SciELO - Scientific Electronic Library Online

Home Pagealphabetic serial listing  

Services on Demand




Related links


Journal of Physical Education

On-line version ISSN 2448-2455

J. Phys. Educ. vol.29  Maringá  2018  Epub May 24, 2018 

Artigo Original



Roberta Castilhos Detanico Bohrer1  2 

Angélica Lodovico2 

Marcia Regina Irber Kertscher1 

Gleber Pereira1 

André Luiz Felix Rodacki1 

1Universidade Federal do Paraná, Curitiba-PR, Brasil.

2Universidade Positivo, Curitiba-PR, Brasil.


Approximately 21% of the falls in older adults occur due to tripping, while walking. There is a paucity of information regarding the gait variability and reliability when a tripping is induced in different days mainly with elderly. It was aimed to analyze the variability and the reliability (intra- and inter-day) of spatiotemporal gait parameters and joint angles after controlled tripping in older adults. Eight healthy older women participated. The trip was induced during the early-mid swing phase on the transposing segment and the kinematic data was obtained from trials. The variability and reliability of spatiotemporal gait parameters and joint angles during the gait cycle were checked through the coefficient of variation (CV), the intraclass coefficient correlation (ICC) and the standard error of measurement (SEM). The variability of spatiotemporal and intra- and inter-day angular parameters was low for most variables, except for plantar flexion. The SEM was low for all parameters. Intra-day reliability was moderate to high for the spatiotemporal and angular parameters. Inter-day reliability was considered low to moderate for all parameters. The variables did not differ between instants and days. Experimental procedures demonstrate that the walking pattern did not change, but should be considered with caution in studies that include intervention, particularly for angular parameters during gait.

Key words: Stumble; Falling; Elderly.


Aproximadamente 21% das quedas em idosos ocorrem como consequência de tropeços ao caminhar. Há uma escassez de informações referentes à variabilidade e à confiabilidade dos parâmetros cinemáticos da marcha em diferentes dias de avaliação, sobretudo com idosos. Buscou-se analisar a variabilidade e a confiabilidade (intra e inter-dia) dos parâmetros espaço-temporais e angulares da marcha de idosos, após a indução de tropeço controlado. Oito idosas participaram do estudo. O tropeço foi induzido durante o início da fase de balanço da marcha. Foram analisados os dados cinemáticos das tentativas de marcha. A variabilidade e confiabilidade dos parâmetros espaço-temporais da marcha foram verificados através do coeficiente de variação (CV), do coeficiente de correlação intraclasse (ICC) e do erro padrão de medida (SEM). A variabilidade dos parâmetros espaço-temporais e angulares intra e inter-dia foi baixa para a maioria das variáveis, à exceção da flexão plantar. O SEM foi baixo para todos os parâmetros. A confiabilidade intra-dia foi moderada a alta para os parâmetros espaço-temporais e angulares; A confiabilidade inter-dia foi baixa a moderada para todos os parâmetros. As variáveis não diferiram entre instantes e dias. Apesar do padrão de marcha não ter alterado deve ser analisado com cautela em estudos que incluam intervenção, particularmente para os parâmetros angulares.

Palavras-chave: Tropeço; Queda; Envelhecimento.


Falls are a major public health concern(1), as the rate of older adult population and the absolute number of falls have increased in the last decades(2). Approximately 21% of the falls in older adults occur due to tripping, while walking forward (accounting for 24%)(3) and may result in serious injury and/or even death(4). Then, understanding the underlying mechanisms involved in tripping are required and may help to improve preventive and intervention procedures designed to reduce falls among older adults5),(6. Most studies devoted to determine fall incidence have applied retrospective and/or prospective approaches, which are prone to a number of issues that may obscure the results7),(8. These approaches are unable to identify near-fall or missteps, which are relevant while assessing risk of falls9),(10. and also disregard changes in physical activities with respect to time, i.e., the physical characteristics may vary from the instant they were assessed and the trip or fall occurred. In addition, retrospective studies rely on memory11),(12),(13, which is not always reliable especially if the fall did not produce significant injuries.

Innovative approaches to induce laboratory trip during walking include obstacle rising to obstruct the swing foot motion14),(15),(16),(17 or restricting the swing foot motion using a rope or similar devices18),(19. Despite the fact that these methods can create approximate conditions that closely simulate a trip, anticipatory adjustments have been shown to influence the results when repeated trips are performed in one session (i.e., intra-session variation)15),(17. Although intra-day gait kinematics variability has been found low (10-17%)(14), there is a paucity of information regarding to inter-day variability and reliability when an induced trip is repeated between sessions. Low variability and high reliability inter-day would entitle one to use laboratory controlled tripping tests to evaluate the effects intervention programs (i.e., training programs) on a person’s ability to recover from a trip and avoid a fall.

In addition, most studies14),(15),(20 that analyzed reproducibility measures in laboratory induced trips included only young subjects, rather than old adults. There are several indications that these populations differ with respect to their ability to recover from a trip(21), in which older adults are less able to regain balance and, therefore, more vulnerable to falls(20). Although Wright and colleagues(22) showed that previous experience of falling did not result in gait pattern changes, others have reported a more cautious pattern due to fear of tripping and falling(23), which may occur within and between sessions. Older adults tend to be more susceptible to fear of falling than their young counterparts(23). Thus, the use of a non-specific population in previous investigations (i.e., young subjects) may have clouded the results and requires further research(2).

Therefore, this study aimed to determine the variability and the reliability (intra- and inter-day) of spatiotemporal gait parameters and joint angles after a controlled laboratory tripping in older adults using a novel approach. This system may be used as a plausible method to better understand movement control and organization without some drawbacks and disadvantages of others and help to design preventive fall-related strategies. It has been hypothesized that no differences within and between sessions will be found in gait pattern. If subjects do not change their gait pattern after tripping, such test may be applied repeatedly to induce a trip on a laboratory environment.



Eight healthy older women, independent in daily activities (70.2 (5.8) years; 69.6 (10.2) kg; 1.56 (0.03) m) were recruited through advertisements at the Sports Science Department and volunteered to participate of the study after signing an informed consent form in conformity with Helsinki Declaration of 1975, as revised in 1983. The local Ethics Committee approved the experimental procedures (protocol number 664.638). The functional status of each elderly subject was assessed using the Timed-up-and-go test (TUG). The short time to perform the TUG test (7.50± 0.75 s) indicates the healthy status of our sample(24).


Participants visited the laboratory twice to determine variability and reliability of spatiotemporal gait parameters and joint angles after the tripping simulation. In the first day, participants performed 10-15 gait trials (pre-trip). The trip was induced once between the 10th and the 15th trial. After tripping, an additional set of 10-15 gait trials were performed (post-trip)(1). Three months later, identical experimental procedures were performed in a second visit to the laboratory. In both visits, participants were requested to walk using a self-selected pace on a walkway of 10 m long and 2 m wide, with a force plate (AMTI OR6-7, MA, USA) mounted after 3 m from starting position. A full-body safety harness attached to a ceiling-mounted rail was used to prevent individuals to hitting the ground after failing to recovery from the trip. Participants were instructed to walk at a self-selected velocity over the long walkway. They were advised that their balance could be perturbed during the experiment, but no information about how and the instant the perturbation would occur was provided. To induce the trip, an automated customized electronic device lifted a wire crossing the walkway (0.1 m height), catching the participant’s swinging segment. The device was triggered when the participants’ left foot was in the early-mid swing phase, while the right foot was in contact with the force plate. Three non-functional but identical dummy wires were placed in the walkway and were deemed not to influence gait (Figure 1). This novel approach differs from others because it uses an automated system in which a wire is raised from the ground to produce a perturbation during the early-mid swing phase of the trailing limb. It is also cheaper and easier to induce trips in a controlled laboratory scenario, as there is no need of a complex apparatus to obstruct the swinging segment during gait.

The authors

Figure 1 Experimental setup representation 

During the gait trials, kinematic data were collected using nine infrared opto-electronic cameras (MX13/T10, Vicon, Denver, USA) sampling at 100 Hz. Fifteen landmarks (sacrum, right and left anterior superior iliac spines, thighs, knees, tibias, lateral malleolus, toes and heels) were placed on participants’ lower limb according to the Helen Hayes Sacrum Plug-in-gait model. The spatiotemporal gait parameters (walking speed, stride time, stance time and stride length) and joint angles (peak flexion and extension of hip and knee joints, and ankle dorsiflexion and plantarflexion) during the gait cycle were measured. Data processing was performed through a specific routine in Matlab® (MathWorks, Inc., version 7.8.0-R2009a). The time series were normalized by the gait cycle (100%) using the Spline function, considering two successive contacts of the heel of the same limb. The three-dimensional coordinates were filtered with a low pass 2nd order Butterworth filter with a cutoff frequency of 10 Hz. Then, the ensemble average of three trials immediately before the trip was calculated to represent the pre-trip data set. The ensemble average of three trials immediately following a trip was calculated to determine the effects of tripping on walking parameters (post-trip).

Statistical Analysis

Intra- and inter-day variability of spatiotemporal gait parameters and joint angles were calculated using the mean coefficient of variation (CV), calculated from the three trials (ensemble average) of each subject. In addition, the intraclass correlation coefficient (ICC3,k) and standard error of measurement (SEM) were used to check the reliability intra-subject (three trials), intra- (pre- and post-trip for each day) and inter-day (day 1 and day 2 at pre-trip and post-trip instants). As suggested by Portney and Watkins, ICC values above 0.75 indicated good reliability, those between 0.5 and 0.75 moderate reliability and those under 0.5 poor reliability25. After determining data normality, a two-way repeated measure ANOVA was performed, having instant (pre- and post-trip) vs. day (first and second days) as inputs. In order to support rejection or acceptance of the null hypothesis (considering the current sample size) or to support results from descriptive statistics the partial eta squared effect size ((2) and power were calculated(26). All analyses were performed using SPSS version 20.0 (SPSS Inc., Chicago, IL) with the significance level set at p < 0.05.


The CV intra- and inter-day ranged from 1.3 to 4.0% to the spatiotemporal parameters of gait. The CV intra- and inter-day of the joint angles ranged from 1.7 to 33.0%, with the highest CV% for the plantar flexion angle. There was only significant interaction effect between instant and day to the absolute values of stride time (F(1,7)=6.89, p=.03, η2=0.49, power=0.62), increasing in average 1% from the 1st to the 2nd day (Table 1).

Table 1 Mean (SD), 95% confidence interval (CI95%), and mean coefficient of variation (CV) of spatiotemporal gait parameters and joint angles at pre- and post-trip measurements in different days (n=8) 

Pre-Trip Post-Trip Pre-Trip Post-Trip
Variables Mean(SD) (CI95%) Mean CV% Mean(SD) (CI95%) Mean CV% Mean(SD) (CI95%) Mean CV% Mean(SD) (CI95%) Mean CV% F
Walking speed (m/s) 1.18 (0.14) (1.06-1.30) 3.61 1.18 (0.14) (1.06-1.30) 3.73 1.15 (0.12) (1.05-1.25) 3.32 1.17 (0.14) (1.05-1.29) 2.57 1.32
Stride time (s) 1.06 (0.08) (1.00-1.12) 2.47 1.06 (0.08) (1.02-1.15) 2.13 1.08 (0.08) (1.02-1.15) 1.81 1.07 (0.07) (1.00-1.13) 1.37 6.90*
Stance phase (% of cycle) 62.10 (2.49) (60.02-64.18) 1.78 62.16 (2.73) (60.92-64.66) 1.39 64.35 (3.66) (61.28-67.41) 1.40 64.17 (2.03) (62.48-65.87) 1.90 0.08
Stride length (m) 1.25 (0.08) (1.18-1.31) 2.62 1.25 (0.08) (1.18-1.31) 2.67 1.25 (0.08) (1.18-1.31) 2.51 1.24 (0.10) (1.16-1.33) 2.37 0.02
Peak hip Flexion (°) 29.50 (5.66) (24.76-34.23) 2.84 30.76 (6.12) (25.65-35.88) 5.39 26.04 (9.31) (18.26-33.83) 2.87 26.13 (10.10) (17.69-34.58) 3.54 1.60
Peak knee Flexion (°) 58.15 (4.42) (54.46 -61.85) 1.76 59.96 (4.91) (55.85-64.03) 2.44 59.54 (3.95) (56.23-62.84) 2.07 60.42 (5.03) (56.21-64.62) 2.27 1.12
Peak ankle dorsiflexion (°) 18.12 (3.08) (15.55-20.70) 3.05 18.25 (2.46) (16.19-20.31) 3.89 18.31 (3.68) (15.23-21.39) 4.27 18.77 (3.63) (15.74-21.80) 4.50 0.25
Peak plantar flexion (°) -7.76 (4.09) (-11.18- -4.34) 31.02 -7.46 (4.66) (-11.36- -3.56) 32.49 -6.87 (2.02) (-8.56- -5.18) 16.33 -6.22 (3.40) (-9.06- -3.73) 3.00 0.16

Note: *Significant interaction between session and day. F values referent to interaction effect

Source: The authors

The calculated SEM presented low values for all analysis. The ICC intra-day ranged from 0.66 to 0.97 for the spatiotemporal parameters, considering the lowest ICC to stance phase variable and from 0.66 to 0.99 to joint angles, with the lowest ICC value to plantar flexion. In addition, the ICC inter-day ranged from 0.44 to 0.65 to spatiotemporal gait parameters and from 0.16 to o.67 to joint angles (Table 2).

Table 2 Intraclass correlation coefficient (ICC3,k) and Standard error measurement (SEM)of spatiotemporal gait parameters and joint angles at pre- and post-trip measurements in different days (n=8). 

Day 1 Day 2
Pré-Trip Post-Trip Pré-Trip Post-Trip
Variables ICCa ICCa ICCb ICCa ICCa ICCb ICCc
Walking speed 0.89 0.95 0.97 0.93 0.94 0.94 0.52
(m/s) 0.05 0.03 0.00 0.03 0.04 0.00 0.01
Stride time 0.86 0.91 0.97 0.93 0.92 0.96 0.54
(s) 0.03 0.02 0.00 0.02 0.02 0.00 0.01
Stance phase 0.67 0.89 0.93 0.93 0.44 0.66 0.44
(% of cycle) 1.43 0.91 0.01 0.97 1.52 0.07 1.13
Stride length 0.82 0.89 0.93 0.89 0.90 0.92 0.65
(m) 0.03 0.03 0.00 0.03 0.03 0.00 0.00
Peak hip Flexion 0.97 0.88 0.94 0.99 0.99 0.99 0.40
(°) 0.98 2.12 0.22 0.93 1.01 0.01 2.21
Peak knee Flexion 0.94 0.85 0.91 0.85 0.81 0.86 0.28
(°) 1.08 1.90 0.38 1.53 2.19 0.23 0.55
Peak ankle dorsiflexion 0.96 0.90 0.95 0.95 0.94 0.92 0.67
(°) 0.62 0.78 0.02 0.82 0.89 0.09 0.14
Peak plantar flexion 0.96 0.86 0.94 0.74 0.91 0.66 0.16
(°) 0.82 1.75 0.05 1.03 1.02 0.27 0.69

Note: ICCa and SEMa intra-subjects reliability; ICCb and SEMb: intra-day reliability; ICCc and SEMc: inter-day reliability

Source: The authors


This is the first study to determine the variability and the reliability (intra- and inter-day) of spatiotemporal gait parameters and joint angles after a controlled tripping in older adults. Such results are relevant as previous studies are limited because young subjects are known to present substantial differences in their ability to recover from a trip when compared to older adults. Considering the intra- and inter-day analyzes, the variability of spatiotemporal gait parameters was low and joint angles variability varied from low to moderate(27). Furthermore, reliability of gait and joint angles was moderate to high(25).

The mean walking speed (1.18±0.14 m/s), stride time (1.06±0.08 s) and stride length (1.25±0.08 m) are comparable to those reported by Hollman and colleagues(28) for women of similar age (1.16±0.20 m/s; 1.06±0.13 s; 1.23±0.17 m). These results are also similar to the group that experienced a previous fall due to tripping (1.19±0.20 m/s; 1.06±0.08 s; 1.26±0.17 m)(22). The findings of Wright and colleagues showed no differences in gait kinematics when non-fallers were compared to individuals with a fall history, irrespective of the cause of the event (i.e., trip or slip). Therefore, the idea that a conservative or cautious gait pattern emerges after a trip was also discarded in the present study, even when tripping is repeated after a brief period of time, i.e., within session. It is likely that tripping was not a significant event (i.e., did not cause an injury) when compared to a fall.

The significant interaction found in the stride time may have occurred due to the high variability between individuals (i.e., large standard deviations), although the average change was low. Indeed, a similar stride time CV (2.2±1.3%) was reported in a previous study for healthy elderly(29). In addition, the spatiotemporal gait parameters presented lower mean variability (1-4%) in comparison to the study performed by Hollman and colleagues(28) for older women (3-8%), but similar to previous that included young and older adults(30). Moreover, most gait variables used to determine gait pattern remained stable (intra-day variability) after participants’ tripping and indicated gait pattern consistence(31).

The low intra-day variability of knee and hip joint angles displacements are in agreement with previous experiments(14). On the other hand, the ankle joint variability was high (~32%), but non-significant and stable between pre- and post-tripping in the first day, considering the respective coefficients of variation. These results are in agreement with Pijnappels and colleagues(14), who reported high ankle joint variability for young adults (37-53%).

The intra- and inter-day reliability of spatiotemporal gait parameters varied from moderate to high (ICC: 0.66-0.99) and were comparable to those reported by Menz and colleagues(31), in which the gait pattern of older adults was analyzed in different days. In general, joint angles presented moderate to high intra- and inter-day reliability, except during plantar flexion and knee and hip flexion in the inter-day assessment. These results do not represent a strategy change, considering the intra-day stability and the low error measurements. In addition, these low to moderate ICC values indicated greater within-subjects variance. In fact, part of the variability between individuals may have occurred from particular characteristics of walking pattern(14).


In conclusion, the findings of spatiotemporal gait parameters and joint angles suggests that such approach can be applied to determine changes in response to intervention programs (e.g. dancing, strength, power, etc.) designed to improve gait and reduce the risk of falls in older adults. Importantly, however, that you must be careful when analyzing the results from interventions, particularly for angular parameters. Therefore, the experimental procedures applied to induce a trip in a laboratory controlled condition were deemed not to affect gait pattern within and between sessions and allowed to confirm our experimental hypothesis. The experimental approach did not cause any discomfort or injuries and was proven to be a safe, cheap and useful strategy to test the ability of older adults to regain balance in a condition that closely mimics a real trip situation.


CAPES to financial support.


1. Whipple R, Wolfson L, Amerman P. The relationship of knee and ankle weakness to falls in nursing home residents: an isokinetic study. J Am Geriatr Soc 1987;35(1):13-20. DOI: 10.1111/j.1532-5415.1987.tb01313.x [ Links ]

2. Grabiner MD, Crenshaw JR, Hurt CP, Rosenblatt NJ, Troy KL. Exercise-based fall prevention: can you be a bit more specific? ‎Exerc Sport Sci Rev 2014;42(4):161-168. DOI: 10.1249/jes.0000000000000023 [ Links ]

3. Robinovitch SN, Feldman F, Yang Y, Schonnop R, Leung PM, Sarraf T, et al. Video capture of the circumstances of falls in elderly people residing in long-term care: an observational study. The Lancet 2013;381(9860):47-54. DOI: 10.1016/s0140-6736(12)61263-x [ Links ]

4. Pavol MJ, Owings TM, Foley KT, Grabiner MD. Mechanisms leading to a fall from an induced trip in healthy older adults. J Gerontol A Biol Sci Med Sci 2001;56(7):M428-M37. [ Links ]

5. Bento PCB, Pereira G, Ugrinowitsch C, Rodacki AL. The effects of a water-based exercise program on strength and functionality of older adults. J Aging Phys Act 2012;20:469-483. [ Links ]

6. Cepeda CCP, Lodovico A, Fowler N, Rodacki ALF. Effect of an 8-week Ballroom Dancing Programme on Muscle Architecture in Older Adults Females. J Aging Phys Act 2015;23(4):607-612. DOI: 10.1123/japa.2014-0101 [ Links ]

7. Srygley JM, Herman T, Giladi N, Hausdorff JM. Self-report of missteps in older adults: a valid proxy of fall risk? Arch Phys Med Rehabil 2009;90(5):786-792. DOI: 10.1016/j.apmr.2008.11.007. [ Links ]

8. Ward RE, Leveille SG, Beauchamp MK, Travison T, Alexander N, Jette AM, et al. Functional performance as a predictor of injurious falls in older adults. J Am Geriatr Soc 2015;63(2):315-320. DOI: 10.1111/jgs.13203 [ Links ]

9. Macaluso A, De Vito G. Muscle strength, power and adaptations to resistance training in older people. Eur J Appl Physiol 2004;91(4):450-472. DOI: 10.1007/s00421-003-0991-3 [ Links ]

10. Teno J, Kiel DP, Mor V. Multiple Stumbles: A Risk Factor for Falls in Community‐Dwelling Elderly; A Prospective Study. J Am Geriatr Soc 1990;38(12):1321-1325. [ Links ]

11. Riva F, Toebes MJ, Pijnappels M, Stagni R, van Dieen JH. Estimating fall risk with inertial sensors using gait stability measures that do not require step detection. Gait Posture 2013;38(2):170-174. DOI: 10.1016/j.gaitpost.2013.05.002 [ Links ]

12. Greene BR, McGrath D, Caulfield B, editors. A comparison of cross-sectional and prospective algorithms for falls risk assessment. Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE; 2014: IEEE. DOI: 10.1109/embc.2014.6944630 [ Links ]

13. Rosenblatt NJ, Grabiner MD. Relationship between obesity and falls by middle-aged and older women. Arch Phys Med Rehabil 2012;93(4):718-22. DOI: 10.1016/j.apmr.2011.08.038 [ Links ]

14. Pijnappels M, Bobbert MF, van Dieën JH. Changes in walking pattern caused by the possibility of a tripping reaction. Gait Posture 2001;14(1):11-18. DOI: ]

15. Potocanac Z, de Bruin J, van der Veen S, Verschueren S, van Dieën J, Duysens J, et al. Fast online corrections of tripping responses. Exp Brain Res 2014;232(11):3579-3590. DOI: 10.1007/s00221-014-4038-2 [ Links ]

16. Pavol MJ, Owings TM, Foley KT, Grabiner MD. The sex and age of older adults influence the outcome of induced trips. J Gerontol A Biol Sci Med Sci 1999;54(2):M103-M8. [ Links ]

17. Rhea CK, Rietdyk S. Influence of an unexpected perturbation on adaptive gait behavior. Gait Posture 2011;34(3):439-441. DOI: 10.1016/j.gaitpost.2011.06.011 [ Links ]

18. Krasovsky T, Baniña MC, Hacmon R, Feldman AG, Lamontagne A, Levin MF. Stability of gait and interlimb coordination in older adults. J Neurophysiol 2012;107(9):2560-2569. DOI: 10.1152/jn.00950.2011 [ Links ]

19. Cordero AF, Koopman HFJM, van der Helm FCT. Multiple-step strategies to recover from stumbling perturbations. Gait Posture 2003;18(1):47-59. DOI:10.1016/s0966-6362(02)00160-1 [ Links ]

20. Wang T-Y, Bhatt T, Yang F, Pai Y-C. Adaptive control reduces trip-induced forward gait instability among young adults. J Biomech 2012;45(7):1169-1175. DOI:10.1016/j.jbiomech.2012.02.001 [ Links ]

21. Pijnappels M, Bobbert MF, van Dieen JH. Push-off reactions in recovery after tripping discriminate young subjects, older non-fallers and older fallers. Gait Posture 2005;21(4):388-394. DOI:10.1016/j.gaitpost.2004.04.009 [ Links ]

22. Wright RL, Peters DM, Robinson PD, Watt TN, Hollands MA. Older adults who have previously fallen due to a trip walk differently than those who have fallen due to a slip. Gait Posture 2015;41(1):164-169. DOI: 10.1016/j.gaitpost.2014.09.025 [ Links ]

23. Menz HB, Lord SR, Fitzpatrick RC. Age‐related differences in walking stability. Age Ageing 2003;32(2):137-142. [ Links ]

24. Bohannon RW. Reference Values for the Timed Up and Go Test: A Descriptive Meta‐Analysis. J Geriatr Phys Ther 2006;29(2):64-68. [ Links ]

25. Portney LG, Watkins MP. Foundations of clinical research: applications to practice: Prentice Hall Upper Saddle River; 2000. [ Links ]

26. Mullineaux DR, Bartlett RM, Bennett S. Research design and statistics in biomechanics and motor control. J Sports Sci 2001;19(10):739-760. DOI:10.1080/026404101317015410 [ Links ]

27. Hopkins WG, Schabort EJ, Hawley JA. Reliability of power in physical performance tests. Sports med 2001;31(3):211-234. [ Links ]

28. Hollman JH, McDade EM, Petersen RC. Normative spatiotemporal gait parameters in older adults. Gait Posture . 2011;34(1):111-118. DOI: 10.1016/j.gaitpost.2011.03.024 [ Links ]

29. Matsuda K, Ikeda S, Nakahara M, Ikeda T, Okamoto R, Kurosawa K, et al. Factors affecting the coefficient of variation of stride time of the elderly without falling history: a prospective study. J Phys Ther Sci 2015;27(4):1087-1090. DOI: 10.1589/jpts.27.1087 [ Links ]

30. Beauchet O, Allali G, Annweiler C, Bridenbaugh S, Assal F, Kressig RW, et al. Gait variability among healthy adults: low and high stride-to-stride variability are both a reflection of gait stability. Gerontology 2009;55(6):702-706. DOI: 10.1159/000235905 [ Links ]

31. Menz HB, Latt MD, Tiedemann A, Mun San Kwan M, Lord SR. Reliability of the GAITRite< sup>®</sup> walkway system for the quantification of temporo-spatial parameters of gait in young and older people. Gait Posture 2004;20(1):20-25. DOI:10.1016/s0966-6362(03)00068-7 [ Links ]

Received: August 23, 2016; Revised: March 28, 2017; Accepted: June 07, 2017

Endereço para correspondência: Roberta Castilhos Detanico Bohrer. Rua Coração de Maria, 92. Bairro Jardim Botânico. Curitiba - PR, Brasil. CEP 80215-370. Email:

Creative Commons License This is an open-access article distributed under the terms of the Creative Commons Attribution License