Objective Pain Metric

May 1, 2017 · 1 min read
projects

This work is focused on identifying correlates of individual pain, defining objective pain metrics, and determining changes to the device parameters that provide the user with the greatest impression of relief. A number of data streams will be studied to identify pain correlates from physiological signals, environmental stresses, and individual behavioral responses. These correlates will be used to identify pain metrics, understand the individual patient’s pain experience and how the device parameters can be changed to optimize the sense of change in a manner that is adaptive to the varying needs of the patient.
Role I am the technical leader for developing AI algorithms to define and build an objective pain metric and identifies pain correlates.
IBM Research. Oct 2016 - Oct 2019.

IBM AI Research AIML
Mohamed Ghalwash
Authors
Mohamed Ghalwash
Associate Professor
Mohamed Ghalwash is an Associate Professor of Artificial Intelligence at Ain Shams University / Zewail City of Science, Technology, and Innovation. Ghalwash is interested in developing machine learning and AI models for discovery of interpretable spatio-temporal patterns from complex events and exploiting their utilities in practical high impact real-world applications, focusing on analytics for healthcare, health behavior, decision support, and to support the generation of real world evidence from medical data, wearable devices and instrumented environments. He also has more than ten years of expertise in the software engineering industry, developing software that are currently being deployed, where he engaged in all phases of the project life cycle for the development of large business applications. My long-term goal is to put my footprints in the field of pattern recognition through contribution of original ideas and translating those ideas to end applications and products.