Marta Čeko's R21 NIH Sponsored Grant 'Automated Physiological Assessment of Chronic Pain in Daily Life'

Marta's two-year award from the National Institute of Nursing Research (NINR) at National Institute of Health (NIH) is an Exploratory/Development Grant R21.

In this study Marta and the research team propose to establish diagnostic physiological markers of ongoing clinical pain by capturing ongoing clinical pain and the associated physiological fluctuations and psychological processes.

"We will develop fully automated real-time detection of ongoing pain in N=80 CBP patients from physiological signs collected in everyday life. We will record multiple physiological signals (electroencephalogram (EEG), facial electromyography (EMG), electrooculography (EOG), electrodermal activity (EDA), and heart rate (HR)) from two wearable devices, one worn around the head (Earable) and one worn around the wrist (Empatica). The sensing system will be integrated with an experience sampling method (ESM) smartphone app to collect ratings of pain and psychological processes associated with pain episodes. Our goal in Aim 1 is to establish computational physiology-based models that can predict clinical pain in real-life. To achieve this, we will apply machine-learning techniques to physiological data preceding pain self-reports to build predictive models of ongoing pain, with the ultimate goal for these computational models to be able to trigger psychological interventions when needed most, which we aim to develop in our future research. Our goal in Aim 2 is to field-test these computational models in a new group of N=20 CBP patients."

If the real-life pain experience of patients can be captured in physiological patterns preceding pain, then automated tracking of physiology has considerable potential to improve the efficacy of psychological treatments, by providing signals to trigger just-in-time interventions. Overall, the proposed project will contribute fundamental scientific knowledge about psycho-physiological signs of real-life pain and lay the groundwork for translational efforts to improve outcomes of pain self-management and reduce opioid use.