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Relationship between gait variables and domains of neurologic dysfunction in multiple sclerosis using six-minute walk test., , and . EMBC, page 4959-4962. IEEE, (2016)Longitudinal estimation of gait time series density in multiple sclerosis subjects using inertial data., , and . BSN, page 152. IEEE, (2016)Causal analysis of inertial body sensors for enhancing gait assessment separability towards multiple sclerosis diagnosis., , , and . BSN, page 1-6. IEEE, (2015)Causality Analysis of Inertial Body Sensors for Multiple Sclerosis Diagnostic Enhancement., , , and . IEEE J. Biomed. Health Informatics, 20 (5): 1273-1280 (2016)Correlations between Inertial Body Sensor Measures and Clinical Measures in Multiple Sclerosis., , , and . BODYNETS, ICST, (2015)Adaptive symptom reporting for mobile patient-reported disability assessment., , , , and . Wireless Health, page 172-179. IEEE, (2016)Determining physiological significance of inertial gait features in multiple sclerosis., , , and . BSN, page 266-271. IEEE, (2016)Toward Detection and Monitoring of Gait Pathology using Inertial Sensors under Rotation, Scale, and Offset Invariant Dynamic Time Warping., , , , and . BODYNETS, ICST, (2015)Understanding the Physiological Significance of Four Inertial Gait Features in Multiple Sclerosis., , , , , , and . IEEE J. Biomed. Health Informatics, 22 (1): 40-46 (2018)Demonstrating the real-world significance of the mid-swing to heel strike part of the gait cycle using spectral features., , , and . BSN, page 133-136. IEEE, (2017)