Listed below are tools developed by the iDASH team for Patient-Centered research.
Click on the name in the left-hand column to download or access the tool.
Pain is a common but significant problem that is considered a high priority area of care. Although there are many pain assessment scales that can be applied to patients who can communicate, either verbally or non-verbally, pain assessment for minimally responsive patients is limited. In this preliminary work, we developed a novel approach for assessing pain in such patients using a principal component analysis (PCA)-based local detector. Our algorithm produce a single index to indicate the increase in pain level based on unsynchronized, sparse and noisy time series data collected from electronic flowsheets.
Platform: Linux / Macintosh / Windows
Datasets that can be used: UCSD medical center data available here
Citation: S. Wang, X. Jiang, Z. Ji, R. El-Kareh, J. Choi, H. Kim, "When you can ’t tell when it hurts: a preliminary algorithm to assess pain in patients who can’t communicate" AMIA Annu Symp Proc. 2013 Nov 16;2013:1429-37. PMID: 24551418. PMCID: PMC3900156