Walking Motion Analysis of Intermittent Claudication and its
Application to Medical Diagnosis
Tetsuyou Watanabe, Yui Sanou, Takeshi Yoneyama,
Yasumitsu Toribatake, Hiroyuki Hayashi and Noriaki Yokogawa


Abstract— There are mainly two kinds of diseases inintermittent claudication. One is lumbar spinal canal stenosis(LSS) and the other is peripheral arterial disease (PAD).
Differentiating LSS and PAD is a critical issue. Wrong
differentiation might cause amputation of lower extremities. At
small clinics and hospitals, simple and cheap differentiation
system is required. Concerning this, this paper investigatedwalking motions of the patients. The subject with LED markers
walked on the treadmill until she or he felt pain. We recorded
the walking motion by camera and tracked the LED markers.
Treadmill enables to measure walking motion for a long time ina small space, and LED marker provides position of every joint
in the walking. Then, we can get the information such as joint
angle trajectory, hemi-foot step, stance and swing phases
without any other sensors like foot switch or force plate. We
compared walking motions of healthy persons, LSS patients and
PAD patients, found their features and 3 factors for diseasedifferentiation; average bending angle of knee joint at the startof stance phase, average dorsiflexion angle of ankle joint, andaverage hemi-foot step length. The results indicate that 2
dimensional images of walking motion for several seconds areenough for deriving the factors. Then, we can construct thesimple examination system for the disease differentiation.

I

I. INTRODUCTION

NTERMITTENT Claudication [1] is a walking symptom
defined that the patients cannot continue walking due toalgia or numbness of lower limbs after walking for someperiod, but if they take a rest, they can walk again. We areapproaching to aged society. Then, recently there has been amarked increase in the number of patients who consult adoctor of orthopedic surgery due to the intermittent
claudication [2]. Roughly speaking, there are two kinds ofmain problems for intermittent claudication: LSS (lumber
spinal canal stenosis) and PAD (peripheral arterial disease).
These diseases are definitely different diseases. Therefore itis clinically very important to differentiate the main problems.
If the doctor missed the diagnosis and the patient were cared
for according to the wrong diagnosis, the patients would
suffer from necrosis or paralysis of lower limbs, orvesicorectal disorder. The medical treatments of LSS patientsare done by the doctors of orthopedic surgery while thetreatments of PAD patients are done by the doctors ofvascular surgery or cardiovascular internal medicine [1].
T. Watanabe, Y. Sanou and T. Yoneyama are with the College of Scienceand Engineering, Kanazawa University, Kakuma-machi, Kanazawa,
920-1192, Japan (corresponding author to provide phone: +81-76-234-4682;
fax: +81-76-234-4682; e-mail: twata@t.kanazawa-u.ac.jp).
Y. Toribatake, H. Hayashi and N. Yokogawa are with the Department ofOrthopedic surgery, Koseiren takaoka Hospital.

VascularSurgery,
1.8%
Internal
Medicine,
12.4%

Emergency
Department,
0.9%
CerebralSurgery,
0.4%

Orthopedic
Surgery,
84.5%

Fig.1. Specialty of the doctor whom the patients of intermittent
claudication consult at the first time
PAD
13.3%
LSS+PAD
10.8%

LSS
75.9%

Fig.2. Main problem of the patients of intermittent claudication who
consult orthopedic surgeon.

However, the intermittent claudication is a kind of walking
trouble, and then most of the patients firstly consult the doctorof orthopedic surgery as shown in Fig.1 [3]. As shown in
Fig.2, the main problem of about 13% of the patients who
consult orthopedic surgeon was reported to be PAD [3].
Therefore, it is critical to distinguish PAD and LSS in the
medical diagnosis at orthopedic surgery clinics. In Japan, thenumber of LSS patients is larger than the number of PAD
patients while in western countries, the number of PAD
patients is larger. However, if taking aging population andwesternization of dietary habit into consideration, the numberof PAD patients is considered to be large in future in Japan[3].
So far, there are several methods for the differentiation:
examination by touch or observing standing posture, andexamination through large precision instruments such as
angiography, myelography, and MRI (magnetic resonanceimaging). However, with the former examination, the doctors
sometimes can not identify its main problem. On the otherside, the latter examinations are invasive and high cost, andonly professionals can use such precision instruments. Then,
it is difficult to conduct such a high cost examination at small
hospitals and clinics. From the viewpoint of the patients, thehigh cost is not undesirable.
Concerning the above, this papers aims at developing an
examination system which can differentiate PAD and LSS
easily and with low cost, and which can be used even at small
hospitals and clinics, by using walking motion analysis. The
main contributions of this paper are as follows.

1. Extraction of factors to differentiate PAD and LSS: By
analyzing the walking motion, we extract 3 new factors todifferentiate PAD and LSS.
2. Walking motion measuring method for thedifferentiation: Based on the experimental results, we showthat we only have to observe walking motion for a few
seconds to differentiate PAD and LSS. This is good news forthe patients suffering from intermittent claudication since
they can stop walking before feeling pain at their legs.
3. Simple walking motion measuring system: The subjects
with LED markers walk on the treadmill. The walking motion
is recorded by commercially available digital cameras. The
obtained motion image is analyzed to differentiate PAD and
LSS. Generally, special markers and cameras are needed formotion capture system. In addition, many numbers ofcameras and large space are needed to capture walking.
However, it is difficult to provide such special instruments
and large space at small hospitals and clinics. We use simple
handmade LED markers, measure only one side of the patient
by camera and do not use the other sensors such as footplate.
The obtained motion image doesn‟t have 3 dimensional
information but, we show 2 dimensional motion image hasenough information to differentiate PAD and LSS. Then, we
can develop the measuring system which can be used easily
and with low cost by the doctors at small clinics who is notprofessional for engineering or technology.
From half a century ago, there are researches concerningwith walking motion; for example, walking pattern analyses
for normal men [4] and women [5], estimation of humanposition at indoor [6], measuring joint moment of lower limbs
when the subjects attach artificial legs [7], analysis ofwalking pattern of the patients suffering from osteoarthritis of
hip [8], and analysis of the long-term walking motion of thepatients whose hip totally replaced with artificial one byoperation [9], analysis of epidural pressure in patients withlumbar spinal stenosis [10]. However, the walking motion
analysis for main problem identification of intermittent
claudication has not been done yet. We aim at developing
simple walking motion analysis system and at differentiating
PAD and LSS.
II. WALKING MOTION MEASUREMENT AND ANALYSISSYSTEM

A. Measurement system
As shown in Fig.3, we attached handmade LED markers on
the subject. We turned off the room lights so that only thelights of the LED markers could be seen. Every subject
walked on the treadmill until she or he felt pain at her or his
leg. The merit of using treadmill is that 1) we can measureeven in a small room, 2) we can record long-term walking
motion with a few cameras (we do not need a lot of cameras),3) we can fix the camera position and then stable motion
image can be obtained. On the other side, the drawback ofusing treadmill is that the walking could be different fromLED

Fig.3. LED markers on the subject

Fig.4. Walking measurement systemyyAcromion(x1,y1)

Angle I

Iliac crest(x2,y2)=(0,0)

xxAngle II
Caput fibulae(x3,y3)

Angle III
Angle IV

Lateral malleolus(x4,y4)

Fifth metatarsal caput(x5,y5)(a) Marker positions(b) Angles
Fig.5. Coordinate frame, marker positions, and angles

normal walking on the floor. In this paper, we have to develop
the measurement system which can be used even in small
clinics where it is hard to provide the room specially set up for
motion capture. Then, we will take this way.
Fig.4 shows the detail of the system. The camera is placed
2300 [mm] away from the subject. We only recorded either
left or right side of the walking posture. We put LED markers
on acrominon, iliac crest, caput fibulae, lateral malleolus andthe 5th metatarsal caput of the subject. Hereafter we call the 5
LED markers Marker 1, Marker 2, Marker 3, Marker 4, andMarker 5 in the order listed before. Fig. 5 (a) shows thedefinition of the coordinate frame and the marker positions.
Note that the right side is assumed to be forward direction in
Fig.5. Here is the reason why we used the 5 markers and theirpositions:--First, we can detect the corresponding bone positions inspite of the existence of the skin, and then we can easily andrelatively accurately attach the markers on the desired
positions.
--Second, 5 is the minimum number to get the information

(1)

(2)

(3)

(4)

Hemi-foot step length

Fig. 8. Definition of hemi-foot step length

(5)

(6)

(7)

(8)

Fig. 6. Captured walking motion in one cycle

Fig. 7. Estimated marker position based on the tracked point by KLT
filterabout the angles of the hip, knee, and ankles. Note thatrigorous accurate angles are not necessary, but angle
information for differentiating the diseases is needed.
B. Method
The LED markers were attached on the leg where thepatient has disorder. The subjects walked on the treadmill insemidarkness so that only the lights of the LED markers canbe captured by the camera. Before the experiment, thesubjects took a practice to walk on the treadmill. This practiceincluded the two purposes: getting used to walk on thetreadmill for safety, and setting the speed of the treadmill. We
decided the speed so that the subject can normally walk. If thesubject felt pain, then we stopped the measurement. If thesubject did not feel pain, the subject walked for 10 minutes.
Fig. 6 shows the overview of the captured walking motion
image for healthy person. It corresponds to one cycle of thewalking. The subjects are 13 normal healthy persons (4males and 9 females), 15 LSS patients (8 males and 7
females), and 8 PAD patients (7 males and 1 females).
C. Deriving marker positions
We got the image in which the areas around the markers
were white and the other areas were all black. Then, by
tracking the white areas, we got every marker positions. Fig.6
shows the images in which the marker positions (featurepoints) are connected by while lines.
The detail procedure is as follows. Firstly, using KLT filter[11], we detected the positions near the markers.

Unfortunately, the white areas were not constant but varied
due to, for example, the change of the subject motion speed,
and reflection of the LED light off the treadmill. Therefore,
the tracked point by KLT filter did not always coincide withthe center of the white area. Then, we recalculated the center
position of every white area, based on the tracked points. First,
we set the quadrangle area around the tracked points. Then,we extended the area size until the all edges of the area did notinclude the white area. Then, we got the quadrangle area
which had only one white area. We calculated the geometricalcenter of the white area in the quadrangle area. It is theobtained marker position (see Fig.7).
D. Derived data
1) Angle: As shown in Fig.5 (a), we used the relative
coordinate whose origin is located at Marker 2 attached on
iliac crest. We derived Angle I, Angle II, Angle III and Angle
IV as shown in Fig.5 (b). Angle I is the angle between x axis
and upper body (the link belonging to half plane y 0). It
corresponds to the anteverted angle of the upper body. Angle
II is the angle between x axis and the lower body (the linkbelonging to half plane y 0 and connecting to Marker 2). It
corresponds to the bending angle of hip joint. Angle III
corresponds to the bending angle of knee joint. Angle IV
corresponds to the dorsiflexion angle of ankle joint. Note thatthese angles are not completely identical to joint angles, butthey are enough for disease differentiation.
2) Stance and swing phases: We present the way to derivestance phase starting time and swing phase starting time fromonly the captured images (without any other sensors such asfoot switch or force plate). We focus on the motion of Marker
5 attached on the 5th metatarsal caput. We consider the time
when the x component of the 5th metatarsal caput position is
maximum (the moving direction is x direction), namely when
the foot reaches its most forward position. We define the timeis the stance phase starting time. We also consider the time
when the x component of the 5th metatarsal caput position isminimum, namely when the foot reaches its most backward
position. We define the time is the swing phase starting time.
3) Hemi-foot step length: Fig. 8 shows the definition ofhemi-foot step length. Note that in Fig. 8 walking motion isassumed to be captured from the right side of the subject, andthen the right side is forward. The dot line in Fig.8 expresses
the right leg in the case when it lands on the belt of thetreadmill (stance phase starts). The solid line expresses theright leg in the case when it leaves from the treadmill (swing
phase starts). We define the hemi-foot step length as the
distance that the foot (Marker 5) moves on the treadmill in(a) Normal(a) Nromal(a) Nromal(b) PAD(b) PAD(b) PAD(c) LSS(c) LSS(c) LSS

Fig. 9. Angle III

Fig.10. Angle IV

one cycle. We normalized hemi-foot step length with the leg
Fig. 9.(the
Angle
III
lengthsummationof the length between Marker 2 andMarker 3 and the length between Marker 3 and Marker 4).
We derived hemi-foot step length by using the position ofMarker 5 at stance and swing phase starting times.
III. RESULTS
Fig. 9, Fig. 10 and Fig. 11 show the experimental results
for representative subjects, in which the features we foundappeared saliently (Later we show we got statisticalsignificant difference with respect to the features). Fig.9
shows the time-series data for Angle III corresponding to thebending angle of knee joint. (a) is for normal healthy subject.
(b) is for PAD patient. (c) is for LSS patient. Fig 10 shows thetime-series data for Angle IV corresponding to thedorsiflexion angle of ankle joint. Fig.11 shows the averagevalues for hemi-foot step length. In Fig. 9 and Fig. 10, theblack lines express the derived data from the walking motion

Fig.11. Hemi-foot step lengthfor 10 seconds just after the walking starts while the greylines express the derived data from the walking motion for 10
seconds just before the walking stops. In Fig.11, Start andEnd denote the average values of hemi-foot step lengths for
10 seconds just after the walking starts and before thewalking stops, respectively. Since intermittent claudication isa disorder that patients feel pain at their leg after walking for awhile, we compared the data just after the walking starts withthe data just before the walking stops.
A. Bending angle of knee joint
Here, we discuss the data of Angle III corresponding to thebending angle of knee joint shown in Fig. 9. As shown in
Fig.9 (a), the wave form for normal healthy person includes awave form like the letter M, which means there are two local
maximum and one local minimum values. It reaches its first
local maximum when the foot lands on the treadmill(corresponding to the start of stance phase and the posture* : p < 0.05

*

170

160
150

*

140
130

PAD

LSS

Fig. 12. Average angle of Angle III at the start ofstance phase

0.8

*

*

Normal

PAD

0.6

120

0.4

110

0.2

100

Normal* : p < 0.05

1

Length [-]*180* : p < 0.05

150

Angle [degree]

Angle [degree]

190

0Normal

PAD

Fig. 13. Average angle of Angle IV

shown in Fig. 6 (5)). Subsequently, knee joint bends a little
bit for standing, and we get local minimum (corresponding
postures are shown in Fig. 6 (6)-(8)). After that, to kick thebelt to leave from the treadmill, the knee joint is extended andwe get local maximum again (corresponding posture is shownin Fig. 6 (2)).
We focus on the bending angle of knee joint at the start ofstance phase (corresponding posture is shown in Fig. 6 (5)).
The angle for PAD patients was small comparing with it fornormal healthy persons and it for LSS patients. The small
angle for PAD patients is considered to be resulted from a gait
strategy of a biophylactic response to crural muscle(musculus triceps surae and soleus muscles) which is most apt
to go to ischemia due to walking load [1]. The two main
mechanisms can be considered for it. One is that bending
knee joint makes popliteal artery relaxed and then the
diameter of the corresponding blood vessel increases.
Therefore, we can deliver blood to crural muscle minimizing
the loss of the blood flow at the knee joint in spite of thedecrease of the blood flow at the upstream due to stenosis.
The other one is the relaxation of crural muscle resulted fromthe flexion of knee joint. If crural muscle is relaxed, thenexternal pressure to small blood vessel inside the muscle
decreases, and then collapse and stenosis of blood vessel do
not apt to cause. Then, we can decrease the effect of thedecrease of blood flow due to arterial disease at the upstream.
In case of LSS patients, the change of the bending angle wasrelatively small in swing phase, but the angle itself was not
small especially at the start of stance phase.
Concerning this, we investigated the average values of thebending angle of knee joint at the start of stance phase. As it
can be seen from Fig.9, there were little differences between
the data just after the walking starts and the data just before
the walking stops. Then, we focused on the data just after thewalking starts. Fig. 12 shows the results. It shows that thebending angle for PAD patients is smaller than those fornormal healthy persons and for LSS patients. We conductedstatistical t test to the data. We got statistical significant
differences between normal healthy persons and PAD
patients and between LSS patients and PAD patients at the
5 % significant level. From these results, it can be said that the
average bending angle of knee joint at the start of stancephase can be used as a factor for the disease differentiation.

LSS

LSS

Fig. 14. Average length of hemi-foot step

B. Dorsiflexion angle of ankle joint.
Here, we discuss the data of Angle IV corresponding to thedorsiflexion angle of ankle joint shown in Fig. 10. Spiked
peak can be seen in Fig.10 (a). This spike peak means strong
kicking at the moment when the leg leaves from the treadmill(corresponding posture is shown in Fig.6 (3)). After theleaving, the walking goes to swing phase. After that, the heellands on the treadmill, flexing the ankle joint (stance phasestarts), and then the ankle joint is extended to place the wholepart of the foot on the floor (corresponding posture is shownin Fig. 6 (5)). After that, as the foot goes backward due to the
motion of the treadmill, the ankle joint is flexed(corresponding postures are shown in Fig. 6 (6)-(8) and (1)).
From Fig. 10, it can be seen that kicking‟s of LSS and PAD
patients at the moment when the leg leaves from the treadmill
were weaker than that of normal healthy persons. In addition,
the average value of the dorsiflexion angle of ankle joint was
small for LSS patients while it was large for PAD patients,
comparing with that for normal healthy persons.
In case of PAD patients, if the amplitude of thedorsiflexion angle of ankle joint is large, the leg needs large
amounts of blood, and ischemia could cause. Therefore, PAD
patients do not move the ankle joint, and keep the amplitude
small. On the other side, decreasing the dorsiflexion angle ofankle joint means extending calf muscle, and it leads tocollapse the blood vessel of the calf. Then ischemia could
cause and the PAD patients feel pain. To prevent thissituation, they are considered to keep the dorsiflexion angleof ankle joint large.
LSS patients feel pain due to external press to spinal tissue
by bone or soft tissue. Then, the pain can be relaxed if thepatients bend forward [10]. Therefore, the feet of the LSS
patients are apt to be placed backward comparing with thegravity center during the walking. It means the angle between
the treadmill and the lower thigh is small. The angle
corresponds to Angle IV (the dorsiflexion angle of ankle
joint). Then its average value tends to be small.
Concerning this feature, we derived the average value ofthe dorsiflexion angle of ankle joint. As it can be seen from
Fig.10, there was little difference between the data just after
the walking starts and the data just before the walking stops.
Then, we focused on the data just after the walking starts. Fig.

13 shows the results. From Fig. 13, it can be seen that the
average angle for LSS patients was smaller than that for PAD
patients. It coincides with the results shown in Fig.10. We
conducted statistical t test and got statistical significant
difference between LSS patients and PAD patients at the 5 %significant level. From this result, it can be said that the
average value of the dorsiflexion angle of ankle joint can beused as a factor for the disease differentiation.
C. Hemi-foot step length
Here, we discuss the data of hemi-foot step length shown in
Fig. 11. The hemi-foot step lengths for LSS and PAD patientswere smaller than that for normal healthy persons. The
patients suffering from disorder in walking are apt to take thefollowing walking strategy to prevent the pain at lower limbs
and make the walking stable: to shorten the duration for
putting the weight on the disorder leg. It is considered to be
one of the reasons why the hemi-foot step length was small
for PAD and LSS patients.
Concerning this feature, we derived the average value ofthe hemi-foot step length with respect to the data just after thewalking starts since there was little difference between thedata just after the walking starts and the data just before thewalking stops. Fig. 14 shows the results. From Fig. 14, it canbe seen that the average lengths for LSS and PAD patients are
smaller than that for normal healthy persons, similarly to theresults shown in Fig.11. We conducted statistical t test andgot statistical significant differences between normal healthy
persons and LSS patients and between normal healthy
persons and PAD patients at the 5 % significant level. Fromthese results, it can be said that the average value of thehemi-foot step length can be used as a factor for the diseasedifferentiation, especially to differentiate normal healthy
persons and patients.
D. Discussion
From Fig.9, Fig.10, and Fig.11, it can be seen that there
were little differences between the data just after the walking
starts and the data just before the walking stops. It means thatthe symptom of the disorder appeared from the start of thewalking. Namely, the walking motion data for 10 seconds justafter the walking starts is enough to analyze and differentiate
the diseases. We do not need the whole walking motion fromthe start to the time when the patients feel pain. It means thepatients do not have to walk until they feel pain for theexamination, and only have to walk for several seconds.
On the other side, we detected the three factors for diseasedifferentiation from the 2 dimensional motion image analysis.
Then, we can construct simple measuring system which evenperson (for example, medical doctor at small clinics) who
does not have special professional knowledge can use.
IV. CONCLUSION
This paper investigated the walking motions of normal
healthy persons, PAD and LSS patients, aiming at the main
problem identification of the patients suffering fromintermittent claudication. The main results are as follows.
1. We showed that simple measuring system for walking isenough for the disease differentiation. We attached handmade
LED markers on the 5 feature points of the subject andrecorded the walking motion of the subject on the treadmill
with commercial cheap camera. We only have to measure themotion of the limb where disorder causes from only one side,and then we need only one camera to measure the walking.
Since the treadmill was used, walking motion can bemeasured in a small room which can be easily provided evenin small hospitals and clinics. Even non-professional people
such as medical doctors at small clinics can measure thewalking.
2. We showed that: a) we can get enough information forthe disease differentiation from 2 dimensional motion image(we do not need 3 dimensional information); b) Analyzing
walking motion for 10 seconds just after the walking starts isenough for the disease differentiation, and then the patients
can stop walking before feeling pain.
3. We derived 3 factors for the disease differentiation;
average angle of Angle III (corresponding to bending angleof knee joint) at the start of stance phase, average angle ofAngle IV (corresponding to dorsiflexion angle of ankle joint),
and average hemi-foot step length. We will be able toconstruct the disease differentiation method/system by using
3 factors. It is our future work.
REFERENCES[1]

Y. Toribatake et al., “Classification and Differential Diagnosis ofIntermittent Claudication,” Spinal Osteomyelitis Journal, vol. 21, no. 4,
2008, pp.333-340.
[2] Y. Toribatake et al., “The frequency and differential diagnosis ofperipheral arterial occlusive disease in intermittent claudicants inorthopaedics,” Orthopaedic surgery and traumatology, vol. 45, no. 6,
2002, pp. 665-674.
[3] Y. Toribatake et al., “Vascular and neurogenic intermittent
claudication,” Cardioangiology, vol. 56, no. 1, 2004, pp. 50-56.
[4] M. P. Murray, A. B. Drought, and R. C. Kory, “Walking patterns ofnormal men,” the journal of bone and joint surgery, vol. 46-A, no. 2,
1964, pp. 335-360.
[5] M. P. Murray, R. C. Kory, and S. B. Sepic, “Walking patterns of normal
women,” Archives of physical medicine & rehabilitation, vol. 51, 1970,
pp. 637-650.
[6] K. Yamanaka et al., “Localization of Walking or Running User with
Wearable 3D Position Sensor,” Technical report of IEICE. Multimedia
and virtual environment, vol. 106, no. 234, 2006, pp. 115-120.
[7] K. Kobara et al., “The Effect of Ankle Joint Rigidity in Plastic
Ankle-Foot Ortho ses on the Ankle and Knee Joint Moments ofHemiplegics in the Walk-ing Stance Phase,” Kawasaki medical welfare
journal, vol. 16, no. 2, 2006, pp. 299-304.
[8] A. Tokura, “Kinesiologic and Kinematic Analysis of Walking Pattern
on Osteoarthritis of the Hip,” J. Jap. Orthop. Ass., vol. 48, no. 1, 1974,
pp. 1-11.
[9] A. Tanabe et al., “Treadmill gaint analysis of pre/post operation in total
hip replacement,” Congress of Japanese Private Medical College
Physical Therapy, vol. 22, no. 1, 2005, pp. 17-20.
[10] K. Takahashi et. al., „„Changes in epidural pressure during walking inpatients with lumbar spinal stenosis,‟‟ Spine, vol.20, 1995,
pp.2746-2749.
[11] Bruce D.Lucas, Takeo Kanade, “An lteretive Image Reg-istration
Technique with an Application to Stereo Vision,” Proc. 7th Int. Conf.
on Artificial Intelligence (IJCAI), 1981, pp.674-679.