This project aims to better understand and improve how wearable health devices are used across healthcare, industry, and research. To begin, we are gathering insights from a wide range of experts, including engineers, healthcare professionals, and decision-makers from both academia and industry. By doing so, we hope to map out the current landscape of wearable technology and understand where the main challenges lie. A key part of our work is examining existing standards for wearable devices and identifying why many of these standards have not been widely adopted. Based on this, we are developing a new, open standard for raw wearable data. This standard is designed to make it easier for different groups—such as developers, clinicians, and researchers—to share and work with wearable data effectively.To support practical use, we are creating openly available data schemas (structured templates) that define how wearable data should be formatted. We are also building equivalent ROS 2 (Robot Operating System) messages, enabling wearable data to contribute to robotic applications in areas like healthcare and assisted living. Importantly, this standardization will also play a key role in the development of machine learning algorithms. By reducing the time needed for data cleaning and preparation, it will enable researchers to more easily apply and reuse models across a wide range of wearable devices, accelerating innovation and impact.