As mobile and wearable health technologies have evolved, constant monitoring of bio-signals from patients has become important for accurate diagnosis using mobile and remote health services. As the need for constant monitoring of bio-signals increases, the amount of biosignal data also increases, therefore an efficient compression method for specific bio-signals should be developed. In contrast to other types of signals, bio-signals contain important diagnostic information that should not be removed during compression. An effective compression algorithm for phonocardiogram (PCG) signals that contain important diagnostic information (murmur) is proposed. In this algorithm, the murmur is first estimated, then an adaptive thresholding scheme is applied in the wavelet domain to the normal portions and the murmur portions of PCGs depending on the murmur estimates during compression. Although other conventional compression methods result in substantial loss of murmur information, the proposed method is able to keep most of the murmur information in compressed PCGs.
All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering