Background: Change of handwriting can be an early marker for severity of Parkinson's disease but suffers from poor sensitivity and specificity due to inter-subject variations. Aim: This study has investigated the groupdifference in the dynamic features during sketching of spiral between PD and control subjects with the aim of developing an accurate method for diagnosing PD patients. Method: Dynamic handwriting features were computed for 206 specimens collected from 62 Subjects (31 Parkinson's and 31 Controls). These were analyzed based on the severity of the disease to determine group-difference. Spearman rank correlation coefficient was computed to evaluate the strength of association for the different features. Results: Maximum area under ROC curve (AUC) using the dynamic features during different writing and spiral sketching tasks were in the range of 0.67 to 0.79. However, when angular features (φ and p_n) and count of direction inversion during sketching of the spiral were used, AUC improved to 0.933. Spearman correlation coefficient was highest for φ and pn. Conclusion: The angular features and count of direction inversion which can be obtained in real-time while sketching the Archimedean guided spiral on a digital tablet can be used for differentiating between Parkinson's and healthy cohort.