The widespread adoption of wearable devices such as smartwatches and fitness trackers has fueled the demand for reliable physiological and movement data collection tools. However, challenges such as limited access to large, high-quality public datasets and a lack of control over data collection conditions hinder the development of robust algorithms. This work presents Colepp, an open-source, cross-platform tool designed to collect and synchronize data from multiple wearable devices, including heart rate (via ECG and PPG) and motion signals (accelerometer and gyroscope). The system integrates a smartphone as a central hub, receiving data from a Polar H10 chest strap and a Wear OS smartwatch, and exporting synchronized datasets in CSV format. Through a custom synchronization protocol and user-friendly interface, Colepp facilitates the generation of customizable, real-world datasets suitable for applications such as human activity recognition and heart rate estimation. A use case shows the effectiveness of the tool in producing consistent and synchronized signals.

翻译：智能手表和健身追踪器等可穿戴设备的广泛普及，推动了对可靠生理与运动数据采集工具的需求。然而，诸如难以获取大规模高质量公共数据集、以及对数据采集条件缺乏控制等挑战，阻碍了鲁棒算法的开发。本研究提出了Colepp，一个开源的跨平台工具，旨在收集并同步来自多个可穿戴设备的数据，包括心率（通过ECG和PPG）和运动信号（加速度计和陀螺仪）。该系统集成了智能手机作为中央枢纽，接收来自Polar H10胸带和Wear OS智能手表的数据，并以CSV格式导出同步数据集。通过自定义的同步协议和用户友好的界面，Colepp促进了适用于人类活动识别和心率估计等应用的可定制真实数据集的生成。一个用例展示了该工具在生成一致且同步信号方面的有效性。