Assessment and Classification of Early-Stage Multiple Sclerosis With Inertial Sensors: Comparison Against Clinical Measures of Disease State

By B. Greene, S. Rutledge, I. McGurgan, C. McGuigan, K. O'Connell, Brian Caulfield, N. Tubridy. 2015

46 citations recorded by the source corpus.

Subfields: Orthopedics and Sports Medicine, Pathology and Forensic Medicine, Physical Therapy, Sports Therapy and Rehabilitation

How researchers see this paper

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1. Lieven Billiet
2. S. Van Huffel
3. Vanya Van Belle
4. Berk Ustun
5. Cynthia Rudin
6. Ivan Markovsky

Citations in the corpus

• Interval Coded Scoring: a toolbox for interpretable scoring systems (2018, background): “More recently, Ryali et al. (2012) applied the elastic net to estimate functional connectivity from fMRI data, whereas Greene et al. (2015) exploited it to detect mobility parameters progression of early multiple sclerosis and to discriminate patients from a control population based on…”
• Toward Pervasive Gait Analysis With Wearable Sensors: A Systematic Review (2016, unknown): “[56] 2/3D accelerometer + 3D gyroscope/bilateral shanks Statistical features of signals during TUG test Classification of Multiple Sclerosis”