of a hospital stay for individuals who are living at home. Telemonitoring can also be applied on a long-term basis to elderly persons to detect gradual deterioration in their health status, which may imply a reduction in their ability to live independently.