High blood pressure (HBP) is at the root of many cardiovascular diseases, causing millions of deaths every year worldwide. Continuous monitoring of blood pressure (BP) is necessary, not only to prevent cardiovascular disease, but also to help those already affected. While many methods of blood pressure measurement exist at present, they present two major inconve-niences, these methods do not allow continuous measurement and they are frequently very invasive. In this paper, we present an alternative method to measure systolic and diastolic blood (SBP and DBP) pressure values with photoplethysmographic (PPG) signals using a deep learning architecture. PPG signals come from MIMIC II, a noisy and unprocessed database. Using a ResNet neural network coupled with LSTM layers, we succeeded in predicting SBP and DBP values, with an RMSE of 8.96 mmHg.

This paper presents a new variation of the packing problem, where the dimensions of the objects belong to intervals instead of being fixed. This problem is solved with linear optimization and applied to the automated computation of a dwelling layout. The proposed layout, besides meeting some elementary building rules, also takes into account wishes expressed by the future occupant.

We present and investigate, in the first part of this paper, a set of published works that may be employed to remotely quantify mental stress based on physiological signals by non-contact means. Several techniques can be used to this purpose, thermal imaging being currently the most advanced in our knowledge. Webcams correspond to a ubiquitous and to the most accessible techniques in the particular purpose of mental stress detection. After all these theoretical reminders, we present a pilot study based on a new framework that was developed to detect mental workload changes using video frames obtained from a low-cost webcam. To induce stress, we have employed a computerized Stroop color word test on twelve subjects. The results offer further support for the applicability of mental workload detection by remote and low-cost means, providing an alternative to conventional contact techniques.

In this paper, we focus our attention on the development of a virtual reality exposure system (VRE) to induce anxiety to phobic people and on a strategy for recognizing it. We describe a short term anxiety detection from blood volume pulse (BVP) measurement, we detail data collection, feature extraction and classification. We propose a model of anxiety detection using support vector machines (SVM) and evaluate it on the collected data. Results show that our model detects anxiety with a good accuracy. This study aims to support the psychologist in social anxiety diagnosis.

The ability to recognize emotion is one of the hallmarks of emotion intelligence. This paper proposed to recognize emotion using physiological signals obtained from multiple subjects. IAPS images were used to elicit target emotions. Five physiological signals: Blood volume pulse (BVP), Electromyography (EMG), Skin Conductance (SC), Skin Temperature (SKT) and Respiration (RESP) were selected to extract 30 features for recognition. Two pattern classification methods, Fisher discriminant and SVM method are used and compared for emotional state classification. The experimental results indicate that the proposed method provides very stable and successful emotional classification performance as 92% over six emotional states.

In this paper, we present a detection and tracking feature points algorithm in real time camera input environment. To trace and extract a face image, we use a modified face detector based on the Haar-like features. For feature points detection, we use good features to track of Shi and Thomasi. In order to track the facial feature points, pyramidal Lucas-Kanade feature tracker algorithm is used. Results on the real time indicate that the proposed algorithm can accurately extract facial features points.

We present in this paper a method for distance computing in an encoded environment. The proposed method allows to find the closest point between a general polygonal shape obstacle (a robot) and some complex general shapes objects (the obstacles). Due to the discretized aspect of the model, the algorithm complexity does not depend on the obstacles number and shape. In order to have a preprocessed model, the multivalue number coding has been used. Such a distance computing can be used in mobile robotics field as a basic tool in local path planning algorithms or in more sophisticated general paths planners. All the proposed algorithms follow a general schema which makes their implementation easier in an oriented object language, using a series of class.

Proposes to exploit an uncertain man-made representation of an indoor environment. The problem of uncertainties valuation is solved by a human behavior modeling which consists in using proximity relations between the geometrical primitives of the objects. The multivalue numbers formalism provides an efficient structure in order to model the a priori representation. The dynamic aspect of such a model makes real-time alterations of the map components possible. A Kalman filter used in order to match ultrasonic data with the preprocessed map while navigating. This process allows the map to be incrementally improved while preserving the original shape of the obstacles.

The VAHM project constitutes a research and development project aimed at automating an electric wheelchair for the disabled. The aim consists in delegating the control of some low-level functionalities to the wheelchair during the motion in order to allow the person to be free of the driving constraints that may be painful for some handicapped persons. The authors describe the hardware and software structure chosen to perform the intelligent mobility functions in association with a disabled person.>

An application of the multivalue codes representing the free configuration space of a mobile robot with purely translational and rotational motions is described. Starting with a binary array, the multivalue codes define a collection of cells representing free space rectangles (in 2-D) and include the location and the size. The authors propose the use of multivalue coding to represent the 2-D free environment to which a third dimension is added to code the intervals of validation according to the rotation angle of the robot.>