Early childhood children feel music and lyrics of songs physically and emotionally. They often express their feeling by body movements to represent actions. Recently, the author has quantitatively analyzed the data of eye and body movements obtained during musical expression using a 3D motion capture system and eye tracking system to extract feature quantities contributing the classification discrimination of developmental degree of musical expression, and implemented to machine learning with fair forecasting accuracy (2023; 2024). Although considerable focus on combination of body and eye movements brought high classifying capacity with minimum feature quantities, comprehensive analysis suggested improvement margin by applying finger movement, consequently enabling holistic understanding and application in machine learning which objectively assesses developmental degree of music. In this study, the author focused on the hand-play songs analyzed by Meta gloves in 2024, 3-year-old, 4-year-old, and 5-year-old children participated in this measurement (n=86), and conducted a quantitative analysis focusing on the movements of the second finger to clarify their characteristics in early childhood. Finger movements were analyzed using the Meta gloves system connected to MVN as 3D motion capture system, and a three-way non-repeated analysis of variance was conducted on the calculated data for the second metacarpal, second proximal phalanx, second middle phalanx, and second distal phalanx with child facility factor, data type factor, and age factor. The author also investigated the moving average acceleration and the moving smoothness, which were characteristic of the second finger. As a result, similar trends were observed in the second metacarpal and second proximal phalanges, but it was found that in the second middle phalanges, age-related differences in the moving smoothness resulted in differences in song. The difference also occurred in the second distal phalanx. The moving average acceleration was most observed in the songs in which the movement of the image was actively performed. Overall the moving smoothness was most evident in movements showing a slow, steady beat, and was most likely to be observed in minor-key children's songs. It was found that in the second middle phalanges and the second distal phalanges at the fingertips, movements induced by lyrics were more pronounced when singing in time with the beat, regardless of the melody. Those above results will contribute music education in early childhood from the point to capture the characteristic movements to express images of lyrics of songs, to extract more effective feature quantities contributing to musical development.