A small, preliminary study suggests that multiple sclerosis patients might be monitored based on the speed for their smartphone use.
How quickly individuals can tap on a smartphone keyboard may be a useful tool for monitoring multiple sclerosis (MS) severity and determining progression of the disease.
Juan Luis Chico-Garcia, M.D., with the Hospital Ramon y Cajal, Neurology in Madrid, Spain, presented the research at the 38th Congress of the European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS), October 26–28 in Amsterdam and virtually.
In the prospective study of 50 MS patients at the Hospital Ramon y Cajal comprehensive MS center, researchers assessed tapping speed during first week, passively measured by an in-house smartphone application. They explored the correlation between median values of first week of assessment and several baseline disability measures, including the Expanded Disability Status Scale (EDSS).
“Our software is intended to detect progression independent of relapse activity in patients who already have a diagnosis of multiple sclerosis. This progression is often subtle and detected when time has passed; our aim is to detect it earlier in order to start treatments that can prevent, slow down or maybe stop progression in the future,” Chico-Garcia told Managed Healthcare Executive®.
The patients had a median age of 44.5 years and an EDSS score of 2.0., Eighty percent had relapsing-remitting MS (RRMS), 12% had secondary-progressive MS (SPMS), and 8% primary-progressive MS (PPMS).
The tapping speed was lower in patients diagnosed with SPMS than in RRMS. Patients’ tapping speed correlated with EDSS score and several other scales and time since MS first symptoms.
The research is unique, as Chico-Garcia is aware of only one previous study of tapping on smartphone keys involving MS patients, “but they used different metrics and strategy.”
Chico-Garcia and his colleagues would like to see if a prospective monitoring of MS patients with their tapping software can predict those at risk of neurodegeneration. “It could be also linked with other biomarkers, from serum or imaging, probably,” Chico-Garcia said.
Although the pilot study is promising, Chico-Garcia also advised interpreting them with caution. “The true challenge comes now, and our software may need to prove it is useful to detect the neurodegeneration associated to multiple sclerosis. We are very excited with the possibilities it can offer us, but we know we have a long road to walk,” he said.
In addition to MS, further research could look for applications in other different chronic neurodegenerative diseases, according to Chico-Garcia.