###### Abstract
While initially developed for sports performance enhancement, biomechanical feedback has also found applications in physical rehabilitation, helping patients regain mobility and correct movement patterns [1; 2]. Biomechanical feedback systems are implemented with different types of devices, from professional high-precision motion capture systems to commercial mass products such as wristbands. While the former provide detailed data on the activity or movement of a specific body part, they are also expensive and require trained professionals and an adapted environment for use. The latter, on the other hand, are primarily intended for recreational use and generally only provide simple statistical data on activity. In light of the above, it is clear that we need devices that fill the gap between the two extremes. These are usually devices that are designed for a specific sport, activity, or even just a single movement. Most of these devices are wearable devices that do not interfere with activity and have wireless connectivity. These devices are worn on the body as accessories, attachments, or implants and encompass a broad spectrum--from smart devices like smartphones and smartwatches to small accessories such as smart eyewear, and specialized sensor devices or intelligent sports equipment [3]. The commercially available devices mentioned are only intended for a set of predefined activities and cannot be adapted to specific requirements, e.g., to measure a specific activity parameter. Furthermore, they usually do not offer the possibility to view the raw data and therefore do not allow in-depth analysis. Researchers in the field of biomechanical feedback systems are therefore developing their own wearable devices that enable the capture and analysis of specific activities and parameters. Our own experience in this research has led us to realize that we can meet a variety of biomechanical feedback system requirements with the same or similar devices, but with different settings and under different conditions. Therefore, there is a need to develop a solution for the acquisition and wireless streaming of sensor data with wearable devices that can cover a variety of applications, which is the main objective of this work. A crucial aspect of biomechanical feedback systems is the timing of feedback delivery [1], which determines when corrective information is provided to the user. Feedback can be terminal (delivered after task completion), concurrent (provided in real time during the movement), or cyclic (offered immediately after completing a repeating motion cycle). Wearable devices play a key role in enabling real-time feedback, as they allow unobtrusive monitoring and wireless communication with processing units. Comprehensive overviews of wearable devices and their associated challenges are provided in [4; 5], while their technical challenges and limitations are explored in [1; 6; 7]. When evaluating wearable sensor devices for real-time biomechanical feedback (RTBF), our focus was primarily on kinematic sensors, such as inertial measurement units (IMUs) [8]. They are widely used in wearable technologies for performance enhancement and risk assessment in various fields, including sports, industry [9], and rehabilitation [10]. IMUs employ gyroscopes and accelerometers to capture body motion, and are sometimes used to supplement marker-based optical systems for monitoring high-speed motion in sports [11]. Other types of sensors, such as piezoelectric [12] or triboelectric [13], are available for measuring human activities, body processes, and states, but they do not fall into the scope of this work. A promising future development is the integration of kinematic sensors in textiles, which will significantly improve wearability in sports and rehabilitation [14]. Real-time biomechanical feedback applications for analysing human motion require strict time guarantees, especially when high sampling frequencies are required, often exceeding 100 or 200 Hz [15].