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Studying aging, mobility and chronic low back pain in older adults using remote monitoring

Project Description

Chronic low back pain is a very common clinical condition in older adults. Many structural changes resulting from aging predispose an individual to chronic low back pain. Continuing pain and changes to core muscle strength further impact mobility and physical activity in these individuals. Although exercises are commonly prescribed, patients are often unable to perform them due to pain.

Pain related to movement is functionally important. Traditional methods of pain assessment do not efficiently capture this burden. The first study phase will validate a wearable device to capture bio-mechanical signals indicative of gait and activity (type and amount). The second phase will use this device in 20 older adults with chronic low back pain to integrate the information from the device with real time recording of pain symptoms and contextual information. Additionally, neurophysiological measurements will be collected to understand exercise and physical activity induced changes within the nervous system, to better understand movement related pain in chronic low back pain patients. 

“This project will help us to understand the relationship of physical activity and exercise with chronic low back pain in older adults. Such ecological momentary assessment of activity and its context allows us to study the pain burden in real world settings in older adults. The integration of machine learning and predictive modelling allows the possibility of personalized care based on potentially contradictory outcomes of benefits or intolerance of physical activity in subgroups of participants. Potentially, this technology can also be used to monitor patients after specific treatments for chronic low back pain.” 
Harsha Shanthanna



  • Harsha Shanthanna
  • Aimee Nelson
  • Jamal Deen
  • Ravi Selvaganapathy
  • Luciana Macedo
  • Lisa Carlesso
  • Lehana Thabane
  • Mohit Bhandari
  • Kim Madden
  • Moin Khan
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