Objective

To create a novel neurological vital sign and reliably capture MS-related limb disability in less than 5 min.

Methods

Consecutive patients meeting the 2010 MS diagnostic criteria and healthy controls were offered enrollment. Participants completed finger and foot taps wearing the MYO-band© (accelerometer, gyroscope, and surface electromyogram sensors). Signal processing was performed to extract spatiotemporal features from raw sensor data. Intraclass correlation coefficients (ICC) assessed intertest reproducibility. Spearman correlation and multivariable regression methods compared extracted features to physician- and patient-reported disability outcomes. Partial least squares regression identified the most informative extracted textural features.

Results

Baseline data for 117 participants with MS (EDSS 1.0-7.0) and 30 healthy controls were analyzed. ICCs for final selected features ranged from 0.80 to 0.87. Time-based features distinguished cases from controls (P = 0.002). The most informative combination of extracted features from all three sensors strongly correlated with physician EDSS (finger taps r_s  = 0.77, P < 0.0001; foot taps r_s  = 0.82, P < 0.0001) and had equally strong associations with patient-reported outcomes (WHODAS, finger taps r_s  = 0.82, P < 0.0001; foot taps r_s  = 0.82, P < 0.0001). Associations remained with multivariable modeling adjusted for age and sex.

Conclusions

Extracted features from the multi-sensor demonstrate striking correlations with gold standard outcomes. Ideal for future generalizability, the assessments take only a few minutes, can be performed by nonclinical personnel, and wearing the band is nondisruptive to routine practice. This novel paradigm holds promise as a new neurological vital sign.