Background: Wearable technology offers objective and remote quantification of disease progression in neurological diseases such as amyotrophic lateral sclerosis (ALS). Large population studies are needed to determine generalization and reproducibility of findings from pilot studies.
Methods: A large cohort of patients with ALS (N = 202) wore wearable accelerometers on their dominant and non-dominant wrists for a week every two to four weeks and self-entered the ALS Functional Rating Scale-Revised (ALSFRS-RSE) in similar time intervals. Wearable device data were processed to quantify digital biomarkers on four upper limb movements: flexion, extension, supination, and pronation using previously developed and validated open-source methodology. In this study, we determined the association between digital biomarkers and disease progression, studied the impact of study design in terms of required sensor wear-time and sensor position, and determined the impact of self-reported disease onset location on upper limb movements.
Results: The main investigation considered data from a sensor placed on the non-dominant wrist. Participants with higher ALSFRS-RSE scores performed more frequent and faster upper limb movements compared to participants with more advanced disease status. Digital biomarkers exhibited statistically significant change over time while their rate of change was more profound compared to survey responses. Using data from the dominant wrist and changing data inclusion criteria did not alter our findings. ALS disease onset location significantly impacted use of upper limbs. Results presented here were comparable to an earlier study on twenty patients with ALS.
Discussion: Digital health technologies provide sensitive and objective means to quantify ALS disease progression. Interpretable approaches, such as the one used in this paper, can improve patient evaluation and hasten therapeutic development.
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http://dx.doi.org/10.1186/s12984-024-01514-7 | DOI Listing |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11662782 | PMC |
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