Past and current use of walking measures for children with spina bifida: a systematic review.

Bisaro DL, Bidonde J, Kane KJ, Bergsma SA, Musselman KE. (2015) Past and current use of walking measures for children with spina bifida: a systematic review.

Arch Phys Med Rehabil. 2015 May 2. pii: S0003-9993(15)00384-6. doi: 10.1016/j.apmr.2015.04.014

Abstract

OBJECTIVE:

To describe walking measurement in children with spina bifida, and to identify patterns in the use of walking measures in this population.

DATA SOURCES:

Seven medical databases were searched from inception until March 2014. Search terms encompassed three themes: 1) children, 2) spina bifida, and 3) walking.

STUDY SELECTION:

Articles were included if participants were children aged 1-17 years with spina bifida, and if walking was measured. Articles were excluded if the assessment was restricted to kinematic, kinetic or electromyographic analyses of walking. A total of 1,751 abstracts were screened by two authors independently, and 109 articles were included in this review.

DATA EXTRACTION:

Data were extracted using standardized forms. Extracted data included study and participant characteristics, and details about the walking measures used, including psychometric properties. Two authors evaluated the methodological quality of articles using a previously published framework that considers sampling method, study design, and psychometric properties of the measures used.

DATA SYNTHESIS:

Nineteen walking measures were identified. Ordinal-level rating scales (e.g., Hoffer Functional Ambulation Scale) were most commonly used (57% of articles), followed by ratio-level, spatiotemporal measures, such walking speed (18% of articles). Walking was measured for a variety of reasons relevant to multiple health care disciplines. A machine learning analysis was used to identify patterns in the use of walking measures. The learned classifier predicted whether or not a spatiotemporal measure was used with 77.1% accuracy. A trend to use spatiotemporal measures in older children and those with lumbar and sacral spinal lesions was identified. Most articles were prospective studies that used samples of convenience and unblinded assessors. Few articles evaluated or considered the psychometric properties of the walking measures.

CONCLUSIONS:

Despite a demonstrated need to measure walking in children with spina bifida, few valid, reliable and responsive measures have been established for this population.
Copyright © 2015 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Gait analysis in low lumbar myelomeningocele patients with unilateral hip dislocation or subluxation.

Gabrieli AP, Vankoski SJ, Dias LS, Milani C, Lourenco A, Filho JL, Novak R. Gait analysis in low lumbar myelomeningocele patients with unilateral hip dislocation or subluxation. Journal of Pediatric Orthopedics. 2003 May-Jun;23(3):330-4.

Children's Memorial Hospital/Northwestern University Medical School, 680 North Lake Shore Drive, Chicago, IL 60611, USA.

The surgical indications for the treatment of unilateral hip dislocations or subluxations in patients with low lumbar myelomeningocele remain highly debatable. This study examines the influence of unilateral hip dislocation or subluxation on the gait of these patients using three-dimensional gait analysis. Twenty patients with a diagnosis of low lumbar myelomeningocele underwent three-dimensional gait analysis. All patients were community ambulators with solid ankle-foot orthoses and crutches who presented with unilateral hip dislocation or subluxation and no scoliosis. The patients were divided in two groups. Group 1 comprised 10 patients who demonstrated either no evidence of hip flexion or adduction contractures or symmetric hip contractures. Group 2 comprised 10 patients with unilateral hip flexion and/or adduction contractures. Pelvic and hip kinematics were assessed to determine the symmetry of motion between the involved and the noninvolved side during walking. Seven patients from group 1 walked with a symmetric gait pattern; only two patients from group 2 walked with a symmetric pattern. Gait symmetry corresponded to the absence of hip contractures or bilateral symmetrical hip contractures and had no relation to the presence of hip dislocation. The authors concluded that reduction of the hip is unnecessary.

PMID: 12724595

From neuromuscular activation to end-point locomotion: An artificial neural network-based technique for neural prostheses.

Chang CL, Jin Z, Chang HC, Cheng AC. From neuromuscular activation to end-point locomotion: An artificial neural network-based technique for neural prostheses. Journal of Biomechanics. 2009 Apr 21. [Epub ahead of print]

Department of Physical Medicine & Rehabilitation, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.

Neuroprostheses, implantable or non-invasive ones, are promising techniques to enable paralyzed individuals with conditions, such as spinal cord injury or spina bifida (SB), to control their limbs voluntarily. Direct cortical control of invasive neuroprosthetic devices and robotic arms have recently become feasible for primates. However, little is known about designing non-invasive, closed-loop neuromuscular control strategies for neural prostheses. Our goal was to investigate if an artificial neural network-based (ANN-based) model for closed-loop-controlled neural prostheses could use neuromuscular activation recorded from individuals with impaired spinal cord to predict their end-point gait parameters (such as stride length and step width). We recruited 12 persons with SB (5 females and 7 males) and collected their neuromuscular activation and end-point gait parameters during overground walking. Our results show that the proposed ANN-based technique can achieve a highly accurate prediction (e.g., R-values of 0.92-0.97, ANN (tansig+tansig) for single composition of data sets) for altered end-point locomotion. Compared to traditional robust regression, this technique can provide up to 80% more accurate prediction. Our results suggest that more precise control of complex neural prostheses during locomotion can be achieved by engaging neuromuscular activity as intrinsic feedback to generate end-point leg movement. This ANN-based model allows a seamless incorporation of neuromuscular activity, detected from paralyzed individuals, to adaptively predict their altered gait patterns, which can be employed to provide closed-loop feedback information for neural prostheses.

PMID: 19389678