Researchers have developed an algorithm that, when paired with wearable sensors, provides more informative and effective monitoring of the way people with multiple sclerosis walk. The improved monitoring will help clinicians more easily assess the effectiveness of existing treatments and disease progression in people with MS.

Doctors at Sheffield Teaching Hospitals approached researchers at the University of Sheffield and asked them to help find a way to measure how patients walk in “real life” conditions. Currently, mobility of MS patients is assessed in specialized gait laboratories. The relevant technologies can be expensive and require highly skilled personnel. Measurements taken of people with MS in a lab may not be an accurate representation of their everyday condition. Having data from real life scenarios will help clinical staff assess a patient's condition more accurately. 

Researchers started off by checking that their portable sensor was accurate, comfortable, and able to give the same results as a lab-based sensor. They then developed an algorithm specific to the patient's condition that processed the measurements taken from this sensor. They ensured the algorithm was capable of handling and processing data from complex movements outside labs. 

They acknowledge that while this is a small study, the results are encouraging and provides enough information to progress to a large scale clinical trial. For patients this will mean better treatment as a result of clinicians being more informed about their condition. The effect of this research could therefore be significant for patients as well as cost-effective.

Assessing the way a person walks is often used as an indicator in the early stages of MS. Mobility problems affect 75 percent to 90 percent of people with MS.

The study was published in the journal PLOS ONE.