A markup language mPCG-xml for mobile health care systems

The phonocardiography (PCG) provides a recording of the heart sounds. This information is diagnostically more important. Many disease of the heart cause changes in the heart sounds and additional murmurs before other signs and symptoms appear. Hence heart sound analysis by auscultation is the primary test conducted by physician to assess the condition of the heart. PCG signals or heart sounds have been studied extensively from past many years. Phonocardiography play an important role in cardiac care as they are non-invasive, non-expensive but accurate monitoring method for valves functioning, it is easily repeatable with no risk to the patient. However, heart diagnosis by auscultation requires high skills and experience of the listener [1]. Heart failure and stroke cause big burden on society due to their high costs of care, lower quality of life and premature death. PCG signal is one vital physiological signal that telemonitoring systems normally pay attention [2]. We proposed a telecardiogarphy system for PCG data access and a new XML schema designed specially for PCG data exchange and monitoring on mobile devices. We discussed major activities like acquisition, storage, transmission and interpretation of PCG signals over mobile devices. In this work we propose a system for remote healthcare using PCG signals and a XML based markup language for transmission and interpretation of PCG data over mobile WSN in telemedicine application. Prototype implementation of real-time PCG data access system using mPCG-xml to capture the patient data, tags and elements in an effective manner such that it is human readable and will enable the seamless integration of PCG data into remote healthcare architecture and applications[4]. The performance is evaluated with mobile computing XML end terminal (mobile phones, PDA etc), is experimented with PCG data. The audio application services of mobile networks were used to transfer the XML based PCG data to the experts over mobile networks, and found that improved decision making with low cost in terms of bandwidth and complexity.