1. Introduction to healthcare-oriented monitoring of persons1.1. Objectives of healthcare-oriented monitoring
1.2. Systems for healthcare-oriented monitoring
1.2.1. Monitoring techniques
1.2.2. Commercially available monitoring systems
1.3. Semantic and mathematical modelling of monitoring systems
1.3.1. Semantic modelling of monitoring systems
1.3.2. Mathematical modelling of monitoring systems
1.4. Overview of measurement-data processing in healthcare-oriented monitoring systems
1.4.1. Localisation of persons by means of impulse-radar sensors
1.4.2. Localisation of persons by means of depth sensors
1.4.3. Denoising and differentiation of persons' movement trajectories
1.4.4. Fusion and postprocessing of data from impulse-radar sensors and depth sensors
2. Localisation of persons by means of impulse-radar sensors - basic methods
2.1. Methods for extraction of signal from impulse-radar data
2.1.1. Mathematical model of impulse-radar data
2.1.2. Method based on arithmetic averaging
2.1.3. Method based on exponential averaging
2.1.4. Method based on singular-value decomposition
2.2. Methods for estimation of impulse-radar signal parameters
2.2.1. Mathematical model of impulse-radar data
2.2.2. Method based on time-domain template matching
2.2.3. Method based on frequency-domain template matching
2.2.4. Method based on maximum-envelope matching
2.3. Methods for estimation of two-dimensional trajectories
2.3.1. Methods for smoothing of distance trajectories 2.3.2. Methods for conversion of two distance trajectories into movement trajectory
2.4. Chapter conclusions
3. Localisation of persons by means of impulse-radar sensors - advanced methods
3.1. Principles of Bayesian inference
3.1.1. Bayesian methods for measurand reconstruction
3.1.2. Key role of a priori information
3.1.3. Recent applications of Bayesian inference in data processing
3.2. Extraction of signal from impulse-radar data
3.2.1. Method #1 3.2.2. Method #2
3.2.3. Method #3 3.3. &nb
