Measurement of Osteoarthritic Patient Pain Through Electrodermal Activity Signals

Osteo Arthritis Knee

Pain, Electrodermal Activity Signals, Osteoarthritis, Knee

This pilot study aims to investigate the viability of using a smartwatch-based electrodermal activity (EDA) sensor to capture enough EDA signal to quantitatively assess pain in osteoarthritis subjects and test the feasibility of its methods and procedures for later use in subsequent larger-scale studies.

Chronic pain, a disease in its own right, afflicts one in three adults in the US and poses an enormous economic burden ($560-$635 billion annually), more than heart disease, cancer, and diabetes. To treat pain, doctors often prescribe opioids to suffering patients. Paradoxically, prescription opioid abuse has become a national epidemic, costing $500 billion annually in medical, economic, social, and criminal ramifications. However, the development of effective treatment for chronic pain is hampered by the lack of a reliable biomarker that can quantify the level of pain and detect any attenuation after treatment. This is reflected in the failed statistical significance in many clinical trials of drugs for managing chronic pain (e.g., ONO-2952 and Ibodutant) or a large enrollment number being required to reveal significant but small effects (e.g., 1,798 enrollments for the trial on Renzapride). Dysfunction of the autonomic nervous system (ANS) has been linked with many chronic pain conditions. The ANS is the primary pathway in brain-gut communication and manifests the body's emotional and psychological states. This makes it particularly relevant to pain, which has a strong emotional component. The ANS includes the sympathetic (SNS) and parasympathetic nervous systems (PNS), and chronic pain conditions reportedly correlate with an unchecked predominance of SNS activity and desensitized PNS. Thus, the PNS and SNS are promising targets for developing sensitive and robust biomarkers for chronic pain. The investigators will leverage the EmbracePlus smartwatch for the non-invasive quantification of both SNS and PNS activities with time- and frequency-domain analysis of EDA. In this proposed pilot study, the investigators aim to establish whether this biomarker for quantifying pain levels shows promise for osteoarthritis patients when detected through a smartwatch. This is intended to be preliminary work to support a grant application for a more extensive study. In this work, the investigators will collect EDA measurements across up to 15 subjects (2/3 with symptomatic osteoarthritis (Kellgren-Lawrence grade >= 3) and 1/3 control). Each participant's baseline response will first be measured using a thermal grill (a research device commonly used to induce a painful stimulus without injury). Participants will also report their results using a VAS. Then, Participants will be put through three OARSI standardized functional tests: the 30-second chair test, the 40m fast-paced walk, and the stair climb test. During these tests, subjects will receive a handheld clicker to mark moments of their sharpest pain. The results of each test will then be analyzed through a set of time- and frequency-domain analyses of the recorded bio-signals to extract key parameters and measure how well EDA signal detection captured both sharp and dull pain in subjects. If effective, this method can be particularly useful. Existing commercial wearable sensors can collect patient data for a week at a time. This would allow for the collection of in-vivo and continuous patient pain data, which could greatly enhance the understanding of patient pain both pre- and post-treatment.

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United States