A graphical interface for consolidating data from multiple wearable devices: concordance and the effect of sensor positioning relative to the smartwatch

Abstract Currently, smartwatches are widely used to record heart rate (HR) and heart rate variability (HRV), but two obstacles limit their use: closed ecosystems and signal degradation during daily activities. Consolidating data from multiple devices requires asynchronous export, making beat-for-beat comparison impractical. To solve this, we developed a centralized graphical interface that ingests, chronologically orders, and displays raw streams from three Samsung Galaxy Watch 4s simultaneously, recording independent columns with timestamps, signaling anomalies in real time, and exporting a consolidated table. The platform demonstrated high stability (50 Hz sampling, 19.1 ± 18.5 ms latency, 99.8% integrity, zero connection loss, and 1.2% false alarms). We used the system to examine the consistency of heart rate intervals in volunteers instrumented at the right wrist (S1), left wrist (S2), and left ankle (S3) during 19-minute sessions (treadmill walking at 1.5 km/h with supine or seated resting postures). Wrist data showed a normal distribution, while ankle data deviated (Shapiro-Wilk, p = 0.028), justifying the use of the Friedman test. Monitoring identified distinct sources of artifacts, such as attenuation at the ankle and flow occlusion at the left wrist by a sphygmomanometer. RR intervals were processed in Python (PyBios) to obtain the RMSSD. The main contribution is not a smoothing method, but an acquisition layer that makes multi-site wearable data recording auditable at the time of capture, converting fragmented exports into a single synchronized and traceable record.