Three-dimensional gait analysis of healthy subjects in different age groups in Turkey

Three-dimensional gait analysis of healthy subjects in different age groups in Turkey

ESMAC Abstracts 2015 / Gait & Posture 42S (2015) S1–S101 (9 diplegic, 2 hemiplegic) GMFCS I–III, with mean age 7.7 (SD 3.7), height 127.2 (17.4) cm a...

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ESMAC Abstracts 2015 / Gait & Posture 42S (2015) S1–S101

(9 diplegic, 2 hemiplegic) GMFCS I–III, with mean age 7.7 (SD 3.7), height 127.2 (17.4) cm and weight 30.4 (11.8) kg participated in mean 15 (5) training sessions of robot-assisted program using the Lokomat® (Hocoma AG, Volketswill, Switzerland) over mean time of 41 (20) days. Additionally all children participated in regular physiotherapy. Angle values from 2D video gait analysis were collected with on screen goniometry. Results: Mean total distance, mean total time, mean velocity and mean body weight support of the all training sessions were 11.256 (6.042) m, 10.4 (4.2) h, 1.02 (0.23) km/h, 10.8 (26.9) kg, respectively. We observed significant improvement in swing phase expressed by greater ankle dorsiflexion (p < 0.05) in mid and terminal swing and nominal improvement of knee extension (p = 0.26) in terminal swing. Discussion: This is a part of a bigger study in which we focus on treatment outcomes of Robot-assisted gait training. RAGT in combination with physiotherapy shows influence on the swing phase kinematics in the study group. Reference [1] Borggraefe, et al. Eur J Paediatr Neurol 2010;14(6):496–502.

http://dx.doi.org/10.1016/j.gaitpost.2015.06.121

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Fig. 1.

processes). The cognitive task might provoke a reversed effect as it withdraws attention [3] from the cueing task which causes a more automatic movement. References [1] Todorov E, Jordan MI. Optimal feedback control as a theory of motor coordination. Nat Neurosci 2002;5:1226–35. [2] Baker K, Rochester L, Nieuwboer A. The immediate effect of attentional, auditory, and a combined cue strategy on gait during single and dual tasks in Parkinson’s disease. Archiv Phys Med Rehabil 2007;88:1593–600. [3] Polskaia N, Richer N, Dionne E, Lajoie Y. Continuous cognitive task promotes greater postural stability than an internal or external focus of attention. Gait Posture 2015.

http://dx.doi.org/10.1016/j.gaitpost.2015.06.122

Session PS14 Outcome study The effect of a cognitive dual task on step-time-constrained overground-walking variability in young and older individuals

Session PS14 Outcome study

D. Hamacher ∗ , D. Hamacher, L. Schega

Three-dimensional gait analysis of healthy subjects in different age groups in Turkey

Otto von Guericke University Magdeburg, Institute of Sport Science, Magdeburg, Germany

K. Beng ∗ , S. Aydil, O. Lapcin, P. Ozkan, K. Albayrak, Y.S. Kabukcuoglu

Research question: Does gait control change when stride times are externally constrained by auditory cues and does an additional cognitive load given to young and older individuals influence this potential effect? Introduction: Movement variability does not always interfere with task performance. Hence, controlling movement variability which does not interfere with achieving a goal is not efficient. Humans distinguish between variability of task-relevant and task-irrelevant movement parameters and apply the minimum intervention principle [1] in order to regulate only task-relevant fluctuations. Materials and methods: Twenty young and 13 old individuals were asked to perform 3 walking conditions: (1) normal unconstrained walking with preferred walking speed, (2) walking with constrained step times (using a metronome), and (3) walking with constrained step time and a cognitive dual task. Inertial sensors (MTw, Xsens Technologies B.V., The Netherlands) were attached to each of the subjects’ feet. Gait variability was quantified using the Coefficient of Variation of stride time. Data were analysed with a two-way repeated measures ANOVA. Results: Our results are depicted in Fig. 1. We observed an interaction effect between groups and normal walking and metronome-walking (p = 0.042; Coefficient of Variation of stride time in older subjects was significantly higher in the metronome walking condition, p = 0.016) which disappeared when regarding normal walking and metronome walking while performing a dual task (p > 0.05). Discussion: Our results corroborate the work of Baker et al. [2] who also observed a slight increase in step-time variability in older persons when walking on cues (which might be due to a shift in focus of attention or conscious intervention in automatized control

Baltalimani Bone Disease Training and Research Hospital, Istanbul, Turkey Research question: Is generating normalization data in threedimensional gait analysis of different age groups Necessity? Introduction: The gait pattern varies by age due to maturation of the nervous and musculoskeletal system and it reaches its maturity phase by the age of 8. Complexity of gait requires us to show an age-based approach in evaluation and generate agerelated normalization data. In this study, our aim was to generate normalization data of 3 dimensional gait analysis in different age groups to differentiate pathological gait patterns from normal. Materials and methods: 59 healthy subjects (age range: 5–21) who did not have any gait abnormalities were included in the study. Subjects were divided into 3 groups. Group 1 consisted of 19 subjects (5–8 years), group 2 of 21 subjects (9–13 years), group 3 of 19 subjects (14–21 years). Gait analysis was performed using Vicon Motion System. Statistical analysis was done with SPSS 20 [1–7]. Results: All temporo-spatial variables differed significantly between groups. Our data have shown that stride time, stride length and step width increase as height and lower limb length increase but cadence and velocity decrease. The kinematic values of the knee in the sagittal plane showed that; in group 1 knee flexion was higher at initial contact, knee extension was lower at midstance, peak knee flexion was higher during swing phase (p < 0.05). During preswing phase higher ankle plantar flexion moment was found in group 1 and statistically significant (Table 1). Discussion: We need to collect data of normal gait parameters; kinetic, kinematic and temporo-spatial using 3 dimensional gait analysis in different age groups to describe pathological gait patterns. Our findings are of importance as they present how the temporo-spatial parameters change due to maturation of the

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ESMAC Abstracts 2015 / Gait & Posture 42S (2015) S1–S101

Table 1 Kinematic and kinetic variables were compared between 3 groups with ANOVA.

Session PS14 Outcome study Hip and knee sagittal angles and muscle activation in stair locomotion: Impact of age and gender A. Farrag a,∗ , W. Elsayed b a

Faculty of Physical Therapy, Cairo University, Cairo, Egypt b College of Applied Medical Sciences, University of Dammam, Dammam, Saudi Arabia

musculoskeletal system and show the variances in kinetics and kinematics based on age. In conclusion, defining the age-related changes in gait is necessary to describe the pathological gait patterns. References [1] Davis RB. A gait analysis data collection reduction technique. Hum Mov Sci 1991;10:575–87. [2] Hallemans AA. Cross-sectional study spanning the first rapid development phase of walking. Gait Posture 2005;22:107–18. [3] Sutherland DH. The development of mature gait. Gait Posture 1997;6:163–70. [4] Ounpuu S. Three-dimensional lower extremity joint kinetics in normal pediatric gait. J Ped Ort 1991;11:341–9. [5] Oeffinger D. Pediatric kinetics: age related changes in able-bodied populations. GaitPosture 1997;5:155–6. [6] Cupp T. Age-related kinetic changes in normal pediatrics. J Ped Ort 1999;19:475–8. [7] Perry J. Gait analysis normal and pathological function; 2009.

Research question: Do age and gender affect hip and knee sagittal angles and muscle activation in stair ascent and descent? Introduction: Stair walking is more demanding than level walking [1]. In subjects with lower limb disability, this activity may be provocative of many symptoms as pain. Gender and developmental age proved to have kinematic and kinetic differences in certain athletic activities [2]. Analysis of stair climbing has been restricted only to young or elderly subjects regardless of gender requirements. This study aimed to determine whether there are gender and/or age differences in stair locomotion. Materials and methods: Forty healthy subjects were recruited and assigned to 2 groups: adults (10 males and 10 females, 22 ± 3.5 y) and children (10 males and 10 females, 8.7 ± 1.1 y). Subjects performed stair ascent (AS) and descent (DS) on a two-sided four steps staircase. Sagittal angles were measured including maximum (Max) and minimum (Min) flexion angles of the dominant hip and knee. Dynamic EMG activity was picked up from gluteus medius (GM), and rectus femoris (RF) muscles. Results: Angles were significantly higher in children than in adults except for the Knee-Min during DS and AS, and Hip-Min during DS. Females had higher angles than males except for Hip-Min in AS, and both knee angles in DS. Interaction of age and gender was found significant for hip angles in AS and DS, and for Knee-Max in AS only. Children exerted higher normalized EMG activity than adult during AS and DS.

http://dx.doi.org/10.1016/j.gaitpost.2015.06.123 Age effect Adult Hip-Max AS DS Hip-Min AS DS Knee-Max AS DS Knee-Min AS DS

Gender effect Children

Males

Females

Adult males

Adult females

Children males

Children females

56 (9) 31 (9)

72 (10)* 40 (9)*

60 (14) 33 (12)

67 (9)** 38 (6)**

49 (8) 26 (8)

63 (7) 37 (4)

72 (11) 41 (11)

72 (9)*** 39 (7)***

11 (6) 12 (7)

16 (6)* 12 (8)

12 (6) 15 (6)

15 (6) 15 (6)**

9 (6) 8 (5)

14 (4) 18 (4)

17 (5) 14 (10)

15 (8)*** 12 (7)***

92 (9) 88 (5)

102 (9)* 107 (7)*

93 (12) 96 (11)

101 (9)** 99 (16)

86 (9) 87 (7)

99 (6) 90 (18)

101 (11) 107 (5)

103 (14)*** 107 (9)

19 (7) 18 (6)

21 (8) 17 (7)

18 (8) 17 (7)

23 (6)* 18 (7)

17 (7) 18 (6)

22 (5) 19 (5)

19 (10) 16 (7)

24 (6) 18 (8)

Age effect

GM AS DS RF AS DS

Interaction effect

Gender effect

Interaction effect

Adult

Children

Males

Females

Adult males

Adult females

Children males

Children females

0.5 (0.2) 0.3 (0.1)

0.7 (0.2)* 0.5 (0.2)*

0.5 (0.2) 0.4 (0.2)

0.6 (0.2) 0.4 (0.2)

0.4 (0.1) 0.3 (0.2)

0.5 (0.2) 0.4 (0.1

0.7 (0.2) 0.5 (0.2)

0.7 (0.2) 0.5 (0.2)

0.4 (0.2) 0.4 (0.2)

0.6 (0.2)* 0.6 (0.2)*

0.5 (0.2) 0.4 (0.2)

0.6 (0.1) 0.5 (0.2)

0.4 (0.2) 0.3 (0.2)

0.5 (0.1) 0.4 (0.1)

0.6 (0.2) 0.5 (0.1)

0.6 (0.2) 0.6 (0.2)