Sigma Lognormal

The sigma-lognormal model is a statistical framework used to analyze complex, dynamic processes characterized by multiplicative variations, often exhibiting lognormal distributions. Current research focuses on applying this model to diverse fields, including handwriting analysis for Alzheimer's diagnosis, signature verification through 3D on-air signature synthesis, and modeling speech kinematics. This versatile model offers improved accuracy and efficiency in various applications by capturing the inherent variability and non-linearity of the underlying systems, leading to advancements in fields ranging from healthcare to computer vision.