The need for effective, real time measurement of disease progression
It is vital that we come up with new ways to measure disease progression. We need cheap, fast, reliable ways to be able to detect real time changes in disease activity. This is especially important for progressive MS, where reliable measures are needed to be able to carry out clinical trials in an expedited manner. It is also important for relapsing remitting MS, where early detection of disease progression might lead to a rapid switch of medications, and thus prevent a relapse and accumulation of disability.
Currently, ways to detect disease progression take time, such as following someone and monitoring obvious changes in disabilities combined with MRIs, neither of which are rapid nor in real time. Researchers are investigating alternatives such as subtle changes in gait.
Measuring walking stability in people with MS
New research has shown that measuring walking stability in people with MS using relatively inexpensive technology, could open the door to a quicker, more reliable way to monitor disease progression. Walking manner, also known as gait, can be affected by balance issues that people in the early stages of MS may experience. Even in the absence of obvious disabilities, many people with MS use strategies to improve their stability and reduce the risk of falling, such as taking shorter steps.
Current ways to measure walking stability in the clinic are not sensitive enough to detect the subtle changes in gait that people with MS may experience. This makes it difficult to monitor progression and make changes to current treatments to prevent further disease activity. Therefore, there is a need to better monitor the advancement of disease and the effectiveness of medications in people with MS.
How did researchers use wearable sensors to measure gait?
Professor Mary Galea, a MS Research Australia funded researcher, has found that using wearable sensors can provide information on subtle movement changes that were previously only available as an expensive movement analysis in a Movement Laboratory. Her research has focused on using these sensors to measure walking and balance in people with MS during their appointments at the clinic. By doing this, the results can be immediately provided to the neurologist to determine whether a person’s treatment is effective in preventing disease progression, or whether changes needs to be made. Since these sensors can detect the most subtle changes, disease progression can be monitored closely, and any changes can be acted on quickly to prevent further progression.
Part of this work has been published in Gait and Posture. In this study, Professor Galea and her team compared gait stability between 30 people with MS with no gait impairments and 15 people without MS using different sensor locations and data sources. The participants walked on a treadmill at 1.2 metres per second and movement data was obtained from sensors on the sacrum (base of the spine), shoulder and cervical markers (base of neck), as well as an accelerometer placed at the sacrum. The researchers used these to calculate the local divergence exponent (LDE), a new, simple and sensitive measure of gait stability, which is believed to match up with changes in the brain and spinal cord based on magnetic resonance imaging (MRI).
What did the researchers find?
The researchers found that people with MS, despite not showing any obvious signs of gait instability, walked a lot less stable than people without MS based on all four measurements. However, the accelerometer placed on the sacrum appeared to underestimate gait instability compared to the sensors, with the LDE being about 18% higher in people with MS based on the sensors compared to only 7% from the accelerometer. Therefore, the LDE, as calculated by the sensors and accelerometer, was effective in detecting subtle changes in gait stability in people with MS who show no obvious signs of disability.
What does this all mean?
This means that measuring gait can detect subtle physical changes and may determine the effectiveness of the treatment regimen early in the disease course, allowing clinicians to act upon this quickly to prevent further progression.