Wearables are widely used for mobile health monitoring, and photoplethysmography (PPG) is a key sensing modality for heart rate and related physiological measurements. However, public in-the-wild PPG datasets remain largely wrist-centric or limited to short, controlled studies, constraining research on emerging wearable form factors. We present Multi-site PPG, an in-the-wild physiological dataset collected from four custom-developed unobtrusive wearables: a smart earring, ring, watch, and necklace. Each device records green and infrared reflective PPG, 3-axis acceleration, and temperature with timestamps for cross-device alignment, while a Polar H10 chest strap provides reference electrocardiogram (ECG). Participants wore the devices for multiple days during daytime activities while continuing their normal routines. The dataset contains over 350 hours of raw data and 230-290 hours of modeling-ready 8-second windows per wearable. We benchmark heuristic, supervised, and self-supervised heart-rate estimation methods, showing substantial body-site differences: the best methods achieve mean absolute errors (MAEs) of 2.30 bpm on the earring, 5.13 bpm on the ring, 8.37 bpm on the watch, and 8.68 bpm on the necklace. We further analyze motion effects and evaluate multi-site and PPG-accelerometer fusion, demonstrating the dataset's value for robust physiological sensing across emerging wearable form factors.

翻译：可穿戴设备广泛应用于移动健康监测，其中光电容积描记术（PPG）是心率及相关生理测量的关键传感模态。然而，现有的野外PPG数据集大多局限于腕部采集或受控条件下的短期研究，限制了针对新兴可穿戴形态的研究。我们提出多部位PPG（Multi-site PPG）这一野外生理数据集，该数据集来自四种定制开发的无感可穿戴设备：智能耳环、戒指、手表和项链。每个设备记录绿色和红外反射式PPG、三轴加速度及温度数据，并附带时间戳以实现跨设备对齐，同时采用Polar H10胸带提供参考心电图（ECG）。参与者佩戴这些设备进行多日日间活动，保持正常生活作息。该数据集包含超过350小时的原始数据，以及每个可穿戴设备230-290小时经建模处理的8秒窗口数据。我们对启发式、监督式和自监督式心率估计方法进行了基准测试，揭示了显著的体表部位差异：最优方法在耳环上达到平均绝对误差（MAE）2.30 bpm、戒指5.13 bpm、手表8.37 bpm、项链8.68 bpm。我们进一步分析了运动干扰影响，并评估了多部位融合及PPG-加速度计融合方法，证明了该数据集在提升新兴可穿戴设备形态鲁棒生理感知方面的价值。