BSMonitor: Noise-Resistant Bowel Sound Monitoring via Earphones

Bowel sound (BS) is an important physiological signal of the human body, which is also an objective reflection of gastrointestinal motility. However, BS has characteristics of weak signal, strong noise, and randomicity, which bring great challenges to the daily detection of BS. In this paper, we propose BSMonitor, the first BS monitoring system with strong noise-resistant capability via earphones. BSMonitor uses one earphone attached to the abdomen to collect BS signals and the other earphone worn in the ear to collect external noises and internal noises. After eliminating the noises through the Kalman filter and band-pass filter, the signal containing BS is separated via the empirical mode decomposition. Then BSMonitor extracts MFCC features of BS signals and applies a carefully-designed LSTM network to perform highly-accurate BS detection. Finally, an alert mechanism calculates the frequency and duration of detected BS and compares with the normal values to alert users. Furthermore, to increase the amount and diversity of training data, we introduce a data augmentation method, which can further improve the accuracy and generalization of BSMonitor. Through extensive experiments with 18 volunteers, we find that BSMonitor not only achieves high accuracy of BS detection but also has strong generalization across different users and environments. Particularly, BSMonitor achieves accuracy up to 98.73% and 94.56% in the benchmark experiments and the cross experiments, respectively.