Amputees Clinical Trial
Official title:
Comparing Running-Specific and Traditional Prostheses During Running: Assessing Performance and Risk
The purpose of this research is to provide clinically, administratively, and field-relevant
objective running outcomes by directly comparing running biomechanics of individuals with
lower extremity amputation (ILEA) using RSPs (Running Specific Prostheses) and traditional
prostheses. Within this purpose, the project has two specific aims:
Specific Aim 1: To compare RSPs and traditional prostheses with respect to running ability
and performance
Specific Aim 2: To compare RSPs and traditional prostheses with respect to injury risks
associated with running
Hypothesis 1a: RSPs will outperform traditional prostheses at all velocities as measured by
kinetic data (ground reaction forces, joint powers, joint and limb work) and 50m dash time.
Hypothesis 1b: ILEA intact limbs and able-bodied control limbs will outperform residual limbs
with RSPs and traditional prostheses at all velocities as measured by kinetic data.
Hypothesis 2: Running with RSPs will show reduced acute and chronic injury risks compared to
traditional prostheses at all velocities as measured by loading rates, EMG amplitudes,
lumbopelvic kinematics, and modeled joint loads.
A. BACKGROUIND
Current knowledge and understanding of individuals with lower extremity amputations (ILEA)
when running are limited with respect to biomechanical performance and injury risks. ILEA are
able to run with both running-specific prostheses (RSPs) and traditional prostheses; however,
direct comparisons of subjects running with each of these prosthetic designs do not exist.
The reported literature examining one design or the other often do not have participants
running at the same velocities. Additionally, when running velocities are similar between
studies, the same variables are rarely investigated. This makes comparisons between RSPs and
traditional prostheses exceedingly difficult, and drawing conclusions on both performance and
injury risk is virtually impossible. Furthermore, no ILEA running studies to date have
investigated muscle activities, nor have running simulations of musculoskeletal models been
generated. These major gaps in research substantially limit the understanding of both
performance and injury risk of ILEA running with different prosthetic designs. Gaining this
knowledge will directly inform clinicians and administrators within the Department of Defense
and Veterans Administration systems on prosthesis prescription for running at a range of
speeds as well as for return to duty scenarios. Therefore, the proposed study will utilize
motion capture, muscle activity, and musculoskeletal modeling techniques to directly compare
performance and injury risks of ILEA running with both RSPs and traditional prostheses across
a range of speeds. The investigators will also capture an able-bodied control group for
normative comparisons. In doing so, this project directly attends to the OPORA's goals and
needs at multiple levels.
B. RESEARCH STRATEGY:
Subjects Twelve subjects with unilateral transtibial amputations will be recruited from the
military, veteran, and civilian populations. Twelve able-bodied sex, age, height, and
weight-matched subjects will serve as a control group to provide normative data for
comparison. All subjects must provide their informed consent prior to beginning any portion
of the study and will have the option to discontinue the study at any time without penalty.
All subjects must complete the Physical Activity Readiness Questionnaire (PAR-Q) prior to
beginning the experiment. If subjects fail this questionnaire (by responding "yes" to any of
the 7 questions), they will not be allowed to participate in the study until they provide
documentation from a physician clearing them to participate.
Experimental Procedures A randomization computer program will determine the order of
prosthetic foot conditions (RSP or traditional) for the ILEA subjects. All subjects (Controls
and ILEA) will undergo 3D running analysis on an instrumented treadmill. A motion capture
system will collect kinematic data (i.e. limb positions; joint angles, velocities,
accelerations) at 200 Hz from reflective markers placed on specific body landmarks. On the
amputated limb, the shank cluster will be placed laterally on the socket and a marker will be
placed at the distal tip of the socket to define the long axis of the residual shank segment.
For the RSP conditions, eight additional markers will be placed on the prosthesis keel. The
marker on the most acute point of the prosthesis will define the prosthetic limb "ankle"
joint. For the traditional prosthesis conditions, markers will be placed similarly to the
intact foot.
An instrumented treadmill will collect ground reaction force (GRF) data at 1000 Hz from force
platforms imbedded in the treadmill. Kinematic and ground reaction force data will be
combined and standard inverse dynamics techniques will be used to calculate joint kinetic
data (i.e. forces, moments, powers, and work) using Visual3D (C-Motion, Germantown, MD)
software.
Muscle activation data will be collected at a sampling frequency of 2000 Hz using surface
electromyography (EMG) from six bilateral hip and trunk muscles. Disposable pre-gelled
silver-silver chloride (Ag-AgCl) electrodes will be placed over bilateral gluteus medius,
gluteus maximus, rectus femoris, biceps femoris, lumbar erector spinae, internal oblique, and
external oblique muscles. Maximal voluntary isometric contractions (MVIC) will be obtained
for normalization purposes using manual resistance applied in standardized positions.
All subjects (ILEA using RSPs, ILEA using traditional prosthesis, and Controls) will run at
six prescribed speeds (2.5, 3.0, 3.5, 4.0, 5.0, 6.0 m/s) on a treadmill, presented in
randomized order. ILEA subjects will complete all speed conditions wearing both their RSP and
traditional prosthetic foot. As mentioned earlier, the prosthesis order will be randomized,
but all speed conditions will be completed in one prosthesis prior to changing into the
second prosthesis condition. This will save time and maintain a similar prosthetic fit
between speed conditions. The study protocol requires that every subject runs at the same 6
specific speeds identified above. Each treadmill speed condition will take approximately 30
seconds, or the time needed for subjects to stabilize their gait at the speed and a
collection of 10 consecutive strides to be collected. At least 2 minutes rest will be
provided between each speed condition, and subjects can take more rest if needed.
After completing the treadmill trials, subjects will complete 3x50m dashes in each foot
condition to determine maximum speed. Again, at least 2 minutes rest will be provided between
each effort, and subjects can take more rest if needed. The order of prosthesis use will also
be randomized for this test, but all three dashes will be completed consecutively for each
prosthesis condition.
To evaluate performance while running, the primary outcome measures being evaluated will
include peak joint powers; concentric, eccentric and total joint and limb work; average
vertical and Anterior and Posterior (AP) GRFs; vertical and AP GRF impulses; and 50m dash
time/speed. To evaluate injury risk while running, the primary outcome measures being
evaluated will include average GRF magnitudes and loading rates, asymmetry in GRFs and joint
moments, normalized EMG amplitudes, lumbopelvic kinematics, and peak and average joint
contact forces over stance. Data for these measures will be collected for all subjects and
then compared among the three groups (ILEA with RSPs, ILEA with Traditional Prosthesis, and
Controls). No intervention will be offered to any subject and no follow-up to assess
biomedical and/or health outcomes will be conducted.
Electromyography Signal Analysis Raw EMG data will be demeaned, band-pass (cutoff
frequency10-400 Hz) and band-stop (cutoff frequency 59-61 Hz) filtered to remove movement
artifact and 60 Hz electrical noise using dual-pass (zero phase lag) Butterworth filters. EMG
data will then be full wave rectified and low pass filtered to create linear envelopes. Peak
values will be extracted from the MVIC trials to be used for normalization of the running
trials to express EMG data as % Maximum Voluntary Contraction (MVC). Root mean square (RMS)
of each muscle's activity will be calculated during stance and swing phases of running to
investigate amplitude differences. Cross-correlation methodology will be utilized to
investigate relative timing between trunk and hip musculature. Comparisons will be made to
assess symmetry of muscle activation amplitude and timing between intact and prosthetic limb
sides for each of the running speed and prosthesis conditions.
Musculoskeletal Model Three musculoskeletal models will be developed in OpenSim. For the
first model, the investigators will use a generic musculoskeletal model representing a
non-amputee adult male, which has previously been used to assess muscle function during
non-amputee running. The second and third models will be modified versions of the non-amputee
model that represents a person using a prosthesis. The second model will include a
traditional transtibial energy storage and return prosthesis, and the third model will
include a running specific prosthesis. For both models, the investigators will remove the
ankle muscles from the residual leg, including the medial and lateral gastrocnemius, soleus,
tibialis posterior, flexor digitorum longus, tibialis anterior and extensor digitorum longus.
Running Simulation Generation The models will be scaled to each individual subject using
manual, uniform scale factors, computed from an inverse dynamics model based on kinematic
marker positions and developed in Visual3D (C-Motion, Inc., Germantown, MD). Then, an inverse
kinematics solution will be computed in Visual3D using a weighted least squares optimization
algorithm. After the inverse kinematics solution has been computed, the investigators will
perform a Residual Reduction Algorithm. Once minor changes have been made to the model and to
the kinematic trajectories of the generalized coordinates, the investigators will implement a
Computed Muscle Control algorithm. Once a solution for individual muscle excitations is found
using the Computed Muscle Control algorithm, the investigators will compare it to the
experimentally-collected electromyographic data. The investigators will generate running
simulations at all running speeds for all participants. The results of these simulations will
be compared between groups and across speeds, similar to the experimental measures that will
be analyzed in this study.
Joint Contact Force Analysis Once the running simulations have been developed, the
three-dimensional contact load at the hip will be determined from the joint intersegmental
force and compressive forces from the muscles crossing the joint, similar to the previous
analyses during amputee walking. In addition, the muscle forces determined from the movement
simulation will be used to help interpret the net contact loads.
Material Properties and Anthropometrics Inertial properties of the prosthetic components and
intact body segments will be estimated for use with the inverse dynamics approach. Subject
masses will be measured using a force platform. Height and body weight of each subject will
be measured, and anthropometric measurements from marker positions will be used to estimate
the mass, center of mass, and moments of inertia of intact limb segments. Because ILEA
subjects are missing one foot and part of their shank, an adjusted body mass (ABM) will be
used as an input to anthropometric regression equations that account for the missing body
segments.
For subjects with amputation, the residual limb length and circumferences at the knee joint
and distal end of the limb will be measured using a measuring tape. Residual limb inertial
properties will then be estimated as a frustum of a right circular cone. Residual limb mass
will be estimated from the calculated geometric volume assuming a uniform 1.10 g/cm3 tissue
density. For the RSP conditions, the inertial properties of the RSP will be estimated from
data published by the PI. Subsegments within the RSP keels will be defined via reflective
marker placements and the inertial properties of each subsegment will be estimated by
assuming each segment as a rigid trapezoidal cuboid. For the traditional prosthesis
conditions, the inertial properties of the prosthesis will be estimated according to
published literature.
C. STATISTICAL PLAN and DATA ANALYSIS
Statistical Analysis This research is designed to determine the effects of prosthesis type on
a variety of performance and injury-risk related outcome variables across a range of running
speeds. A three factor (Group x Limb x Speed) mixed model ANOVA will be used to identify
statistical changes of the following dependent variables: peak hip, knee, and ankle joint
powers and mechanical work; average ground reaction forces; loading rates; and EMG
amplitudes. Group (Individual Lower Extremity Amputation Running-Specific Prosthesis
(ILEARSP) vs Individual Lower Extremity Amputation Traditional Prosthesis (ILEATrad) vs.
Control) will be considered as a between-subjects independent variable, Limb
(prosthetic/intact or left/right) as a within-subjects independent variable and Speed (2.5,
3.0, 3.5, 4.0, 5.0, and 6.0 m/s) as a within-subjects independent variable.
A two factor (Group x Speed) ANOVA will be used to identify statistical changes of dependent
variables including ground reaction force symmetry, joint kinetic symmetry, and lumbopelvic
kinematics. A one-way ANOVA will determine statistical differences between groups for the 50m
dash time and speed.
Significance for all statistical tests will be set at α=0.05.
Sample Size Calculations This study will have appropriate statistical power to assess our
hypotheses. Effect sizes for significant differences between RSP, intact, and able-bodied
limbs in GRF loading rates, average GRF, and total joint work were estimated based on prior
data collected by the PI from 8 ILEA and Control subjects running at 2.5, 3.0, and 3.5 m/s.
These effect sizes ranged between 0.4 and greater than 0.9. An effect size of 0.7 was also
estimated from the volume of oxygen (VO2) values of one study comparing subjects running with
RSPs and traditional prostheses. To be conservative, the investigators utilized the lowest of
these effect sizes (0.4) to perform a power analysis for ANOVA with repeated measures using
G*Power (v. 3.1.9.2, Dusseldorf, Germany). This yielded a total sample size of 24 with α =
0.05 resulting in 80% power to detect differences between limbs, prosthetic feet, or ILEA and
Control subjects in kinetic values during running. The investigators anticipate similar
effect sizes for changes in the remaining biomechanical variables the investigators will
examine in the proposed study. Based on this analysis, 12 ILEA subjects and 12 control
subjects will provide substantial statistical power to detect significant differences in
biomechanical outcomes between groups and prosthetic feet.
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