1. TITLE PAGE

Full title of the paper: Identifying biomechanical gait parameters in adolescent boys with haemophilia

using principal component analysis

Authors

Luke Benjamin Suckling

David Stephensen

Mary Christine Cramp

Ryan Mahaffey

Wendy Isobel Drechsler

Address (work carried out)

School of Health, Sport & Bioscience, University of East London, Stratford, London, United Kingdom

Author Correspondence

David Stephensen

Kent Haemophilia & Thrombosis Centre

Canterbury, United Kingdom

Telephone: 01227 783166

Email: david.stephensen@nhs.net

Running title: Gait deviations in adolescent boys with haemophilia

Key words: Gait, Biomechanics, Adolescence, Haemophilia, PCA, Ankle

Footnote

Present addresses of the authors:

Luke Benjamin Suckling: (as above work carried out address)

David Stephensen (as above author correspondence address)

Mary Christine Cramp: Allied Health Professions, University of the West of England, Bristol, UK

Ryan Mahaffey: School of Sport, Health and Applied Sciences, St Mary’s University Twickenham, UK

Wendy Isobel Drechsler: Faculty of Life Sciences & Medicine, Kings College London, London, UK

Manuscript Word Count: 2,642 words (limit 3,000 words)

2. ABSTRACT

Introduction: Improvements in the medical management for those with haemophilia have resulted

in improved clinical outcomes. However, current treatment regimens do not alleviate all joint

haemarthroses with the potential for long-term joint deterioration remaining. The evaluation of

functional activities such as gait, using standardized tools to monitor children with haemophilia is

emerging. Aim: This study explored differences in sagittal plane biomechanics of walking in

adolescent boys aged 11-18 years with haemophilia and an age-matched group of typically

developing boys. Methods: A motion capture system and two force platforms were used to collect

sagittal plane kinematic, kinetic and temporal spatial data during level walking. Principal component

analysis was applied to kinematic and kinetic waveform variables. Group differences in temporal

spatial and principal component scores for each kinematic and kinetic variable were evaluated using

independent t-tests. Results: Significant alterations (p < 0.05) in temporal spatial and kinetic

parameters were found in adolescent boys with haemophilia. Compared to typically developing

adolescent boys, boys with haemophilia walked with reduced stance phase duration and altered

pattern of external ankle joint moments during push off and the beginning of swing. Conclusion: The

use of principal component analysis (PCA) rather than predetermined discriminatory variables

provided additional insight into biomechanical alterations in adolescent boys with haemophilia, with

adaptations occurring during terminal double support and early swing, affecting the ankle joint. This

finding might be a key biomechanical marker that could be used to evaluate the joint function and

the progression of early haemophilic arthropathy.

Word count: 246

3. MAIN BODY OF TEXT

INTRODUCTION

Current evaluation of the physical status of joints is monitored radiologically using x-ray and MRI [1].

Investigations such as these focus on joint structure and integrity providing little information on joint

function and performance. In addition, regular multi-joint investigation is expensive, time consuming

and challenging in children due to movement artefact. The development of more recent

haemophilia specific clinical tools has been used to evaluate functional limitations but are based on

symptoms of end stage musculoskeletal impairment. Stephensen et al., evaluated sagittal plane gait

biomechanics and reported subtle alterations in joint motion and moments of force to be early

musculoskeletal impairments following lower limb haemarthrosis [2].

Increasingly, motion capture technology is being used to evaluate movement disorders and provide

details about mobility imperceptible to the naked eye [2-5]. Bladen et al., evaluated temporal-spatial

walking parameters using a GAITRite electronic walkway in 20 adolescent boys with severe

haemophilia aged 7-17 years compared to age matched control subjects and reported increased

swing, reduced stance, increased single support times and reduced double support times in the

group of boys with haemophilia [3]. Stephensen et al., evaluated 14 preadolescent boys with

haemophilia aged 7-13 years with a history of ankle joint bleeding using a three-dimensional (3D)

motion capture system and two force platforms and reported: greater flexion angles at the knee

during early to mid-stance and swing phase of gait, greater external moments at the knee

throughout stance, greater ankle plantarflexion external moments during early stance and lower hip

flexion external moments during mid stance [2]. In contrast to the findings of Bladen et al., no

alterations were found in temporal spatial parameters between the groups. Forneris et al.,

evaluated 42 children and adolescents with haemophilia aged 4-18 years using a 3D motion capture

system to calculate the Gait Deviation Index and Profile Scores. Compared to normative reference

data, children with haemophilia were found to walk with functional gait alteration [4]. Lobet et al.,

evaluated the walking patterns of eighteen adults with haemophilia (aged 40 ± 10 years), reporting

gradual infra-clinical alterations in temporal spatial, kinematic and kinetic parameters in those with

advanced joint pathology [5].

Previous studies evaluating gait biomechanics in those with haemophilia [2-3, 5] have evaluated

parameterised values, such as maximum and minimum joint angles extracted at specific points of

the gait cycle (for example, heel strike) [2-3, 5]. However, such techniques ignore the pattern of

movement that occur between these predetermined points. The use of waveform analytical

techniques may provide additional insight into biomechanical alterations in adolescent boys with

haemophilia. Principal component analysis (PCA) is an exploratory method of data analysis in the

field of biomechanics [6-9], enabling exploration of the entire waveform and does not require an a

priori determination of variables to extract. To our knowledge, waveform statistical techniques have

not been used to examine differences in kinematic and kinetic patterns in adolescent boys with

haemophilia. Therefore, the aim of this study was to identify differences in kinematic and kinetic gait

patterns in adolescent boys with haemophilia aged 11-18 years compared to age matched typically

developing boys. It was hypothesised that the pattern of sagittal plane joint motion and moments

would be altered in adolescent boys with haemophilia.

MATERIALS & METHODS

Subjects

Two groups of children participated in this study (Table.1). Fourteen boys with haemophilia (H) and

14 age and puberty status matched typically developing boys (TD) were recruited. Puberty status

was self-rated by the participants according to the Tanner Scale [10]. Boys were excluded if they

presented with a history of lower limb fracture, major ligamentous injury or trauma to the lower

limb, orthopaedic surgery, acquired brain injury or any other disturbance to the central nervous

system or any lower limb joint or muscle bleed in the preceding six weeks prior to testing. Eleven

boys had severe haemophilia (<1 iu/dl), one had moderate haemophilia (1-5 iu/dl) and two boys had

mild form of the disease (5-50 iu/dl). Lower limb bleeding episodes over the previous 12-months

were measured using a self-report questionnaire. Ethical approval was obtained from both the NHS

and local University Ethics Committee (11/LO/1202).

Protocol

Gait analysis was performed using an eight-camera Vicon 612 (VICON Motion Systems Ltd, Oxford,

UK) system to capture and record motion of skin mounted reflective markers at 200 Hz. Two force

platforms (Bertec, Model 4020 H, MIE Ltd, UK) embedded in the laboratory floor captured ground

reaction forces during gait trials at 1000 Hz. Children wore shorts and were barefoot during testing.

Anthropometric measurements were recorded for height, mass, leg length, and knee and ankle

width. Sixteen reflective markers (14 mm) were attached bilaterally to the anterior superior iliac

spine, posterior superior iliac spine, lateral condyle of the knee, lateral malleolus of the fibula,

posterior surface of the calcaneus and midline of the lateral thigh and shank (Plug-In-Gait PiG) lower

limb model [2]. Subject preparation and measurement was performed by a single assessor (LS). Boys

were asked to ambulate at a self-selected walking speed through the capture volume. A single trial

was considered for analysis if two sequential full steps were simultaneously captured by the cameras

and force platforms. Six gait trials were captured and saved for subsequent analysis.

Data management

Marker trajectories were reconstructed using Vicon software to ensure visibility throughout the gait

cycle. Only trials where trajectories were visible over the whole gait cycle were used for analysis.

Marker trajectories were gap filled to a maximum of five frames using a cubic spline technique. The

gait cycle was defined from initial contact with the force platform (20 N threshold) to subsequent

foot contact of the same foot, with data expressed as a percentage of the gait cycle. Data from the

limb with greatest number of joint bleeds in the boys with haemophilia and the right limb from the

age matched typically developing controls were used for analysis.

Temporal spatial parameters determined from motion capture data included gait velocity, cadence,

stride distance, stride time and single and double support duration. The influence of body

anthropometrics on temporal spatial characteristics were accounted for by normalisation to the

dimensionless values described by Hof [11]. Length parameters were normalised to leg length, time

parameters to [leg length/ gravity (9.81 m/s -2)]½, and velocity and cadence parameters to

[acceleration due to gravity (9.81 m/s-2)/ leg length]½.

Data points corresponding to every 1% of the gait cycle were extracted to represent the sagittal

plane joint motion and moment waveforms of hip, knee and ankle. Kinematic data were derived

from the PiG lower limb model. Sagittal plane kinetic data consisting of external joint moments at

the hip, knee and ankle, normalised to body mass were calculated using the principles of inverse

dynamics using estimated segmental inertial properties, kinematic and ground reaction force data.

Segmental inertial properties were estimated from participant anthropometric data with ground

reaction forces obtained from the force platforms. Joint moments were smoothed using a

Butterworth filter with a cut-off frequency of 10 Hz.

Statistical analysis

Statistical analysis were performed in SPSS version 20.0. Data were assessed for normality of

distribution using the Kolmogorov-Smirnov test. Waveform matrices for sagittal plane kinematics

and kinetics were constructed on 28 subjects and corresponding data points (kinematic matrices: 28

x 101), (kinetic matrices: 28 x 101). Waveform matrices were transformed into principal components

following eigenvector analysis of the covariance structure. Variation in the waveforms data were

extracted by rotating the variables using orthogonal rotation into components that maximally

explain variance in original waveforms. To interpret which factors contribute to a given principal

component, the rotated components were used for analysis. Rotated factor loadings were evaluated

to determine which aspect of the gait cycle contributed to each principal component (PC). Rotated

factor loadings ± 0.748 were considered as contributing to a component [12]. Factor scores were

calculated for each participant for extracted PCs, providing a measure of magnitude and direction of

deviation from the mean gait curve [7]. For each component factor score, between-group

comparisons using independent t-tests were performed. Statistical significance was set to p<0.05.

RESULTS

Joint haemarthrosis history

Median and inter-quartile range (IQR) of lower limb joint bleeding reported by the H boys over the

preceding 12 months was 1.00 bleed (IQR: 2.00). The ankle joint was the most frequent site of

bleeding (0.5 bleeds; IQR: 1.75), followed by the knee (0 bleeds; 1.00) and hip (0 bleeds; 0.00) joints.

Six boys with haemophilia reported no haemarthroses in the previous 12-months prior to testing,

with 8 boys reporting at least one lower limb joint bleeding episode during this period.

Temporal spatial parameters

Absolute and normalised temporal spatial (TS) parameters are presented in Table 2. Stance phase

duration was significantly lower and swing phase significantly greater in the H boys compared to TD

boys (between-group difference 1.2%; p<0.05). No other significant between-group differences were

observed during level walking.

Sagittal plane kinematics

Table 3 presents the results of PCA on sagittal plane joint motion of the hip, knee and ankle joints.

Variation in lower limb joint motion waveforms was explained by three hip, four knee and six ankle

joint PC’s. No significant between-group differences were found for retained PC factor scores (Figure

1).

Sagittal plane kinetics

Table 4 presents the results of PCA on sagittal plane joint moments of the hip, knee and ankle and

vertical ground reaction force (VGRF). Variation in lower limb joint kinetic waveforms was explained

by; six hip PC’s, six knee PC’s and six ankle PC’s. Three VGRF PC’s were identified. Factor scores for

ankle joint moment PC2, representing the end of stance and beginning of swing, were significantly

lower in the H boys compared to the TD boys (TD: 0.20 ± 0.18, H: -0.20 ± 0.26; p<0.05, Table 4 and

Figure 2). No significant between-group differences were found for retained PC factor scores for the

hip and knee joints or VGRF waveforms.

DISCUSSION

The aim of this study was to determine whether walking patterns of adolescent boys with

haemophilia differed from typically developing boys. We identified shorter stance duration and, by

utilising PCA, showed alterations in ankle joint moments during push off and at the beginning of

swing phase in boys with haemophilia, compared to their typically developing peers. However, no

differences in joint kinematics were identified. These findings partly support our hypothesis that

lower limb joint angular motion and moments would be altered in the H group of boys. Furthermore,

waveform analysis identified alterations in movement patterns not previously reported in adolescent

children with haemophilia.

Boys with haemophilia spent significantly less time (1.2%) in stance phase and more time in swing

phase compared to those without haemophilia. It is acknowledged that this difference is small and

whether this finding is clinically relevant is not currently known. The shorter stance phase concurs

with the study of Bladen et al., who found significant reductions (group difference: 2.52%) in an

adolescent group of hemophiliac boys with no radiographic evidence of joint pathology (mean age:

12.7 ± 2.5 years) compared to typically developing boys (mean age: 12.0 ± 2.0 years [3]. Lobet et al.,

also reported significant alterations in stance phase duration (mean difference: 0.4%) between

repeated testing 18 ± 5 weeks apart (range 13-33 weeks) in adults with haemophilia (aged 40 ± 10

years) [5]. In contrast, Stephensen et al., reported comparable stance phase duration in a younger

group of boys with haemophilia aged 10.43 ± 2.13 years, despite kinematic and kinetic impairments

[2].

The mechanism for the subtle reduction in stance phase duration observed in the haemophilic boys

is not clear from the current study. Although, annual lower limb joint bleeding rates in the preceding

12 months were low and not confirmed by clinical records, the walking pattern alterations found in

the haemophilic boys in the current study might be a protective mechanism due to early blood-

induced arthropathy. Future studies exploring early signs of arthropathy and gait are required.

Secondary to concerns regarding the accuracy of self-reported records [13] and the small sample

size evaluated in the current study, no further analysis on the bleeding history data was performed.

Reductions in stance phase duration have previously been reported in adults with medial knee

arthrosis [14] and proposed to occur as a result of altered walking speed [15]. The finding of reduced

stance duration despite comparable gait velocity in the boys evaluated in this study, suggests the

presence of an alternate underlying adaptive strategy in adolescent boys with haemophilia.

Factor scores for ankle joint kinetics at the end of stance and beginning of swing (PC2) were

significantly different in the H boys compared to the TD boys. Inspection of the moment curves and

PC loading plots (Fig. 1) suggest that the external ankle dorsiflexor moment toward the end of stance

may be reduced or declining at a different rate together with a larger external ankle plantarflexor

moment in early swing in the boys with haemophilia when compared to the typically developing

boys. External joint moments are counteracted by opposing internal muscle moments. The actions of

pre-swing are commonly referred to as push off and relate to limb progression and foot clearance

for the subsequent step. The finding of reduced external ankle dorsiflexor moment at the end of

stance reported in the current study may be equivalent to reduced ankle plantarflexor muscle

activity and subsequent push off. Stephensen et al., examined the strength of the ankle

plantarflexors in young children with haemophilia and found significant muscle weakness compared

to age matched controls [16]. Lobet et al., (2010) reported a trend towards reduced power

generated at the ankle joint at the end of stance, interpreting this as a deterioration in ankle joint

function [5]. Furthermore, the larger plantarflexor moment in early swing may reflect greater ankle

dorsiflexor muscle activity and coupled with longer swing duration may be a strategy to aid foot

clearance and minimise the potential risk of falling as a consequence of the reduced push off [17].

De Souza et al., examined postural adjustment during unexpected perturbation in children (mean

age 10.3 ± 1.3 years) with haemophilia and reported alterations in balance mechanisms in boys with

haemophilia compared to typically developing children [18].

Extracted PC’s were compared between groups in order to identify gait waveform alterations

between H and TD boys. Although we were able to make some interpretation of the biomechanical

features captured by the PC, further work is required to determine whether magnitude, phase shift

and timing features, together with additional inter subject variance are responsible for the

significant PCs identified [19] and is a limitation of the current study. Several of the extracted PC’s

also explained a relatively small amount of variation in the entire waveform and it is unclear whether

the identified alterations are clinically relevant. Future work on a larger sample is needed to confirm

our findings. The sagittal plane hip kinetic waveform also appears to be subject to noise artifact and

should be interpreted with caution. Furthermore, participants were asked to walk at a self-selected

waking speed in this study. Although walking speed was comparable between groups, individual

differences between participants may have contributed to the variability in joint motion and

moments identified [15]. Inclusion of mild and moderate disease severity types may have

additionally influenced the results of the current study. Boys with mild and moderate forms of the

disease suffer fewer haemarthrosis [20] and may be less prone to sub-clinical bleeding episodes than

those with severe forms of the disease [21].

CONCLUSION

This study presents novel information evaluating sagittal plane gait waveforms in adolescent’s boys

with haemophilia and those of age-matched typically developing boys. The use of PCA rather than

predetermined discriminatory variables provided additional insight into biomechanical alterations in

adolescent boys with haemophilia, with adaptations occurring during push off and early swing

affecting the ankle joint. Altered patterns of external ankle joint moments might be a key

biomechanical marker that could be used to evaluate the joint function and the progression of early

haemophilic arthropathy in children with haemophilia.

Word count: 2,642

4. ACKNOWLEDGEMENTS

The authors acknowledge and thank staff at Kent & Canterbury, Addenbrooke’s, Oxford, The Royal

London and Guy’s & St Thomas’ Haemophilia Centres for their assistance with subject recruitment,

and the children and families who volunteered to participate in the study. The study was supported

by a PhD studentship from the University of East London. The authors also acknowledge the funding

of the NIHR CAT for Nurses, Midwives and Allied Health Professionals Internship.

AUTHOR CONTRIBUTIONS

LS has contributed to the design of the study, the data collection and analysis and preparation of the

manuscript. DS, MC, RM and WD have contributed to the design of the study and preparation of the

manuscript.

DISCLOSURES

The authors have no competing interests which might be perceived as posing a conflict or bias.

5. REFERENCES

[1] Stephensen, D., Drechsler, W. and Scott, O. (2012a) ‘Biomechanics of lower limb haemophilic arthropathy, Blood Reviews, 26, pp. 213-221.

[2] Stephensen, D., Drechsler, W., Winter, M. and Scott, O. (2009a) 'Comparison of biomechanical gait parameters of young children with haemophilia and those of age-matched peers.', Haemophilia, 15(2), pp. 509-518.

[3] Bladen, M., Alderson, L., Khair, K., Liesner, R., Green, J. and Main, E. (2007) 'Can early subclinical gait changes in children with haemophilia be identified using the GAITRite walkway.', Haemophilia, 13(5), pp. 542-547.

[4] Forneris, E., Andreacchio, A., Pollio, B., Mannucci, C., Franchini, M., Mengoli, C., Pagliarino, M. and Messina, M. (2016) 'Gait analysis in children with haemophilia: first Italian experience at the Turin Haemophilia Centre.', Mar 8. doi: 10.1111/hae.12920.

[5] Lobet, S., Detrembleur, C., Francq, B. and Hermans, C. (2010) 'Natural progression of blood-induced joint damage in patients with haemophilia: clinical relevance and reproducibility of three-dimensional gait analysis', Haemophilia, 16(5), pp. 813-821.

[6] Deluzio, K.J., Astephen, J.L., 2007. Biomechanical features of gait waveform data associated with knee osteoarthritis—an application of principal component analysis. Gait & Posture, 25, pp. 86–93.

[7] Chester, V. L. and Wrigley, A. T. (2008) 'The identification of age-related differences in kinetic gait parameters using principal component analysis.', Clin Biomech (Bristol, Avon), 23(2), pp. 212-220.

[8] Leporace, G., Batista, L. A., Muniz, A. M., Zeitoune, G., Luciano, T., Metsavaht, L. and Nadal, J. (2012) 'Classification of gait kinematics of anterior cruciate ligament reconstructed subjects using principal component analysis and regressions modelling', Conf Proc IEEE Eng Med Biol Soc, 2012, pp. 6514-6517.

[9] Mahaffey, R., Morrison, S.C., Bassett, P., Drechsler, W.I., Cramp, M.C. (2016) The impact of body fat on three dimensional motion of the paediatric foot during walking. Gait & Posture, 44, pp.155-160.

[10] Tanner, J.M. (1962) Growth at adolescence (2nd Edition). Blackwell, Oxford, UK.

[11] Hof, A.L. (1996) Scaling gait data to body size. Gait & Posture, 4, pp. 222–223.

[12] Stevens, J. (2001) Applied multivariate statistics for the social sciences (4th Edn). Lawrence Erlbaum Associates, New Jersey.

[13] Collins, P. W., Bolton-Maggs, P., Stephenson, D., Jenkins, B., Loran, C. and Winter, M. (2003) 'Pilot study of an Internet-based electronic patient treatment record and communication system for haemophilia, Advoy.com', Haemophilia, 9(3), pp. 285-291.

[14] Gök, H., Ergin, S. and Yavuzer, G. (2002) 'Kinetic and kinematic characteristics of gait in patients with medial knee arthrosis', Acta Orthop Scand, 73(6), pp. 647-652.

[15] Zeni, J. A. and Higginson, J. S. (2009) 'Differences in gait parameters between healthy subjects and persons with moderate and severe knee osteoarthritis: a result of altered walking speed?', Clin Biomech (Bristol, Avon), 24(4), pp. 372-378.

[16] Stephensen, D., Drechsler, W. and Scott, O. (2012b) 'Comparison of muscle strength and in-vivo muscle morphology in young children with haemophilia and those of age-matched peers', Haemophilia, 18(3), pp. e302-310.

[17] Perry, J. (1992) Gait Analysis, Normal and Pathological Function. Slack Inc, New Jersey.

[18] De Souza, F.M., Pereira, R.P., Minuque, N.P. et al. (2012) Postural adjustment after an unexpected perturbation in children with haemophilia. Haemophilia, 18, e311–5.

[19] Brandon, S.C.E, Graham, R.B., Almosnino, S., Sadler, E.M., Stevenson, J.M. (2013) ‘Interpreting principal components in biomechanics: Representative extremes and single component reconstruction.’ J Electromyogr Kinesiol 23(6), pp.1304–1310.

[20] Van den Berg, H. M., Dunn, A., Fischer, K. and Blanchette, V. S. (2006) 'Prevention and treatment of musculoskeletal disease in the haemophilia population: role of prophylaxis and synovectomy', Haemophilia, 12 Suppl 3, pp. 159-168.

[21] Manco-Johnson, M., Abshire, T., Shapiro, A., Riske, B., Hacker, M., Kilcoyne, R., Evatt, B. (2007) 'Prophylaxis versus episodic treatment to prevent joint disease in boys with severe hemophilia.', N Engl J Med, 357(6), pp. 535-544.

Figure 1.The mean ± 2SD sagittal plane joint angles and external joint moments of hip, knee and ankle and during level walking. Blue lines represent typically developing boys; the red lines represent haemophiliac boys. The dashed lines represent ± 2SD for each group. Normalised gait cycle is defined from foot contact of one limb to subsequent foot contact of the same foot, normalised as a percentage (%). Factor loading for each principal component are plotted beneath angle/moment plots (embolden line represents significant difference between groups) Vertical grey lines indicate significant PC factor scores and percentage of the gait cycle they represent. º: degrees.Nm: Newton metres; kg: kilogram.

6. TABLES AND FIGURES

Table 1. Mean ± SD of anthropometric and sexual maturation data from the study group. TD: typically developing boys; H: Haemophiliac boys; BMI: body mass index; TSP; testicles, scrotum & penis; Composite Tanner stage: mean of TSP and hair Tanner scores; p value obtained from independent t-tests. † P value for Tanner scores obtained from Mann-Whitney tests.

TD (n= 14) H (n = 14) P value

Age (years) 14.29 ± 2.13 14.29 ± 2.16 1.00

Body Mass (kilogram) 61.14 ± 17.74 56.86 ± 17.50 0.53

Stature (meters) 1.68 ± 0.16 1.65 ± 0.14 0.56

BMI (kilogram/meters2) 21.02 ± 3.13 20.43 ± 3.79 0.66

TSP Tanner Stage† 3.79 ± 1.12 3.86 ± 1.23 0.77

Hair Tanner Stage† 3.79 ± 1.19 3.86 ± 1.35 0.70

Composite Tanner Stage† 3.79 ± 1.12 3.86 ± 1.28 0.73

Table 2. Mean ± SD of absolute and normalised temporal spatial parameters of children with haemophilia (H) (n=14) and typically developing (TD) children (n = 14). p value obtained from independent t-tests.

Absolute temporal spatial parameters TD H P value

Stride time (seconds) 1.05 ± 0.07 1.03 ± 0.06 0.45

Stride distance (meters) 1.44 ± 0.10 1.41 ± 0.14 0.58

Velocity (meters/second) 1.40 ± 0.08 1.38 ± 0.09 0.65

Cadence (steps/minute) 115.02 ± 7.62 116.53 ± 8.41 0.62

Stance phase (percent) 58.95 ± 1.34 57.75 ± 1.37 0.03*

Swing duration (percent) 41.05 ± 1.34 42.25 ± 1.37 0.03*

Single support (percent) 41.17 ± 1.53 41.71 ± 1.38 0.34

Initial double support (percent) 8.75 ± 1.46 7.94 ± 1.05 0.10

Terminal double support (percent) 9.04 ± 1.33 8.10 ± 1.37 0.08

Normalised temporal spatial parameters

Stride time 0.35 ± 0.01 0.35 ± 0.01 1.00

Stride distance 1.59 ± 0.16 1.61 ± 0.11 0.70

Velocity 0.43 ± 0.03 0.41 ± 0.04 0.36

Cadence 34.89 ± 1.27 34.68 ± 1.34 0.72

* p < 0.05.

Table 3. Principal components (PC) identified for sagittal plane joint kinematic waveform data for the hip, knee and ankle during level walking (n=28). TD: typically developing boys; H: Haemophiliac boys. p value obtained from independent t-tests. %: percentage. Positive PC factor scores indicate flexion and dorsiflexion motion; negative PC factor scores indicate extension and plantarflexion motion.

Joint kinematics

Number of principal components (% variance explained)

% of gait cycle Principal component factor score P value

TD H

Hip Hip PC1 (81.0%) 81 to 20 0.01 ± 0.91 -0.01 ± 1.12 0.97

Hip PC2 (11.7%) 26 to 54 -0.08 ± 0.86 - 0.08 ± 1.14 0.67

Hip PC3 (5.5%) 58 to 71 -0.15 ± 0.83 0.15 ± 1.16 0.48

Knee Knee PC1 (28.4%) 17 to 39 0.01 ± 1.15 -0.01 ± 0.86 0.97

Knee PC2 (25.7%) 67to 88 0.15 ± 0.95 -0.15 ± 1.06 0.45

Knee PC3 (19.8%) 48 to 64 -0.22 ± 0.79 0.22 ± 1.16 0.24

Knee PC4 (19.5%) 96 to 11 -0.09 ± 1.18 0.09 ± 1.18 0.65

Ankle Ankle PC1 (26.9%) 4 to 28 - 0.29 ± 1.15 0.29 ± 0.75 0.13

Ankle PC2 (26.3% 31 to 58 - 0.15 ± 0.91 0.15 ± 1.09 0.45

Ankle PC3 (16.2%) 70 to 82 - 0.31 ± 0.92 0.31 ± 1.00 0.96

Ankle PC4 (14.6%) 91 to 1 - 0.06 ± 1.17 0.06 ± 0.84 0.74

Ankle PC5 (6.9%) 61 to 65 -0.20 ± 0.88 0.20 ± 1.10 0.29

Ankle PC6 (5.1%) 86 to 87 0.26 ± 0.91 -0.26 ± 1.04 0.89

Table 4. Principal components (PC) identified for vertical ground reaction force (VGRF) and sagittal plane joint kinetic waveform data for the hip, knee and ankle during level walking (n=28). TD: typically developing boys; H: Haemophiliac boys. p value obtained from independent t-tests. %: percentage; VGRF: vertical ground reaction force. Positive PC factor scores indicate flexion and dorsiflexion moments; negative PC factor scores indicate extension and plantarflexion moments.

Joint kinetics Number of principal components (% variance explained)

% of gait cycle

Principal component factor score P value

TD H

VGRF VGRF PC1 (27.68%) 28 to 36 - 0.10 ± 1.11 0.10 ± 0.91 0.61

VGRF PC2 (19.84%) 12 to 20 - 0.03 ± 0.66 0.03 ± 1.28 0.87

VGRF PC3 (19.81%) 40 to 48 - 0.17 ± 0.95 0.17 ± 1.06 0.37

Hip Hip PC1 (25.6%) 6 to 30 -0.02 ± 0.85 0.02 ± 1.16 0.12

Hip PC2 (25.4%) 35 to 58 0.21 ± 0.97 -0.21 ± 1.02 0.96

Hip PC3 (11.3%) 60 to 69 -0.03 ± 1.09 0.03 ± 0.94 0.11

Hip PC4 (9.9%) 83 to 90 0.19 ± 0.99 -0.19 ± 1.01 0.98

Hip PC5 (7.7%) 71 to 76 0.19 ± 1.11 -0.19 ± 0.88 0.33

Hip PC6 (5.7%) 0 to 4 0.28 ± 1.16 -0.28 ± 0.76 0.59

Knee Knee PC1 (28.6%) 12 to 37 0.02 ± 1.04 0.24 ± 0.76 0.84

Knee PC2 (16.9%) 42 to 57 0.07 ± 1.03 -0.07 ± 1.00 0.55

Knee PC3 (13.8%) 77 to 86 -0.01 ± 1.21 0.01 ± 0.78 0.12

Knee PC4 (12.4%) 64 to 74 -0.22 ± 1.13 0.22 ± 0.84 0.36

Knee PC5 (8.0%) 88 to 93 0.05 ± 1.15 -0.05 ± 0.87 0.54

Knee PC6 (6.9%) 5 to 8 0.29 ± 0.68 -0.29 ± 1.20 0.67

Ankle Ankle PC1 (18.9%) 2 to 29 0.20 ± 0.09 -0.20 ± 0.10 0.59

Ankle PC2 (15.22%) 48 to 62 67 to 72

0.20 ± 0.18 -0.20 ± 0.26 0.04*

Ankle PC3 (13.4%) 33 to 45 -0.34 ± 0.61 0.34 ± 0.17 0.35

Ankle PC4 (12.7%) 75 to 82 0.12 ± 0.60 -0.12 ± 0.11 0.28

Ankle PC5 (9.3%) 86 to 91 -0.22 ± 0.19 0.22 ± 0.17 0.67

Ankle PC6 (5.7%) 94 to 100 -0.02 ± 0.27 0.02 ± 0.22 0.28

* p < 0.05.