A Dimensionally Reduced Clustering Methodology for Heterogeneous Occupational Medicine Data Mining.

Clustering is a set of techniques of the statistical learning aimed at finding structures of heterogeneous partitions grouping homogenous data called clusters. There are several fields in which clustering was successfully applied, such as medicine, biology, finance, economics, etc. In this paper, we introduce the notion of clustering in multifactorial data analysis problems.

'Do Well B.': Design Of WELL Being monitoring systems. A study protocol for the application in autism.

Introduction: Individuals with autism spectrum disorder (ASD) have difficulties in communication and social interaction resulting from atypical perceptual and cognitive information processing, leading to an accumulation of anxiety. Extreme overloading experienced internally may not be externally visible. Identifying stressful situations at an early stage may avoid socially problematic behaviour from occurring, such as self-injurious behaviour.

Heart rate regulation processed through wavelet analysis and change detection: some case studies.

Heart rate variability (HRV) is an indicator of the regulation of the heart, see Task Force (Circulation 93(5):1043-1065, 1996). This study compares the regulation of the heart in two cases of healthy subjects within real life situations: Marathon runners and shift workers. After an update on the state of the art on HRV processing, we specify our probabilistic model: We choose modeling heartbeat series by locally stationary Gaussian process (Dahlhaus in Ann Stat 25, 1997).