Gait analysis, or motion analysis, is the quantitative laboratory assessment of
coordinated muscle function, typically requiring a dedicated facility and staff.
At its core is videotaped observation of patient walking. Videos can be
observed from several visual planes at slow speed, allowing detection of
movements not detectable at normal speed. Joint angles can be measured, and
various time-distance variables can be measured including step length, stride
length, cadence and cycle time. Electromyography (EMG) assessed during walking
measures timing and intensity of muscle contractions. This allows determination
of whether a certain muscle`s activity is normal, out of phase, continuous or
Kinematics is the term used to describe movements of joints and limbs such as
angular displacement of joints and angular velocities and accelerations of limb
segments. The central element of kinematic assessment is some type of marker
system that is used to represent anatomic landmarks, which are then visualized
and quantitatively assessed during analysis of videotaped observations.
Movement data is compiled by computer from cameras oriented in several planes
and processes the movement data so that the motion of joints and limbs can be
assessed in three dimensions. The range and direction of motion of a particular
joint can be isolated from all the other simultaneous motions that are occurring
during walking. Graphic plots of individual joint and limb motion as a function
of gait phase can be generated.
Kinetics is the term used to describe those factors that cause or control
movement. Evaluating kinetics involves the use of principles of physics and
biomechanics to explain the kinematic patterns observed and generate analyses
that describe the forces generated during normal and abnormal gait analysis.
Gait analysis has been proposed as an aid in surgical planning, primarily for
cerebral palsy and spina bifida, and for planning for rehabilitative strategies
for a variety of disorders.
are no generally recognized standards of performance and interpretation
of gait analysis. Different labs use different computer systems, and
there are no standards for training in gait analysis techniques and
interpretation. Comparison between laboratories is difficult, and there
could be many interpretations of the same data.
analysis has been used extensively as an outcome tool in research on
gait, however, much is still unknown about the specific correlation of
gait analysis parameters to overall functional status.
analysis can be evaluated in terms of accuracy relative to some
reference standard, but the available comparators only allow evaluation
in a very limited sense. For example, accuracy of gait analysis in
determining some specific parameters of gait such as joint flexion could
be compared to clinical observations, and likely show that gait analysis
is most reliable and valid. However, such information is of limited
utility in making diagnostic decisions. The purpose of both clinical
assessment and gait analysis is not to determine specific quantifiable
deficits in gait but to interpret the whole clinical picture and make
clinical decisions that result in the best patient outcomes.
scientific evidence directly addressing the question of improved patient
outcomes due to gait analysis consists of a single retrospective study
of 23 pediatric patients. In the absence of any well-designed
observational or randomized controlled trials, no conclusions can be
drawn about whether gait analysis in routine clinical management has an
effect on health outcomes.
Despite the lack of specific evidence, the use of gait analysis pre- and
post-surgery has become widely accepted as important to improve surgical
One prospective study assessed the relation between blinded gait
analysis data and clinical measurements in 200 randomly selected patients.
(Desloovere, 2006) The study found only fair to moderate correlations between
the measures (r 2 <= 0.60), none of the correlations were considered good. The
authors suggested that gait analysis can provide different information than
clinical measurement, but no data were presented to indicate that this
additional information improved outcomes.
A prospective single-institution study evaluated the effect of gait
analysis on surgical planning. (Lofterod, 2007) Preoperative surgical plans
derived from clinical assessments were found to have been modified in 70% of
patients following multi-disciplinary team gait assessment. Thirty-nine (65%) of
the 60 patients had been referred by an orthopedic surgeon who was a member of
the gait laboratory. A retrospective study of the influence of gait analysis
recommendations reported that the surgeries performed matched those recommended
in 23 (77%) of 30 consecutive patients who underwent orthopedic surgery at the
author’s institution. (Wren, 2005) The gait laboratory physician was also the
referring physician for nearly 65% of the 30 patients.
Although these studies indicate that gait analysis can influence
clinical decision making, results cannot be generalized beyond these
institutions. In a 2003 study funded by the United Cerebral Palsy Foundation, 4
different gait analysis centers gave different treatment recommendations after
evaluating the same 11 patients. (Noonan, 2003) Thus, there appears to be
little consistency in gait analysis recommendations between centers. Questions
remain, therefore, about both the reliability and the validity of gait analysis
recommendations. Multicenter controlled studies are needed to determine whether
gait analysis can improve clinical outcomes.
A study was published by Cimolin and colleagues in Italy (Cimolin,
2011). It included 19 children with cerebral palsy scheduled for gastrocnemius
fascia lengthening surgery and 20 healthy controls (for establishment of
preoperative normative values). Patient evaluation included videotaping and
three-dimensional gait analysis. The study used the Gait Deviation Index (GDI)
to summarize data; this is a measure derived from comparing nine kinematic
variables of a person’s gait to those of a control group. A GDI value of
approximately 100 or higher indicates an absence of gait pathology. Every
decrease in 10 points below 100 indicates 1 standard deviation from normal
kinematics. All participants completed the study. The mean preoperative GDI
value among the 19 children with cerebral palsy was 70.4 +/- 14.8 (i.e., three
standard deviations away from healthy children). After surgery, the mean GDI was
82.9 +/-7.4. The improvement in GDI was statistically significant compared to
the pre-surgery value (p<0.05). The study did not evaluate whether there was
incremental value with use of the postoperative GDI compared to postoperative