In the fast-paced world of digital and communication technology, the Tactile Internet and the Metaverse have emerged as revolutionary frontiers, aiming to revolutionize human-human and human-machine interactions. These innovative concepts go beyond traditional modes of communication, by incorporating haptic input and feedback to contribute to a more immersive and realistic sense of presence in real, digitized or remote environments. It should be imperative that these advancements are inclusive by ensuring equal access, opportunities and treatment of individuals, by embracing diversity and promoting fairness. This research focuses on open access age-representative data. We have created the CeTI-Age-Kinematic-Hand database, which contains naturalistic hand movements of 63 different participants across the adult lifespan. This comprehensive database provides valuable insights into intra-individual and inter-individual variability in hand kinematics, with a specific focus on age-related differences. By doing so, we strove to foster a deeper understanding of intra-individual variations, with a particular emphasis on age-linked differences. Additionally, individual static 3D hand models were generated, offering a holistic perspective on hand movements. By incorporating hand models and anthropometric data, researchers can gain insights into hand kinematics, enhance classification accuracy, develop kinematic models, and inform hand rehabilitation and exoskeleton design.

To develop the CeTI-Age-Kinematic-Hand database, we recorded hand kinematics using wearable resistive bend sensors. This approach allowed us to capture precise and detailed data on hand movements. Sixty-three participants, ranging in age from 20 to 80 years, each performed six repetitions of 40 diverse naturalistic hand movements at their individual paces. The inclusion of a wide age range ensures that the database represents the natural variations in hand movements across the adult lifespan. In addition to the kinematic data, we generated individual static 3D hand models, providing researchers and developers with a comprehensive understanding of hand movements.

We have also included instructional videos used during the data acquisition process, offering transparency and valuable context for the recorded movements. This comprehensive collection of data, made possible through open science, provides researchers and developers with a valuable resource to deepen their understanding of hand kinematics, develop age-inclusive applications, ergonomically designed hand-held devices or datagloves and forensic anthropology. Furthermore, the database holds immense potential in advancing machine-learning approaches for hand kinematic modeling and movement prediction.
In our perspective, open science plays a pivotal role in propelling the advancement of artificial intelligence (AI) by fostering transparency and collaboration. By openly sharing a database of kinematic hand movements, researchers and developers gain access to a diverse range of data, enabling them to analyze and utilize it. This collective sharing of information empowers scientists and engineers to work together in tackling complex problems and enhancing AI algorithms. Moreover, this open approach sparks innovation, expedites progress, and ensures the ethical development of AI technology with a comprehensive understanding of the intricacies of human hand movements.

By leveraging the power of transparency and collaboration, the CeTI-Age-Kinematic-Hand database contributes to the broader goal of creating an inclusive Tactile Internet and enhancing human-machine interactions. Researchers and developers can harness the data within this database to gain valuable insights into hand movements, fostering the development of more sophisticated and effective AI systems to support human-machine, human-human interactions in immersive and remote environments. The database can be accessed here: (https://doi.org/10.6084/m9.figshare.c.6688871). For more details, please refer to the article (Coming in handy: CeTI-Age — A comprehensive database of kinematic hand movements across the lifespan | Scientific Data (nature.com)).

Funded by the German Research Foundation (DFG, Deutsche Forschungsgemeinschaft) as part of Germany's Excellence Strategy -- EXC 2050/1 -- Project ID 390696704 -- Cluster of Excellence ``Centre for Tactile Internet with Human-in-the-Loop" (CeTI) of Technische Universität Dresden. This project was also partly supported by the Bundesministerium für Bildung und Forschung (BMBF, Federal Ministry of Education and Research) and DAAD (German Academic Exchange Service) in project 57616814 (SECAI, School of Embedded and Composite AI).