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Research Article
Knee Flexion and Daily Activities in Patients following Total
Knee Replacement: A Comparison with ISO Standard 14243
Markus A. Wimmer,1William Nechtow,1Thorsten Schwenke,1and Kirsten C. Moisio2
1Department of Orthopedic Surgery, Rush University Medical Center, Chicago, IL 60612, USA
2Feinberg School of Medicine, Northwestern University, Chicago, IL 60610, USA
Correspondence should be addressed to Markus A. Wimmer; markus a wimmer@rush.edu
Received December ; Accepted July
Academic Editor: George Babis
Copyright © Markus A. Wimmer et al. is is an open access article distributed under the Creative Commons Attribution
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly
cited.
Walking is only one of manydaily activities per formed by patients followingtotal knee replacement (TKR). e purpose of this study
was to examine the hypotheses (a) that subject activity characteristics are correlated with knee exion range of motion (ROM) and
(b) that there is a signicant dierence between the subject’s exion/extension excursion throughout the day and the ISO specied
input for knee wear testing. In order to characterize activity, the number of walking and stair stepping cycles, the time spent with
dynamic and stationary activities, the number of activity sequences, and the knee exion/extension excursion of TKR subjects
were collected during daily activity. Flexion/extension proles were compared with the ISO simulator input prole using a
level crossing classication algorithm. Subjects took an average of (range: –) walking cycles including (range: –
) stair stepping cycles. Active and passive ROMs were positively correlated with stair walking time, stair step counts, and stair
walking sequences. Simulated knee motion according to ISO showed signicantly fewer level crossings at the exion angles –∘
and beyond ∘than those measured with the monitor. is suggests that implant wear testing protocols should contain more cycles
and a variety of activities requiring higher knee exion angles with incorporated resting/transition periods to account for the many
activity sequences.
1. Introduction
Total knee replacement (TKR) surgery has become the most
common total arthroplastic procedure in the United States
with over , surgeries being performed in and
rising to an expected . million annual surgeries by
[]. In addition, TKR surgeries are increasingly performed on
younger and more active patients []. In this patient group,
polyethylene wear can be a limiting factor for longevity []. As
for the hip, wear particles generated during sliding contribute
to osteolysis and subsequent loosening of the prosthesis [].
Since this is one of the most common reasons for revision in
TKR [], preclinical wear testing is an important step before
any new TKR device is brought to market.
State-of-the-art knee wear testing is conducted according
to ISO standards - [] and/or - []. ese stan-
dardized protocols presumably mimic the in vivo kinematic
and kinetic conditions of the knee prosthesis during its
lifetime.einputforTKRweartestingisspeciedasa
sequence of gait cycles that are continuously repeated at 1.0±
0.1Hz until million cycles are reached. is, as commonly
assumed,representstheprostheticlifespanofaboutveyears
in vivo. Indeed, several activity studies on patients with total
hip and/or knee replacement found that subjects walk on
average between . and . million gait cycles annually [–
].
However, walking is only one of many daily activities per-
formed by patients following TKR. Other common activities
include standstill with related starting/stopping maneuvers,
stair ascent/descent, chair sitting and rising, lying down to
rest, and a variety of recreational activities. Hence, including
kinematic and kinetic characteristics of these activities into
wear testing may result in a more realistic simulation of
wear. Indeed, better agreement between wear patterns on
simulator tested prostheses and those observed on retrieved
specimens was achieved aer incorporating stair descent into
Hindawi Publishing Corporation
BioMed Research International
Volume 2015, Article ID 157541, 7 pages
http://dx.doi.org/10.1155/2015/157541
BioMed Research International
testing protocols [,]. However, for TKR subjects, duration
and frequency of these additional activities are unknown.
erefore, the purpose of the study was to describe the
frequency and duration of daily physical activities of TKR
subjects during a -hour day using electrogoniometry. In
addition, we chose to follow the exion/extension excur-
sion of the knee prosthesis throughout the day, because
exion/extension movement is an input variable for the
knee simulator, which directly impacts sliding distance and,
thus, wear. e exion/extension excursion is also interesting
from a clinical viewpoint: Active and passive knee exion
ROM are indicators of a patient’s functional status, and knee
ROMiscommonlyusedtoevaluateTKRsurgery[]and
rehabilitation programs []. Although, TKR ROM has been
found uncorrelated with patient satisfaction and perceived
improvement in quality of life [], it is unknown if TKR
ROM is associated with activity prole. We hypothesized that
(a) subject activity characteristics are correlated with knee
exion range of motion (ROM) and (b) there is a signi-
cant dierence between subject exion/extension excursion
movement and the ISO simulator input.
2. Subjects and Methodology
2.1. Subject Population. Forty subjects were recruited from a
large orthopedic practice (Midwest Orthopaedics, Chicago,
IL) specialized in joint replacement surgery. e study was
approved by the institutional review board, and all subjects
gave informed consent. Potential subjects were identied
from a database of all patients who had received a TKR at the
Medical Center. All participants met the following inclusion
criteria: having received a primary TKR implant of a single
design (Miller-Galante or MGII, Zimmer Inc., Warsaw, IN,
USA), having knee in excellent condition as determined by
latest follow-up, being able to walk without assistive devices,
and being able to live and function independently in their
home. Exclusion criteria were as follows: past or present
history of a neurologic disorder; other medical conditions
aecting their physical function; previous revision surgery.
Six subjects were excluded from the analysis because of cable
or connector failure of the electronic data recording device
and two subjects were excluded because of other technical
errors which truncated the activity data. Data for the remain-
ing subjects were included in the analysis (Tab l e ).
2.2. Activity Monitor. e activity monitor utilized hardware
introduced by Morlock et al. []andaportabledatalogger
collecting data from three sensors at Hz. Two inclination
sensors recorded sagittal plane thigh and shank inclinations.
A goniometer connecting the two device segments measured
thekneeexionangle(Figure ). e device weighed less than
g and did not inhibit movement. Normal clothing was
worn over the device.
Data was streamed to a memory card embedded in the
datalogger.epostprocessingcodewaswritteninMATLAB
(MathWorks, Inc., Natick, MA, USA). Dynamic activities
were classied into walking, stair stepping (ascending and
descending combined), and unrecognized activities based on
a pattern recognition program previously written []and
T : Mean, one standard deviation, and range of demographic
and functional data for subjects included in the analysis (𝑁=32).
Parameter Mean
( SD) Range
Gender M/F / N/A
Age [years] . (.) .–.
Height [cm] . (.) .–.
Mass [kg] . (.) .–.
BMI [kg/m] . (.) .–.
Aected and tested side
(right/le) / N/A
Time between surgery
and data collection
[years]
. (.) .–.
Active knee ROM
Flexion [∘](12) –
Extension [∘](3)−–
Passive knee ROM
Flexion [∘](13) –
Extension [∘](4)−–
ROM: range of motion.
Greater
trochanter
Knee joint line
Lateral malleolus
F : Placement of the activity monitor. e following anatom-
ical landmarks served as orientation: greater trochanter, knee joint
line, and lateral malleolus. e electrogoniometer was placed on the
lateral aspect of the knee joint line. e two monitor segments were
aligned along lines connecting the landmarks.
adapted for TKR by H¨
anni et al. [].Lowerandupperexion
angle boundaries for activity recognition were manually set
for each subject using data captured during a calibration
run (Figure ). Stationary activity, for example, lying down,
sitting, and standing, was identied as a period with the thigh
and shank inclination sensors remaining within a ±∘range
foratleast.secondsandwasfurtherclassiedbasedon
limb inclination (Tab l e ).
BioMed Research International
T : Classication of stationary activities into lying down,
sitting, and standing was based on shank and thigh inclination.
Activity
Shank
inclination
[∘]
igh
inclination
[∘]
Minimum
duration
[second]
Lying down > >
Sitting > –
Standing −– −–
0
60
80
20
40
100
−60
−40
−20
−80 28641012
Time (min)
Knee angle
Shank inclination
igh inclination
Sitting
Walking Stair up
Stair down
Walking
Sitting
Standing
AV
LB
UB
Angle (∘)
F : igh and shank inclination angles, as well as knee
exion angle for various activities of a representative subject during
the calibration procedure. Zero-degree exion and zero-degree
inclination indicate a straight knee and vertical limbs (e.g., during
standing). LB = lower boundary, UP = upper boundary, and AV =
average.
Output of the analysis soware included the number of
sequences for each activity, the time of each sequence, the
overall time for each activity, and the number of cycles for
level and stair walking. A sequence was dened as a contin-
uous activity within its respective boundary conditions. All
data were normalized to hours to allow for comparison
between subjects.
2.3. Monitor Validation. Twenty out of subjects were
lmed for approximately two minutes (2.3 ± 0.8 minutes)
while performing sequences of sitting, standing, lying down,
walking, and ascending and descending stairs (simultaneous
to activity monitor recording). Four subjects were lmed
for – minutes while performing routine daily activities.
Two blinded observers, who did not otherwise participate
in the study, independently watched the videos. e number
of cycles walked or climbed was counted; times spent with
lying down, sitting, standing, walking, and stair stepping were
measured; stationary, dynamic, and total activity times were
calculated. Since the intraclass correlation coecient (ICC)
T : Validation data for activity monitor results and observa-
tions of long videos for four subjects. Time values were rounded
to the nearest minute (except for stair walking time). All intraclass
correlation coecients were statistically signicant (𝑃 < 0.04).
Parameter Activity Monitor results Observer
results ICC
Time
[min]
Lying down ±±.
Sitting ± ±.
Stair walking . ±. . ±. .
Level walking ± ± .
Standing ± ± .
Total stationary ± ± .
Total dynamic ± ± .
Overall total ± ± .
Steps Level walking ± ± .
Stair walking ± ± .
between the two observers ranged from . for lying down
time to values greater than . for stair stepping, for both
theshortandlongvideos,theobservers’measurementswere
subsequently averaged. e observer-averaged data were then
used for comparison with the monitor-derived data.
No systematic oset between video and activity monitor
measurements was detected. For the short videos, ICCs for all
parameters, with the exception of sitting time (ICC = .),
exceeded . (range: . to .). For the long videos, ICCs
exceeded . for all parameters (Tab l e ). e high ICC for sit-
ting time measured from the longer videos (ICC = .) con-
rmed the monitor’s utility to track this activity in the eld.
2.4. Testing Procedure. During a brief clinical examination of
the subjects (at their home) by a licensed physical therapist,
height and weight, as well as active and passive knee exion
range of motion (ROM), were measured. Double sided Velcro
tape (Velcro Inc., Manchester, NH, USA) and Elastikon
athletic tape (Johnson & Johnson Inc., New Brunswick, NJ,
USA) were used to attach the activity monitor to the skin
of the subjects. An elastic tube stocking was pulled over the
aected leg to prevent chang of the device against cloths
and to protect the cables from entanglement. Prior to data
collection, each subject performed an activity calibration
protocol consisting of sitting, standing, level walking, and
stair walking, during which the subject was lmed and sensor
data were recorded. Subsequently, the activity monitor was
restarted to begin the actual data collection. e calibration
procedure was repeated before the monitor was detached at
the end of data collection to detect potential sensor shiing
or other changes. Subjects were asked to keep a diary of
their activities and to follow their usual activity patterns
throughout the day. Data collection was initialized as early
as minutes of the subject’s waking time and ended as late
as bed time to capture data for approximately hours.
2.5. Comparison of TKR Flexion/Extension Excursions with
ISO Simulator Prole. e TKR exion/extension curves
from the subjects were compared to the exion/extension
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0
10
20
30
40
50
60
70
0 20406080100
Count
1
1
1
1
2
1
0
Cycle (%)
Angle (∘)
F : Level crossing classication of the exion angle 𝛼during
one typical walking cycle (duration: about s). e count of each
level is summarized to the right.
curve specied in the standard ISO standard by using
the concept of “level crossings.” Referring to a graph of
knee exion (𝑦-axis) versus percent gait cycle (𝑥-axis), a
level crossing is a point where the exion/extension curve
crosses the horizontal line denoting a specied knee angle
level (Figure ). As the exion/extension curve goes up and
down, there can be zero to multiple such crossings for
eachanglelevel.enumberoflevelcrossingsfortheISO
exion/extension curve and for the exion/extension curve of
eachsubjectwascountedatthe0,10, 20, . . . , 140∘angle levels.
Only upward crossings were counted (Figure ). Assuming
an identical number of walking cycles per day, the ISO-
simulated knee exion/extension level crossings were now
compared to those of the TKR subjects.
2.6. Statistical Analysis. All statistical tests were performed
in SPSS Version . (SPSS Inc., Chicago, IL, USA). Aer
normalization to hours, the mean and standard deviations
were computed for the relative amount of time spent with
each activity, the occurring sequences for each activity, and
thenumberofstepsforlevelwalkingandstairwalking.
Linear regression models were used to identify associations
between these monitor-derived values and subject charac-
teristics including time past surgery, BMI, height, mass, age,
and active and passive ROM. One-sample 𝑡-tests were used
to detect signicant dierences in number of level crossings
between the in vivo activitydataandthevaluefortheISO
standard at each angular level. e signicance level for all
statistical tests was set to .. e Bonferroni correction was
applied for tests with multiple comparisons.
3. Results
e average total test duration was 11.3 ± 1.2 hours (range:
.–. hours) out of which 9.3 ± 1.2 hours were identied
as stationary activities and 0.9 ± 0.5 hours consisted of
dynamic activities. e remainder of 1.1 ± 0.4 hours could
not be allocated by the analysis soware and was marked
“unrecognized.” e most frequently performed activity,
according to sequence counts, was standing, followed by
level walking, sitting, stair walking, and lying down (Ta b l e ).
Subjects performed an average of 3102 ±1553 walking cycles
perhoursofdailyactivity,outofwhich65 ± 70 were
stair cycles (.%) (Tabl e ). e number of walking cycles
T : Mean, one standard deviation, and range of relative time,
step counts, and number of sequences for all tested activities for all
included subjects (𝑁=32). Time and steps were normalized to
hours.
Parameter Activity Mean
( SD) Range
Time [%]
Lying down . (.) .–.
Sitting . (.) .–.
Standing . (.) .–.
Level walking . (.) .–.
Stair walking . (.) .–.
Unrecognized . (.) .–.
Steps
Stair walking () –
Level walking () –
Total () –
Pedometer () –
Sequence
Lying down (3)–
Sitting (31)–
Standing () –
Level walking () –
Stair walking (14)–
Unrecognized () –
correlated with the number of walking sequences (𝑟 = 0.743;
𝑃 < 0.001). On average, subjects took 8.3± 3.0 walking cycles
per walking sequence. Subjects spent signicantly more time
sitting than performing any other activity (Tab l e ;𝑃<
0.001). Subjects spent signicantly less time walking than
standing (Table ;𝑃 < 0.001).
Active knee exion ROM (as measured during the clinical
exam) correlated with stair walking time (𝑟 = 0.532,𝑃=
0.002), stair walking counts (𝑟 = 0.551,𝑃 = 0.001), and
stair walking sequences (𝑟 = 0.556,𝑃 = 0.001). Similarly,
passive knee exion ROM correlated with stair walking time
(𝑟 = 0.534,𝑃 = 0.002), stair walking counts (𝑟 = 0.535,
𝑃 = 0.002), and stair walking sequences (𝑟 = 0.538,𝑃=
0.001). Time between surgery and activity analysis did not
correlatewithanyofthefunctionalvariables.Nostatistically
signicant dierence between female and male subjects for
any of the variables was found, except for height (𝑃 < 0.001).
e level crossing classication indicated that the popula-
tion as a whole crossed exion levels ranging from ∘to ∘
approximating a log-normal distribution (Figure ). e ∘
exion level was crossed most frequently with an average of
6789 ± 4376 crossings. e ∘level was crossed the least,
averaging only 2±11level crossings in the day. However, not
all TKR subjects crossed all levels during daily activity. e
∘levelwascrossedbysubjects(althoughonlybysixata
relevant number of >), and the ∘level was crossed by
only three subjects. All TKR subjects crossed levels between
∘and ∘. ere was a signicant correlation between the
subjects’ maximum level crossed and the measured active or
passive ROM (𝑃 < 0.001).
e range of crossed levels for ISO was much smaller (∘
to ∘) following a nonnormal distribution. Comparing it to
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Average subject prole
ISO prole
0
2
4
6
8
10
12
0 140130
12011010090
8070605040302010
Counts [103]
Flexion angle (∘)
F : Mean ( SD) number of level crossings for exion angle
levelsfromto
∘. Standard deviations are indicated for the
average counts of the activity analysis patient population. e ISO
prole count was extrapolated from the exion-extension curve as
provided by ISO (ISO--, ) and the average number
of walking steps taken by the subjects during a -hour period.
subject data, the level crossing pattern was shied to the le
(i.e., towards lower exion angles; see Figure ). Most level
crossings were found for the ∘angle (instead of the ∘
angle). Beyond the ∘angle there were no crossings at all.
e average number of crossings was higher for the subject
population at all exion angles beyond ∘. is nding was
signicant (𝑃 < 0.01), except for the ∘angle (Figure ).
4. Discussion
is study provides information on the frequency and dura-
tion of daily physical activities performed by TKR patients
during a -hour day. Subjects spent most of the time sitting,
followed by standing and walking. e large number of
activity sequences (mean total number of sequences: )
indicates that common daily activities such as standing
are interspersed with frequent transitions between activities
resulting in ever changing in vivo loading proles for the
implant. More distinct sequences of standing were recorded
than of any other activity. e results suggest that standing is
a common resting state between various dynamic activities.
In simulation experiments of total hip joints, resting periods
increased the starting friction, indicating lubricant starva-
tion, potentially leading to increased wear []. e results of
this study suggest that one resting period should theoretically
be included on the simulator every . cycles to properly
reect the dynamic activity prole of walking. Subjects who
took more walking cycles did so during a greater number of
sequences, and the number of walking cycles per sequence
showed a relatively small variability. ese results suggest that
wear proles of more active patients could be simulated by
longer testing times.
e total numbers of walking cycles taken per day in
this subject population are within the ranges reported in the
literature. A recent meta-analysis by Naal and Impellizzeri
[], which included patients with total joint replace-
ment (summarizing data from pedometer/accelerometer
studies), found a weighted mean of (% CI: –
) walking cycles per day. is compares well with our
own average of walking cycles per day, particularly if
the somewhat older age of our subject population is taken
into account. e number also agrees with another meta-
analysis of healthy individuals: Bohannon []found
walking cycles in individuals over years old. Since our
TKR patients are expected to take 1.13± 0.56 million walking
cycles per year, including about , stair stepping cycles,
they are however more active than what is normally assumed
in wear simulations. In general, a large variability in activity
and step patterns was observed between subjects. e most
active patient is estimated to take . million walking cycles
per year, including , stair stepping cycles. Similar
results have been reported for patients following total hip
arthroplasty [].elargevariabilityinthenumberofwaking
cycles per day suggests that results from wear tests are only
representative for some subjects and that larger total numbers
ofcyclesperweartestareneededtosimulatewearpatternsfor
more active patients.
Flexion ROM is an important outcome variable in TKR
since many daily activities depend on it. As has been recently
summarized by Fu et al. [], a higher ROM than walking is
necessary for stair or chair maneuvers (∘–∘), kneeling
or squatting (∘–∘), bathtub use (∘), and gardening
(>∘). Not surprisingly, in this study, there was a high
correlation between the maximum exion angle measured
during daily activity and the ROM measured during clinical
examination. Interestingly, subjects with greater active and
passive knee exion ROM also spent more time level walking
and stair stepping. However, it is unclear if more active
patients had greater knee exion ROM because they were
more active or if greater knee exion ROM facilitated a
greater activity level. Nevertheless, the association between
knee exion ROM and activity level should be taken into
consideration during rehabilitation programs following TKR
surgery. e ndings are also interesting in the context of
the ongoing debate about the usefulness of high-exion knee
implants [,]. Based on this data, active patients might
very well benet from it. Future studies comparing high-
exion and standard TKR should therefore stratify for activity
level to break the stalemate.
elevelcrossinganalysisforactivitiesduringa-
hour period revealed a large range of knee exion during
daily activities. e most frequently crossed angle was ∘
of knee exion in our subject population and some subjects
exed their prosthetic knee up to ∘.Incontrast,themost
frequently crossed angle as specied in the ISO standard
was ∘of knee exion with a maximum knee exion angle
crossing at ∘. While it is well known that the ISO standard is
representative for walking activities, the results of this study
clearly show that the ranges of knee exion experienced in
vivo arenotfullyrepresentedbytheISOprole.Hence,the
ASTM F committee has become active in the development
of a standard guide, which will include loading proles other
than walking (personal communication). Since the medial
and lateral femoral radii of the TKR typically decrease with
BioMed Research International
higher exion angle, stresses at the polyethylene plateau may
increase leading to more surface damage. ese dierences
may explain the discrepancies between wear patterns on
retrieval prostheses and those on simulator wear tested
prostheses [,]. Hence, a modied simulator input prole
entailing the exion prole of activities other than walking is
necessary to simulate in vivo loading and wear of the implant.
Recently, detailed in vivo loading data for daily activities
in patients following TKR has become available [–].
While these studies specied the in vivo load magnitude and
knee exion angles for dierent activities of daily living, the
data in these studies were captured from a relatively small
patientpoolwithinstrumentedkneeimplantsandusually
collected in a laboratory environment, except for D’Lima et
al. [] who conducted some eld measurements for specic
activities. However, combining the contact force information
reportedintheliteraturewiththeactivityprolesobtained
in this study greatly improves the understanding of in vivo
loading proles during daily activities in patients following
TKR. Based on the results of the present study, a ratio of :
of number of walking cycles to the number of stair stepping
cycles would be appropriate to represent loading patterns
during locomotion of daily living.
e study has several limitations. All subjects in this study
had received a Miller-Galante or MGII implant. It is possible
that activity proles dier between implant type and model,
that they change over time, and that these changes may aect
implantwearpatterns.Also,theadvancedageofthesubject
population (mean: . years) may have aected the activity
pattern; however, as discussed above, the observed number
of walking cycles was well within the range reported in the
literature. us, we believe this should be similarly true for
other outcome variables of this study.
e amount of unrecognized activity (.% of the total
measurement time) was unexpectedly high. A detailed anal-
ysis of the recorded waveforms of several subjects revealed
that this unrecognized data set consisted mostly of transitions
from one activity to another. Explicit denitions for transi-
tions between activities would improve the proper allocation
oftime.Further,somepatientswalkedwithtwodistinguish-
able types of step patterns: normal walking steps with a high
exionangleandso-called“nesteps”characterizedbylower
knee exion angle. Fine steps with a peak exion angle below
the lower boundary of level walking were not recognized
and classied as “unrecognized.” ese ne steps were oen
taken in conned spaces such as the kitchen as indicated by
the patients’ diaries. Future renements of the recognition
algorithm should incorporate these additional distinctions
of dynamic activities. Finally, activity and exion/extension
monitoring of the knee occurred without simultaneous
recording of knee contact force, which comprises another
important input variable for knee wear testing. Future studies
are necessary to determine the specic loading prole occur-
ring at exion angles >∘.
5. Conclusion
In conclusion, walking and stair stepping accounted for about
% of the monitoring time, with a ratio of : . Subjects
with a higher knee ROM climbed more stairs. While level
walking is the dynamic activity that the articial implant will
have to endure the most, transition periods between activities
are quite common. Walking sequences oen include periods
of standing. e knee exion excursion during hours of
daily activity in patients following TKR includes knee exion
angles ranging from ∘to ∘,whichisnotrepresentedby
the current ISO standards. Taken together, simulated implant
wear testing should contain resting or transition periods
between activities and a larger range of activities such as
stair walking and chair maneuvers and include more loading
cycles than specied in the current standard.
Conflict of Interests
e authors declare that there is no conict of interests
regarding the publication of this paper.
Acknowledgments
e authors would like to thank Professor Michael Morlock
for helpful discussions about the technical aspects of the
activity monitor, Robert Trombley and Anand Joshi for
performingvideotapeanalyses,andDrs.KharmaFoucher
and Annegret M ¨
undermann for their assistance in data
interpretation and paper editing. is study was funded in
part by NIH (R AR and R AR).
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