A Novel Real-Time Intelligent Axis Selection Based on Body Positions with Simultaneous Cardiac and Respiratory Signal Using an Edge Wearable for Smart Health Applications

Real-time simultaneous monitoring of cardiac and respiratory signals in wearable systems remains challenging due to motion artifacts under varying body postures. This paper proposes an edge wearable integrated with novel methods to acquire and process cardiac and respiratory signals simultaneously from the chest. For respiration monitoring, the system captures chest motion using an IMU and applies dynamic filtering with real-time axis selection in a custom mobile application. It automatically selects the best respiratory axis from six IMU vectors: x, y, z, xy, yz, and zx, improving robustness across body postures and device placements. The proposed system can also capture and process electrocardiogram (ECG) data simultaneously for cardiac monitoring. Cardiac and respiration data were taken from eight healthy subjects, including males and females, followed by five protocols. The overall mean absolute error (MAE) for eight subjects is found to be 0.64 breath per minute (BrPM) after validation by a commercial sensor. In real time, the wearable continuously provides ECG and breathing signal streaming, ECG beat detection, and cardiac and breathing rates with an overall latency of 13.8 ms. The results indicate that the system can monitor the cardio-respiratory signals in real time under static and light-movement conditions.