This dataset provides valuable insights into hand gestures and their associated measurements. Hand gestures play a significant role in human communication, and understanding their patterns and characteristics can be enabled various applications, such as gesture recognition systems, sign language interpretation, and human-computer interaction. This dataset was carefully collected by a specialist who captured snapshots of individuals making different hand gestures and measured specific distances between the fingers and the palm. The dataset offers a comprehensive view of these measurements, allowing for further analysis and exploration of the relationships between different gestures and their corresponding hand measurements.The dataset's potential applications are wide-ranging. For instance, it can be used to develop gesture recognition systems that can identify and interpret hand movements accurately. By training machine learning models on this dataset, it is possible to create algorithms capable of recognizing specific hand gestures based on the measured distances. This can enable intuitive human-machine interaction and interfacing, particularly in domains such as virtual reality, augmented reality, and smart devices. Moreover, researchers interested in the biomechanics of hand movements or exploring the cultural significance of specific gestures can leverage this dataset to gain insights into the physical aspects of hand gestures and their variations across different individuals.