The proposed project?s objective is to develop a system level framework for patient monitoring. This framework is intended to allow the interoperability of various patient monitoring devices; data preprocessing and fusion to detect the data inconsistencies and determine session and data prioritization; and bandwidth-adaptive data and video transmission driven by real-time prioritization. The proposed research will lead to the evolution of protocols that can be used for providing interoperability among various physiological measurement devices/sensors, and will have applications in numerous healthcare domains such as home healthcare, post-operative care, preventive care, adult care and nursing homes.
The outcomes of the proposed work have the potential to impact the medical sciences, healthcare and computer science, enabling an information rich environment with which medical care and outcomes may be significantly improving. The work is supported by the Industry Advisory Board as well as an individual industry member of the center and has the potential to extend the center?s portfolio. The PIs will disseminate the results of the work using the already established TerraFly web-based data dissemination tool.
- Development of the decision support system for predicting rehospitalization for patients with COPD. The decision support system is a web-based tool so as to be easily deployed in a healthcare facility. - Development of a Natural Language Processing framework for extracting the knowledge from unstructured patient information. The system was built using the UIMA and APACHEE framework. - An adaptive video encoding algorithm suitable for healthcare settings to maximize video quality over bandwith connections. The work is particularly useful for telemedicine where three different types of data streams are trasnported: audio, video and physiological data streams. In such scenario a physician can prioritize one data stream over another in order to execute a smooth telemedicine session. - Modifying the video algorithms to optimize the video quality and physiological data stream over multiple data streams - Development of a MOT (software - hardware co-designed system used for interfacing biosensors) that collects data from various on patient sensors, infuse the data, add patient location and send the data to the cloud based systems. Further the information on the cloud could be interfaced with the physicians EHR system and the patient information can be securly transported in HL7 compatible file format. - Development of algorithsm for correctly estimate the patient location and trejectory using Terafly