Monitoring and addressing the progression of multiple sclerosis (MS) necessitates consistent and prolonged access to data on the disease's advancement. A recent investigation reveals that fitness trackers and smartphones can fulfill this requirement.
MS poses a formidable challenge as the immune system targets the body's nerve fibers, impeding nerve signal transmission and causing a range of motor and sensory impairments, varying in severity among patients.
Patients with MS encounter difficulties in reporting their symptoms, such as fatigue, to physicians regularly, relying on memory to recall their health status over weeks or months. This method often yields inaccurate or incomplete information due to memory lapses or social biases, potentially leading to mismanagement of the disease.
Lead author Shkurta Gashi, alongside colleagues from ETH Zurich's computer science department, highlights the necessity for reliable, frequent, and comprehensive health data to aid physicians in effectively monitoring disease progression and recommending suitable treatments.
Their study, published in NPJ Digital Medicine, demonstrates that wearable devices like fitness trackers and smartphones can offer precise, long-term data with a high temporal resolution. During the investigation, participants—comprising 55 individuals with MS and 24 control subjects—utilized fitness tracking armbands and smartphones for two weeks. Data analysis revealed significant correlations between disease severity, fatigue levels, and physical activity metrics obtained from the wearable devices.
Notably, reduced physical activity and heart rate variability were associated with higher disease severity and fatigue levels in MS patients. Smartphone usage frequency also provided valuable insights, indicating a correlation between decreased phone activity and increased disability and fatigue severity.
Furthermore, a smartphone-based motor function test, requiring participants to tap the screen rapidly, yielded insights into motor skills and physical fatigue levels.
By integrating data from fitness trackers and smartphones across various domains—including physiological, behavioral, motor performance, and sleep patterns—the researchers achieved a high level of accuracy in distinguishing between healthy individuals and those with MS.
This novel approach empowers MS patients to collect reliable, clinically relevant data during their daily routines, potentially leading to improved treatment outcomes and disease management strategies. Sharing their dataset with other researchers, the team emphasizes the need for larger studies to develop robust, universally applicable models for automated evaluation.
In the future, such models could revolutionize MS management, offering patients a significantly enhanced quality of life through the continuous monitoring facilitated by fitness trackers and smartphones.
