A Study of Gait Analysis with A Smartphonefor Measurement of Hip Joint Angle

Arinobu Niijima∗ and Osamu Mizuno∗ and Tomohiro Tanaka∗∗NTT Service Evolution Laboratories

E-mail: {niijima.arinobu, mizuno.o, tanaka.tomohiro}@lab.ntt.co.jp Tel: +81 46 859 4672

Abstract—Due to the enhanced performance of recent smart-phones, some studies use them for gait analysis. An accelerometerin a smartphone can be used to measure gait parameters suchas steps and walking speed. Some researchers proposed methodsof measuring these parameters with a smartphone, but they didnot propose methods of measuring joint angles, which are typicalparameters for gait analysis. In this paper we propose a methodto measure hip joint angle with a smartphone by putting it in afront trouser pocket. We conducted an experiment to verify theaccuracy of the proposed method. We compared the measuredhip joint angle with a 3D system and a smartphone. The resultsshowed that the coefficients of determination were about 0.7 -0.9 and the root mean square error was about 4 - 6 degrees.

I. INTRODUCTION

Gait analysis is important for the aging society because itcan assist in diagnosis of joint disease of the elderly [1]. Somegait parameters such as walking speed and walking cycle areuseful as indices of fall risk [2].

Many methods exist to analyze gait. In a hospital, physicaltherapists observe patient’s gait. Some hospitals have a threedimensional motion analysis system (3D system) and forceplates to analyze gait. However, there are too few therapistsand the machines are expensive for widespread use.

In this paper, to achieve low-cost, pervasive gait measure-ment, we propose a method of gait measurement with asmartphone. The merits of using a smartphone are as follows,

• Measuring some gait parameters with a smartphone ispossible because it includes motion sensors such as anaccelerometer and a gyro sensor.

• Smartphones are carried everywhere because they arewidely adopted and become an essential item.

The issue of using a smartphone for gait analysis is lim-itation of measurable parameters. Specifically, there are nopractical methods of measuring joint angles with a smartphone.However, joint angles are important parameters for gait anal-ysis because some joint diseases such as Parkinson’s diseaseare diagnosed by changes of joint angles [3]. They are alsouseful to detect abnormal gait [4].

In our study, we measure “hip joint angle” with a smart-phone placed in a front trouser pocket. Figure 1 shows hipjoint angle, which is configured by three angles; flexion andstretching, abduction and adduction, external rotation andinternal rotation. Hip joint angle is important for gait analysisbecause it correlates with movement of legs. First, we considerto measure flexion and stretching angle, which is the biggestmovement of three angles. It is useful for not only diagnosis

Fig. 1: Hip joint angle

of joint diseases but also calculating other gait parametersgeometrically [5]. In addition, putting a smartphone in atrouser pocket is user-friendly because the location is wheremost people put smartphones while walking [6].

II. RELATED WORKS

Several methods have been proposed to measure gait witha smartphone. The representative parameters of gait analysisare steps, walking speed, stride length, walking cycle, and jointangles [7], [8].

Mladenov and Mock proposed the use of a smartphonewith peak detection technology to count steps [9]. Theycompared the accuracy of the method with the smartphonein several carry locations. The measurement error with thesmartphone detached from the body was bigger than that withthe smartphone attached to the body.

Brajdic and Harle applied common walk detection andstep counting algorithms to acceleration data of a smartphone[10]. They surveyed various algorithms putting a smartphonein different locations. They described that standard devisionthresholding can reliably detect walking, and windowed peakdetection would be an optimal choice for step counting.

Other researchers also proposed methods of gait analysisvia a smartphone [11], [12]. However, they did not proposemeasuring method of joint angles with a smartphone.

There are some methods to measure hip joint angle with aconstrained gyro sensor attached on the body [13], [14]. Oneway is to integrate the angular velocity of a specific axis thatvertically intersects the sagittal plane. However, it is difficultto achieve the same results with an unconstrained smartphonein a trouser pocket because an initial posture is ambiguous andthe equation for estimating hip joint angle is different.

978-616-361-823-8 © 2014 APSIPA APSIPA 2014

III. PROPOSAL METHOD

Our proposal method to measure flexion and stretchingangle of hip joint is to put a smartphone into a front trouserpocket and use a gyro sensor. It represents angler velocity andwe integrate angler velocity of three axes (X,Y, Z) to calculaterotation angles of them. We set following hypotheses;

• A front trouser pocket follows the leg motion.• Abduction and adduction angle is much smaller than

flexion and stretching angle.• A trouser pocket hardly moves by external rotation and

internal rotation of leg motion.Based on these hypotheses, gyro sensor data of the smartphonecorrelate with flexion and stretching angle of hip joint, and itis assumed that flexion and stretching angle is calculated byfollowing equation; θ = aX + bY + cZ + d (where “θ” is hipjoint angle, “X,Y, Z” are rotation angles of each axis, “a, b, c”are regression coefficients, “d” is an intercept; “a, b, c, d” aredetermined by multiple regression analysis).

IV. EXPERIMENT

A. Experimental methodWe conducted an experiment to verify our proposal method

to measure hip joint angle. We used a smartphone (SamsungGalaxy S4) and a 3D system (MA-8000, Anima Corporation),which we employed for reference data. We applied multipleregression analysis to the rotation angles of the three axes ofthe smartphone. The coefficients of determination (R2) and theroot mean square error (RMSE) were calculated to evaluate theaccuracy of the proposed method.

Subjects were 7 males and 7 females who were 18 - 22 yearsold, and 4 males and 4 females who were 64 - 80 years old.All were healthy and worn their own trousers. The size andthe position of the pockets were not the same. The subject putthe smartphone into the front left trouser pocket in the sameposture. 10 markers were put on each leg for the 3D system.Sampling rate of the smartphone was about 15Hz while thatof the 3D system was 250 Hz. The gyro sensor data of thesmartphone and the position coordinates of the markers on thelegs were recorded. We set flexion angle as positive numberand stretching angle as negative number. Each subject walked3 m 3 times.

We analyzed the data gathered in periods when the positionsof all markers were recorded correctly. We integrated theangular velocity of the three axes of the smartphone tocalculate the rotation angle, applied an IIR filter for smoothing,and applied drift correction. The equation of IIR filter wasy(t) = 0.1 ∗ x(t) + 0.9 ∗ y(t − 1) where y(t) is output dataand x(t) is input data. The drift correction was conducted byaddition and subtraction of linear function. We used linearinterpolation between each sample. The rotation angle data ofthe smartphone and the hip joint angle data measured with the3D system were compared at 50 ms intervals. We conductedmultiple regression analysis using stepwise selection and crossvalidation for each trial. R2 and RMSE were calculated bycomparing with the 3D system data and the smartphone data.

TABLE I: The results of cross validation

test data R2 RMSE1-1 0.91 4.761-2 0.81 6.151-3 0.72 7.862-1 0.72 7.942-2 0.96 3.092-3 0.96 2.843-1 0.87 5.273-2 0.84 5.913-3 0.84 6.204-1 0.91 4.244-2 0.74 6.754-3 0.87 5.025-1 0.92 4.005-2 0.96 2.655-3 0.64 8.086-1 0.90 3.776-2 0.71 6.526-3 0.85 4.587-1 0.81 5.537-2 0.93 3.507-3 0.70 7.128-1 0.93 3.528-2 0.81 5.748-3 0.88 4.509-1 0.90 4.089-2 0.87 4.819-3 0.93 3.47

10-1 0.61 7.2010-2 0.84 4.5510-3 0.90 3.8011-1 0.71 7.2311-2 0.93 3.7811-3 0.74 6.87

test data R2 RMSE12-1 0.96 2.7012-2 0.77 6.6212-3 0.88 4.6913-1 0.96 2.8413-2 0.93 3.6713-3 0.93 3.4414-1 0.90 4.6814-2 0.86 5.8814-3 0.89 4.5915-1 0.76 5.8515-2 0.92 3.5915-3 0.86 4.7116-1 0.53 7.7816-2 0.83 4.6616-3 0.78 5.4117-1 0.83 4.3217-2 0.85 4.3017-3 0.86 3.9418-1 0.89 4.3218-2 0.94 3.5018-3 0.91 4.5719-1 0.84 6.3419-2 0.90 4.8319-3 0.80 7.2620-1 0.89 4.9820-2 0.92 4.1720-3 0.93 3.9621-1 0.69 6.8621-2 0.65 7.1721-3 0.84 5.0222-1 0.98 2.1722-2 0.93 3.5022-3 0.94 3.72

B. Results

Table I shows the results of cross validation. R2 was about0.7 - 0.9 and RMSE was about 4 - 6 degrees. There was nobig difference among them due to gender or age.

Figure 2 and Figure 3 compares the measured hip joint anglemeasured with the 3D system and the smartphone. Figure 2shows the results of higher R2 subjects and Figure 3 showsthe results of lower R2 subjects. Figure 3 shows the error wasbigger at heel contact, which is maximum and minimum valueof the hip joint angle.

C. Discussion

We discuss about the error of the hip joint angle measuredwith the 3D system and the smartphone. The causes ofmeasurement error are vibration at heel contact, drift of thegyro sensor, and failure of the pocket to follow leg motion.For noise reduction, we will have to detect heel contact. Itis not so difficult because we can use acceleration sensor ofa smatphone [9]. The drift error seemed to be small becausewe conducted drift correction and the measurement time wasshort as 2000 - 3000 ms. We suppose the R2 variance amongsubjects is caused by the individual variation of the physiqueand the variation of the pockets. It is because our proposalmethod is based on the hypothesis that the front trouser pocketfollow the leg motion, which is depend on the physique and the

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Fig. 2: Hip joint angle measured with the 3D system and the smartphone (higher R2 subjects)

pocket. In the future, we will conduct an evaluation experimentto verify the cause of error. In addition, we will have tothink about a calibration method without 3D system for dailyuse. We suppose that some daily action can be utilized forcalibration such as “sitting on a chair” and “standing”. Thedifference of hip joint angles in each posture is about 90degrees.

V. CONCLUSIONS

In this paper, to achieve low-cost, pervasive gait measure-ment, we proposed a method to measure hip joint anglewith an unconstrained smartphone in a front trouser pocket.We conducted an experiment to verify the accuracy of theproposed method. We compared the hip joint angle measuredwith the 3D system and the smartphone. The results showedR2 was about 0.7 - 0.9 and RMSE was about 4 - 6 degrees.

In future work, we will conduct another experiment for noisereduction and a new calibration method.

VI. ACKNOWLEDGEMENT

This experiment was conducted in Kio University, whichhad an ethical review (H25 - 23).

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Fig. 3: Hip joint angle measured with the 3D system and the smartphone (lower R2 subjects)

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