Handwritten signatures are generally considered a powerful biometric traits for personal verification. Recently, handwritten signatures have been also investigated for early diagnosis of neurodegenerative diseases. This paper presents a new approach for early diagnosis of neurodegenerative diseases by the analysis of handwritten dynamic signatures. For the purpose, the sigma-lognormal model was considered and dynamic parameters are extracted for signatures. Based on these parameters, the health condition of the signer is analysed in terms of Alzheimer disease. The approach is cheap and effective, therefore it can be considered as a very promising direction for further research.