Pain Assessment: A Proof of Concept for the Correlation of Sensor-based Physiological Readings to Self-Report Methods

Abstract

Pain can cause emotional effects on human-like anger, depression, mood swings, and irritability. The discomfort caused by pain can only be seen, but the level of the pain is only felt by the person enduring the pain. One method used by clinicians and doctors to identify one’s pain level is the use of pain score to rate the level of pain endured. Three ways are available to rate the level of pain, which are the patient’s selfreport method, behavioral measurement, and physiological measurement. This study focuses on the correlation between two methods, which are physiological measurement and the selfreport method. The hybrid of integrated physiological sensors and self-report mobile applications is used for system testing in this study. Three physiological variables were used to be collected in system testing which are the heart rate, body temperature, and Galvanic Skin Response. While for the selfreport, an Android mobile application was used to capture the pain level experienced by the authors in the form of numerical scale. To find the correlation between them, all the data collected from the system testing were analyzed using Pearson correlation coefficient formula. The results of the correlation suggested that the heart rate and GSR has a positive relationship with the selfreport, while body temperature has a non-correlated hypothesis. For further work, medical science people and clearance from human ethics need to be considered in the assessment.