Physically Consistent Whole-Body Kinematics Assessment Based on an RGB-D Sensor. Application to Simple Rehabilitation Exercises.

This work proposes to improve the accuracy of joint angle estimates obtained from an RGB-D sensor. It is based on a constrained extended Kalman Filter that tracks inputted measured joint centers. Since the proposed approach uses a biomechanical model, it allows physically consistent constrained joint angles and constant segment lengths to be obtained.

A gait analysis method based on a depth camera for fall prevention.

This paper proposes a markerless system whose purpose is to help preventing falls of elderly people at home. To track human movements, the Microsoft Kinect camera is used which allows to acquire at the same time a RGB image and a depth image. Several articles show that the analysis of some gait parameters could allow fall risk assessment.

Human activities recognition with RGB-Depth camera using HMM.

Fall detection remains today an open issue for improving elderly people security. It is all the more pertinent today when more and more elderly people stay longer and longer at home. In this paper, we propose a method to detect fall using a system made up of RGB-Depth cameras.

Factored interval particle filtering for gait analysis.

Commercial gait analysis systems rely on wearable sensors. The goal of this study is to develop a low cost marker less human motion capture tool. Our method is based on the estimation of 3d movements using video streams and the projection of a 3d human body model.

A support system for ECG segmentation based on Hidden Markov Models.

Pharmaceutic studies require to analyze thousands of ECGs in order to evaluate the side effects of a new drug. In this paper we present a new support system based on the use of probabilistic models for automatic ECG segmentation. We used a bayesian HMM clustering algorithm to partition the training base, and we improved the method by using a multi-channel segmentation.

Dynamic optimization over infinite-time horizon: web-building strategy in an orb-weaving spider as a case study.

Dynamic state-dependent models have been widely developed since 1990s for solving questions in evolutionary ecology. Up to now, these models were mainly run over finite-time horizon. However, for many biological questions an infinite-time horizon perspective could be more appropriate, especially when the end of the modeled period is state- rather than time-dependent.

Automated medical diagnosis with fuzzy stochastic models: monitoring chronic diseases.

As the world population ages, the patients per physician ratio keeps on increasing. This is even more important in the domain of chronic pathologies where people are usually monitored for years and need regular consultations. To address this problem, we propose an automated system to monitor a patient population, detecting anomalies in instantaneous data and in their temporal evolution, so that it could alert physicians.