Computer-aided prediction of extent of motor recovery following constraint-induced movement therapy in chronic stroke.
Constraint-induced movement therapy (CI therapy) is a well-researched intervention for treatment of upper limb function. Overall, CI therapy yields clinically meaningful improvements in speed of task completion and greatly increases use of the more affected upper extremity for daily activities. However, individual improvements vary widely. It has been suggested that intrinsic feedback from somatosensation may influence motor recovery from CI therapy. To test this hypothesis, an enhanced probabilistic neural network (EPNN) prognostic computational model was developed to identify which baseline characteristics predict extent of motor recovery, as measured by the Wolf Motor Function Test (WMFT). Individual characteristics examined were: proprioceptive function via the brief kinesthesia test, tactile sensation via the Semmes-Weinstein touch monofilaments, motor performance captured via the 15 timed items of the Wolf Motor Function Test, stroke affected side. A highly accurate predictive classification was achieved (100% accuracy of EPNN based on available data), but facets of motor functioning alone were sufficient to predict outcome. Somatosensation, as quantified here, did not play a large role in determining the effectiveness of CI therapy.
Department of Biophysics, The Ohio State University, 1012 Wiseman Hall, 400 W. 12th Ave, Columbus, OH 43210, USA. Electronic address: hulbert.15@osu.edu.
Sarah Hulbert
SH
George
Department of Civil, Environmental and Geodetic Engineering, The Ohio State University, 470 Hitchcock Hall, 2070 Neil Ave., Columbus, OH 43220, USA. Electronic address: rafiei.4@osu.edu.
Mohammad Hossein
MH
Rafiei
Physical Medicine and Rehabilitation, The Ohio State University, 480 Medical Center Drive, Columbus, OH 43210, USA. Electronic address: lynne.gauthier@osumc.edu.
Lynne
L
Gauthier
Department of Physical Therapy, The College of St. Scholastica, 1200 Kenwood Avenue, Duluth, MN 55811, USA. Electronic address: aborstad@css.edu.
Alexandra
A
Borstad
Physical Therapy Division, School of Health and Rehabilitation Sciences, The Ohio State University, 453 W 10th Ave, Rm. 516E, Columbus, OH 43210, USA. Electronic address: John.Buford@osumc.edu.
John A
JA
Buford
Departments of Civil, Environmental and Geodetic Engineering, Electrical and Computer Engineering, Biomedical Engineering, Neurology, and Neuroscience, The Ohio State University, 470 Hitchcock Hall, 2070 Neil Ave., Columbus, OH 43220, USA. Electronic address: adeli.1@osu.edu.
Hojjat
H
Adeli
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002908:Chronic Disease; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015915:Motion Therapy, Continuous Passive / Q000379:methods*; D009043:Motor Activity / Q000502:physiology*; D020127:Recovery of Function / Q000502:physiology*; D020521:Stroke / Q000503:physiopathology*; D000071939:Stroke Rehabilitation; D055815:Young Adult
Chronic stroke; Computational neuroscience; Constraint induced movement therapy; Enhanced probabilistic neural networks; Motor function; Somatosensory function