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Assessment of gait performance variability as potential indicator of fall risk: Study design
ESMAC Abstracts 2015 / Gait & Posture 42S (2015) S1–S101
Session PS15 Methods and Models
Session PS15 Methods and Models
Assessment of gait performance variability as potential indicator of fall risk: Study design
A comparison of non-motorized treadmill gait kinematics to both overground and motorized treadmill locomotion
Z. Svoboda ∗ , M. Janura, L. Bizovska, E. Kubonova, M. Hamrikova Faculty of Physical Culture, Palacky University Olomouc, Olomouc, Czech Republic Research question: Can variability of selected kinematic and kinetic variables during gait serve as indicator of fall risk? Introduction: The influence of fall history to increased gait variability has been shown in temporal–spatial variables [1], thus increased variability of other variables (joint angles, COP variables, acceleration) related to gait performance would be expected. The aim of the study is to assess relationship between gait performance variability and falls history and to evaluate level of fall related variables in groups of various ages and with musculoskeletal deficiency and subjects with professional training focused on postural stability. Materials and methods: Measurement methods include the assessment of gait performance variability (centre of pressure movement, joint angles, acceleration), the assessment of static balance (centre of pressure movement) in various conditions, anthropometric measurements and specific balance scales. Fall history observation respect recommendations of Prevention of Falls Network Europe and Outcomes Consensus Group [2]. Results: Project design consisted of prospective study of fall risk in older subjects and assessment of fall related variables in groups of various ages and with musculoskeletal deficiency and subjects with professional training focused on postural stability. First results of the project will be presented on the conference. Discussion: Recently scientific studies showed that fall risk is possible predict rather on the basis of results obtained in dynamic than in static conditions [3], however research in this area is focused mainly to targeted movement tasks. Finding of new relatively procedures, which enable assessment of dynamic stability during gait, can serve as diagnostic tool determining fall risk level with follow up risk of fractures, which have a large impact on both the individual’s quality of life and health-care costs. References [1] Taylor ME, Delbaere K, Mikolaizak AS, Lord SR, Close JC. Gait parameter risk factors for falls under simple and dual task conditions in cognitively impaired older people. Gait Posture 2013;37(1):126–30. [2] Lamb SE, Jørstad-Stein EC, Hauer K, Becker C. Development of a common outcome data set for fall injury prevention trials: the Prevention of Falls Network Europe consensus. J Am Geriatr Soc 2005;53(9):1618–22. [3] van Schooten KS, Rispens SM, Elders PJ, van Dieën JH, Pijnappels M. Toward ambulatory balance assessment: estimating variability and stability from short bouts of gait. Gait Posture 2014;39(2):695–9.
S73
A. Fullenkamp ∗ , C.M. Laurent, D. Tolusso, B. Campbell Bowling Green State University, C119 Eppler Complex, Bowling Green, United States Research question: Do lower-extremity gait kinematics on a non-motorized treadmill differ from those observed on both a motorized treadmill and overground? Introduction: Non-motorized treadmills (NMT) have been marketed as devices that allow for a walking/running experience more comparable to that of overground (OG) locomotion [1,2]. While an NMT may afford users improved gait variability compared to conventional motorized treadmills (MT), there is evidence that the curved geometry of the belt surface may also alter lower-extremity (LE) kinematics [3]. To date, kinematic changes associated with curved NMT use have been demonstrated for ranges of motion, and have only been examined in comparison to MTs. The purpose of this study was to evaluate the gait kinematics between OG, MT and NMT locomotion. Materials and methods: Ten healthy, adult participants were recruited for the study, and all provided informed consent (24.7 ± 5.7 years, 177.3 ± 10.4 cm, and 79.7 ± 17.6 kg). Ten trials each of OG walking and running were collected, after which mean gait velocities were determined. Mean OG velocities were then used for each participant’s subsequent MT and NMT trials. MT and NMT trials consisted of a single, 90-second trial. Lowerextremity gait kinematics were evaluated using a 10-camera, motion analysis system. The motion data were captured at 120 fps and raw marker tracks were filtered using a low-pass Butterworth filter with a 6 Hz cutoff. Euler angles were then calculated for sagittal plane hip, knee and ankle motion. Finally, a repeated measures ANOVA (p = 0.05) was performed with Fisher’s LSD post-hocs. Results: Peak hip and knee flexion as well as knee flexion at foot strike and ankle dorsiflexion post-foot strike were found to be greater (p < 0.05) in the NMT condition compared to both MT and OG for both walking and running (Fig. 1). Further, no differences were found between MT and OG conditions for the variables assessed.
http://dx.doi.org/10.1016/j.gaitpost.2015.06.135
Fig. 1. Walking (left) and running (right) hip, knee and ankle gait kinematics for (a) MT vs. OG and (b) NMT vs. OG. OG kinematics are shaded in each comparison.
Session PS15 Methods and Models
Session PS15 Methods and Models
Assessment of gait performance variability as potential indicator of fall risk: Study design
A comparison of non-motorized treadmill gait kinematics to both overground and motorized treadmill locomotion
Z. Svoboda ∗ , M. Janura, L. Bizovska, E. Kubonova, M. Hamrikova Faculty of Physical Culture, Palacky University Olomouc, Olomouc, Czech Republic Research question: Can variability of selected kinematic and kinetic variables during gait serve as indicator of fall risk? Introduction: The influence of fall history to increased gait variability has been shown in temporal–spatial variables [1], thus increased variability of other variables (joint angles, COP variables, acceleration) related to gait performance would be expected. The aim of the study is to assess relationship between gait performance variability and falls history and to evaluate level of fall related variables in groups of various ages and with musculoskeletal deficiency and subjects with professional training focused on postural stability. Materials and methods: Measurement methods include the assessment of gait performance variability (centre of pressure movement, joint angles, acceleration), the assessment of static balance (centre of pressure movement) in various conditions, anthropometric measurements and specific balance scales. Fall history observation respect recommendations of Prevention of Falls Network Europe and Outcomes Consensus Group [2]. Results: Project design consisted of prospective study of fall risk in older subjects and assessment of fall related variables in groups of various ages and with musculoskeletal deficiency and subjects with professional training focused on postural stability. First results of the project will be presented on the conference. Discussion: Recently scientific studies showed that fall risk is possible predict rather on the basis of results obtained in dynamic than in static conditions [3], however research in this area is focused mainly to targeted movement tasks. Finding of new relatively procedures, which enable assessment of dynamic stability during gait, can serve as diagnostic tool determining fall risk level with follow up risk of fractures, which have a large impact on both the individual’s quality of life and health-care costs. References [1] Taylor ME, Delbaere K, Mikolaizak AS, Lord SR, Close JC. Gait parameter risk factors for falls under simple and dual task conditions in cognitively impaired older people. Gait Posture 2013;37(1):126–30. [2] Lamb SE, Jørstad-Stein EC, Hauer K, Becker C. Development of a common outcome data set for fall injury prevention trials: the Prevention of Falls Network Europe consensus. J Am Geriatr Soc 2005;53(9):1618–22. [3] van Schooten KS, Rispens SM, Elders PJ, van Dieën JH, Pijnappels M. Toward ambulatory balance assessment: estimating variability and stability from short bouts of gait. Gait Posture 2014;39(2):695–9.
S73
A. Fullenkamp ∗ , C.M. Laurent, D. Tolusso, B. Campbell Bowling Green State University, C119 Eppler Complex, Bowling Green, United States Research question: Do lower-extremity gait kinematics on a non-motorized treadmill differ from those observed on both a motorized treadmill and overground? Introduction: Non-motorized treadmills (NMT) have been marketed as devices that allow for a walking/running experience more comparable to that of overground (OG) locomotion [1,2]. While an NMT may afford users improved gait variability compared to conventional motorized treadmills (MT), there is evidence that the curved geometry of the belt surface may also alter lower-extremity (LE) kinematics [3]. To date, kinematic changes associated with curved NMT use have been demonstrated for ranges of motion, and have only been examined in comparison to MTs. The purpose of this study was to evaluate the gait kinematics between OG, MT and NMT locomotion. Materials and methods: Ten healthy, adult participants were recruited for the study, and all provided informed consent (24.7 ± 5.7 years, 177.3 ± 10.4 cm, and 79.7 ± 17.6 kg). Ten trials each of OG walking and running were collected, after which mean gait velocities were determined. Mean OG velocities were then used for each participant’s subsequent MT and NMT trials. MT and NMT trials consisted of a single, 90-second trial. Lowerextremity gait kinematics were evaluated using a 10-camera, motion analysis system. The motion data were captured at 120 fps and raw marker tracks were filtered using a low-pass Butterworth filter with a 6 Hz cutoff. Euler angles were then calculated for sagittal plane hip, knee and ankle motion. Finally, a repeated measures ANOVA (p = 0.05) was performed with Fisher’s LSD post-hocs. Results: Peak hip and knee flexion as well as knee flexion at foot strike and ankle dorsiflexion post-foot strike were found to be greater (p < 0.05) in the NMT condition compared to both MT and OG for both walking and running (Fig. 1). Further, no differences were found between MT and OG conditions for the variables assessed.
http://dx.doi.org/10.1016/j.gaitpost.2015.06.135
Fig. 1. Walking (left) and running (right) hip, knee and ankle gait kinematics for (a) MT vs. OG and (b) NMT vs. OG. OG kinematics are shaded in each comparison.