PhD Fellow Emma Hertel

Knee osteoarthritis (KOA) is a multifactorial condition characterised by pain and altered gait biomechanics affecting an increasing proportion of the world population. Pain in KOA is intriguing, as clinical pain has a limited association with the degree of cartilage degeneration, and cartilage itself has minimal nerve innervation. To date, there is limited evidence of how pain mechanisms and gait biomechanics might influence each other. Therefore, PhD fellow Emma Hertel will investigate 1) the interplay of mechanistic pain profiles and gait biomechanics and 2) factors associated with clinical pain in KOA.

Quantitative sensory test (QST), inflammatory biomarkers and symptoms of pain catastrophising, anxiety and depression will characterise different aspects of pain. QST aims to assess nerve function and might be able to provide proxy assessments for maladaptive changes in the nervous system. Computer-controlled cuff pressure algometry will assess QST, which can characterise changes known to increase vulnerability to pain and risk of poor treatment outcomes. The test works by inflating air cuffs around the calves in different patterns to evoke pain. In collaboration with other researchers in the MathKOA group, motion capture will investigate gait biomechanics in KOA patients and healthy subjects with experimentally induced KOA-like pain.

Finally, this project will attempt to explain the individual variance in cuff pressure needed to evoke pain in KOA patients by including cognitive factors, inflammatory markers, biomechanics, and indicators of central changes in pain processing in the model.

This project will help understand the link between pain sensitivity and knee biomechanics. The results will help characterise the relationship between pain mechanisms, biomechanics, and cognitive factors during knee pain. Future models characterising maladaptive changes in these systems might aid in choosing more specific targets for treatment and improve patient care.

Emma holds a Master of Science degree from Aalborg University in Translational Medicine and has experience in human research and QST methodology. You can read more about Emma’s work here.