New tool in assessing smartphone tapping speed MS, study finds
A small preliminary study suggests that patients with multiple sclerosis may be monitored based on the speed of their smartphone use.
How quickly individuals can tap on a smartphone keyboard to monitor the severity of multiple sclerosis (MS) and determine disease progression.
Juan Luis Chico-García, MD, with Ramon Y Kajal HospitalNeurology in Madrid, Spain, research submitted At the 38th Congress of the European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS), October 26-28 in Amsterdam and virtually.
In a prospective study of 50 MS patients at the Hospital Ramon y Cajal Comprehensive MS Center, researchers assessed tapping speed during the first week, passively measured by an in-house smartphone application. They found a correlation between the mean values for the first week of assessment and several baseline disability measures, including: Extended Disability Status Scale (EDSS).
“Our software aims to detect progression independent of relapse activity in patients who already have a diagnosis of multiple sclerosis. This progression is often subtle and is detected over time,” said Chico-Garcia. “Our aim is to find it earlier to initiate treatment that may halt, slow or perhaps even halt progression in the future.” Managed Healthcare Executive.
The mean age of the patients was 44.5 years and the EDSS score was 2.0. Eighty percent had relapsing-remitting MS (RRMS), 12% had secondary-progressive MS (SPMS) and 8% had primary-progressive MS (PPMS).
The tapering speed was lower in patients diagnosed with SPMS than in RRMS. Patients’ tapping speed is related to EDSS scores and several other scales and time since the first symptoms of MS.
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 tactics.”
Chico-García and his colleagues would like to see whether prospective monitoring of MS patients with their tapping software can predict those at risk of neurodegeneration. “It can also be linked to other biomarkers from serum or imaging,” Chico-Garcia said.
Although the pilot studies are promising, Chico-Garcia also recommends interpreting them with caution. “The real challenge now comes, and our software may be needed to prove that it is useful for detecting neurodegeneration associated with multiple sclerosis. We are very excited by the possibilities it can offer us, but We know we have a long road to walk,” he said.
According to Chico-Garcia, in addition to MS, further research may seek applications in various other chronic neurodegenerative diseases.
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