Khalida Azudin, Kok Beng Gan, Rosmina Jaafar, Mahmoud Muhanad Fadhel, Wallace Wong Ming Yip, Kow Ping, Mohd Hasni Jaafar, Mohd Shawal Faizal Mohammad, Kok Swee Sim
Space missions require reliable and safe physiological monitoring systems, as well as capable of continuous operation, as microgravity affects cardiovascular function and heart rhythm stability. This study develops and validates an intelligent in-ear photoplethysmography (PPG) system for continuous cardiac rhythm monitoring and real-time arrhythmia detection. A total of 2,926 PPG signal segments were collected, covering both normal and arrhythmic conditions. Signals were recorded at 75 Hz and upsampled to 256 Hz, then preprocessed using a 0.56 Hz Butterworth filter, artifact detection, and segmentation into 2,560 data points (≈10 s). A hybrid ResNet–LSTM–Attention model was developed to extract morphological and temporal features, while performance was evaluated using 5-fold crossvalidation. The results demonstrated consistent and robust performance with accuracy 0.7138 ± 0.1115, AUC 0.8078 ± 0.0492, and F1-Score 0.7198 ± 0.0788, confirming the model’s capability to detect cardiac rhythm abnormalities from in-ear PPG signals. These findings highlight the potential of this technology as a continuous cardiovascular monitoring platform, suitable for integration into wearable devices and mobile health applications, as well as for use in extreme environments such as space, where conventional electrocardiography is less practical.