TMRL News Room
The hospital of the future could be supported by fully autonomous, advanced sensor networks that monitor life-saving physiological, human activity, and environmental data from critical care patients. Such extensive remote monitoring could save lives -- and reduce healthcare costs by cutting patient recovery time and preventing hospital-related illnesses.
Thanks to a recent seed grant from the UCSB Institute for Collaborative Biotechnologies, researchers with the Translational Medicine Research Laboratory at UC Santa Barbara and Santa Barbara Cottage Hospital are investigating the use of state-of-the-art multimodal sensors to improve patient care while reducing healthcare costs. The project seeks to set guidelines for designing and deploying a non-invasive multimodal network of sensors for Intensive Care Unit (ICU) rooms. The network will monitor patients’ health and activities in the room and track environmental variables, providing data to correlate with patient recovery rate.
This is a collaborative project between several research disciplines at UC Santa Barbara and TMRL's medical partners. Participating research labs include the UCSB Vision Research Laboratory (Professor B. S. Manjunath), the UCSB Data Mining Research Lab (Professors Xifeng Yan and Jianwan Su), the ICU at Santa Barbara Cottage Hospital (Dr. Jeffrey Fried), and Pacifica Institute for Reconstructive Surgery (Dr. Daniel Kolder). Researchers are working to identify various designs for a network of sensors based on predefined tasks, deploy them in a mock-up room at UCSB and the Surgical ICU skills lab at Santa Barbara Cottage Hospital. They aim to analyze the data for patient monitoring applications before potential deployment in hospital ICUs.
Applications of this work include improvements to hospital-care tasks, such as prevention of infection and bedsores (decubitus ulcers),as well as enhancing at-home medical care for the elderly and handicapped, such as systems for monitoring health and human fall alerts. There are potential military-related health applications, according to the researchers, such as soldier group sleep analysis and sensor network deployment. The long-term goal of this effort is to expand this research into all areas of healthcare and beyond the hospital setting into patient rehabilitation and assisted living environments where predictive models will decrease patient risk and lower cost.
Melissa Van De Werfhorst
UC Santa Barbara
College of Engineering
melissa [at] engineering.ucsb.edu
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