Human bowel sounds (BSs) contain rich information on gastrointestinal health status. Recently, the wearable BS monitoring systems has made it possible to record the human BSs in the long term. However, BSs collected by long-term monitoring devices usually contain various types of noises, which significantly affect the detection accuracy on BS events of interest. To filter out the noises in the long-term BS recordings, a U-Net convolutional neural network (CNN) based BS quality enhancement algorithm is proposed. The algorithm features a frequency-domain BS enhancement using U-Net to efficiently suppress the amplitude spectrum noises of BS segments. Experimental results on our BS dataset show that after enhancing with the proposed algorithm, the average SNR improvement of the sound segments is 28.72dB, which is the best among similar works. Moreover, after the enhancement, the accuracy of BS event detection using a threshold-based approach can reach 98.38%, which proves the effectiveness of the proposed enhancement algorithm. To the best of our knowledge, we are the first to utilize the CNN for BS quality enhancement.

As the demand for broadband wireless access services grows rapidly, much attention has been paid to integrated communication and broadcast networks (ICBN). ICBN can provide high-rate, on-demand, reliable data and multimedia services while in fast moving. In this paper, we introduce an ICBN system in which DMB-T broadcast network works as the forward link and wireless access networks are used for the return channel respectively. We first differentiate four types of services, including digital TV, video on demand, data download and Internet access. Then the system features are given. Next, we design the system architecture and the three subsystems, including the DMB-T broadcast network, the return channel and the terminal. With the introduction of subnetwork data unit (SNDU), the protocol to transmit data on DMB-T broadcast network is presented. We also stack the functions of the system into different layers in terms of four types of services, and introduce each of them, including signaling messages exchange and ARQ scheme, etc. Then the testbed is briefly introduced. Finally we draw the conclusion.