Objective Method for Diagnosis of Chronic Pain

点击翻译按钮获取中文摘要

Pain assessment is essential to providing proper patient care and assessing its efficacy under clinical settings. The ability to accurately distinguish real from fake pain is also crucial in the determination of the appropriate level of compensation for a patient that claims to be suffering from chronic pain (e.g., motor accident injury claims). The sums paid out for workplace and motor claims was $15 billion in 2018 in Canada and is substantially higher in other countries (approximately $560 billion dollars each year in USA). Our industry partner, Karmy Chronic Pain Medical Clinics (Karmy Clinics) specializes in assessment and management of patients with chronic non-malignant pain and is our industry partner for this research project. To assess pain, physicians typically rely on patients' statements, which are subjective, or imaging technologies, which are unreliable as detected abnormalities do not always indicate pain and are not always present in cases of chronic pain. In this research, we will address the problem of accurately detecting authentic pain by creating an Objective Method for Diagnosis of Chronic Pain. We will create and evaluate an automated chronic pain diagnostic system that will output a computer diagnosed pain score with the ability to accurately distinguish real from fake pain. The proposed Automatic Pain Diagnosis System (APDS) will enhance patient care and improve clinical practice efficiencies compared to manual approaches, which are laborious, inaccurate and difficult to use in busy clinical settings. The proposed APDS will outperform a human observer in accuracy and efficiency by using the most advanced 3D technologies and Artificial Intelligence (AI) algorithms such as Deep Convolutional Neural Networks (DCNNs).