A Novel Video Game–Based Device for Measuring Stepping Performance and Fall Risk in Older People

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A Novel Video Game–Based Device for Measuring Stepping Performance and Fall Risk in Older People Daniel Schoene, MSc, Stephen R. Lord, DSc, Paulien Verhoef, Stuart T. Smith, PhD ABSTRACT. Schoene D, Lord SR, Verhoef P, Smith ST. A novel video game– based device for measuring stepping performance and fall risk in older people. Arch Phys Med Rehabil 2011;92:947-53. Objective: To determine whether a dance mat test of choice stepping reaction time (CSRT) is reliable and can detect differences in fall risk in older adults. Design: Randomized order, crossover comparison. Setting: Balance laboratory, medical research institute, and retirement village. Participants: Older (mean age, 78.87⫾5.90y; range, 65– 90y) independent-living people (N⫽47) able to walk in place without assistance. Interventions: Not applicable. Main Outcome Measures: Reaction (RT), movement, and response times of dance pad– based stepping tests, Physiological Profile Assessment (PPA) score, Digit Symbol Substitution Test (DSST) score, time to complete the Trail Making Test (TMT) A⫹B, Fall Efficacy Scale International (FES-I) score, Activities-specific Balance Confidence (ABC) Scale score, and Incidental and Planned Exercise Questionnaire (IPEQ) incidental IPEQ activity subscore. Results: Test-retest reliability of the dance mat CSRT response time was high (intraclass correlation coefficient model 3,k⫽.90; 95% confidence interval [CI], .82–.94; P⬍.001) and correlated highly with the existing laboratory-based measure (r⫽.86; 95% CI, .75–.92; P⬍.001). Concurrent validity was shown by significant correlations between response time and measures of fall risk (PPA: r⫽.42; 95% CI, .15–.63; P⬍.01; TMT A: r⫽.61; 95% CI, .39 –.77; TMT B: r⫽.55; 95% CI, .31–.72; DSST: r⫽⫺.53; 95% CI, ⫺.71 to ⫺.28; P⬍.001; FES-I: Spearman ␳⫽.50; 95% CI, .25–.69; ABC Scale: Spearman ␳⫽⫺.58; 95% CI, ⫺.74 to ⫺.35; P⬍.01). Participants with moderate/high fall-risk scores (PPA score ⬎1) had significantly slower response times than people with low/mild fall-risk scores (PPA score ⬍1) at 1146⫾182 and 1010⫾ 132ms, respectively (P⫽.005), and multiple fallers and single/ nonfallers showed significant differences in RT (883⫾137 vs 770⫾100ms; P⫽.009) and response time (1180⫾195 vs 1031⫾145ms; P⫽0.017).

From Neuroscience Research Australia, Sydney (Schoene, Lord, Verhoef, Smith) and University of New South Wales, Sydney (Schoene, Lord), New South Wales, Australia. Supported by National Health and Medical Research Council (NHMRC) Project (grant no. 568724) and NHMRC Career Development Award-Industry. A commercial party having a direct financial interest in the results of the research supporting this article has conferred or will confer a financial benefit upon the author or 1 or more of the authors. The step training system will be available for purchase from Neuroscience Research Australia. No individual author will have direct financial benefit from sale of the system. Reprint requests to Stuart T. Smith, PhD, Neuroscience Research Australia, Hospital Rd, Randwick NSW 2031, Australia, e-mail: [email protected]. Published online May 6, 2011 at www.archives-pmr.org. 0003-9993/11/9206-01008$36.00/0 doi:10.1016/j.apmr.2011.01.012

Conclusions: The new dance mat device is a valid and reliable tool for assessing stepping ability and fall risk in older community-dwelling people. Because it is highly portable, it can be used in clinic settings and the homes of older people as both an assessment and training device. Key Words: Accidental falls; Aged; Reaction time; Rehabilitation. © 2011 by the American Congress of Rehabilitation Medicine HE ABILITY TO MAKE well-timed and appropriately T directed responses to events surrounding us underpins our ability to successfully interact with our environment. Step1

ping, changing the base of support relative to our center of mass, provides the means by which we are able to avoid obstacles and counter such potentially destabilizing events as slips, trips, and missteps and therefore helps avoid falls. Protective stepping may be initiated volitionally when a threat to balance is perceived or induced reflexively when a disturbance moves the center of mass relative to the base of support at a speed that prevents engagement of volitional strategies.2 A number of studies suggest that both volitional and induced stepping abilities are significantly impaired in older individuals and significantly associated with fall risk.3 Older adults, particularly those with a history of falling, tend to be slower in initiating volitional step responses,4 make inappropriately directed or multiple short steps in response to an external perturbation of balance,5 and have an increased chance of collision between the swing and stance legs during compensatory stepping.6 Several stepping tests exist that discriminate between fallers and nonfallers,4,7-11 with limited evidence that cognitive load is needed.9 The choice stepping reaction time (CSRT) task has been better to discriminate between fallers and nonfallers than other sensorimotor and balance measures4 and to predict falls in older people, mediated through physiologic and cognitive pathways.12 Reaction time (RT) can be affected significantly List of Abbreviations ABC CI CSRT DSST FES-I FOF ICC ICC3,k IPEQ LAB MAT MT PPA RT TMT

Activities-specific Balance Confidence confidence interval choice stepping reaction time Digit Symbol Substitution Test Falls Efficacy Scale International fear of falling intraclass correlation coefficient intraclass correlation coefficient model 3,k Incidental and Planned Exercise Questionnaire laboratory-based measure of CSRT dance mat measure of CSRT movement time Physiological Profile Assessment reaction time Trail Making Test

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by cognitively demanding tasks and age-related deterioration in information processing.13,14 Choice RT tasks, in which 2 or more alternatives are presented to participants,15 have been used to investigate age-related changes in responses that require complex fast information processing, such as the generation of fast volitional stepping to avoid a fall.4 However, these tests require the use of relatively fixed and specialized laboratory equipment. This article reports the development of a portable computer-based version of the CSRT test using a dance mat input device for video games. The dance mat approach has several advantages over current laboratorybased instruments for measuring step reaction time. It is low cost, can be administered at any location, and test duration is less than 5 minutes. Moreover, it enables individuals to assess their own performance and therefore is an example of telehealth technology that opens the opportunity to deliver health care to regional, rural, or remote areas and track performance changes over time. Furthermore, as a computer game device, it also offers a potentially effective approach for preventing falls in independent-living older adults by engaging them in repetitive stepping exercise.16 The primary aims of this study were to (1) determine the test-retest reliability of the new dance mat measure of CSRT (MAT), (2) assess the convergent validity against the established laboratory-based measure of CSRT (LAB) device, and (3) establish the concurrent validity of the CSRT test by its associations with and discriminative ability on a range of physiologic, cognitive, psychological, and health-related measures of fall risk, as well as retrospective falls. METHODS Participants A convenience sample of 47 independent-living older people (mean age, 78.87⫾5.90y) participated in this study. Participants consisted of attendees of community talks and residents of a retirement village. Eligibility criteria were 65 years and older, able to walk in place without assistance (even if walking aids normally were used for ambulation), living in the community, and able to understand English. Table 1 lists characteristics of study participants. Informed consent was obtained from all participants and the study was approved by

the University of New South Wales Human Research Ethics Committee. Test Description and Administration Dance mat measure of CSRT. A custom-made dance mat choice reaction time device,a measuring 150⫻90cm, contained 12 step panels, of which 6 were used for this test: 2 central stance panels, 2 front panels, 1 left panel, and 1 right panel (fig 1A). An image was printed on each panel; left and right cartoon feet on the central panels and directional arrows on the other panels. The mat and a liquid crystal display monitor (resolution, 1280⫻768 pixels; 60Hz refresh rate) were connected to a computer running Microsoft Windows XP(SP3)b with the display screen positioned on the floor 1m in front of the mat. Presentation of visual stimuli on the screen and recording of participant step responses was controlled using custom software written in Python Version 2.6.c During measurement of CSRT, participants were asked to stand on the 2-stance panels. The organization of the dance mat panels was presented on the display screen (see fig 1A). In the rest state, each screen panel showed a black-outlined figure corresponding to a step panel on the dance mat. A trial consisted of a randomly selected arrow changing its color from white to blue on the screen. Participants then were required to step onto the corresponding dance mat panel as quickly as possible. When a correct step was made, the symbol on the screen changed color to green to indicate completion of the step. Participants were informed that stimulus presentation would be random and they should not try to anticipate the location of stimuli. Time between trials also was randomized, with stimuli occurring 1 and 2 seconds after the participant returned both feet to the central stance panels. After practice trials, a random sequence was presented, with 5 repeats per panel. Laboratory measure of CSRT. The laboratory CSRT device consisted of a wooden platform (84⫻74cm) that contained 6 rectangular panels (30⫻15cm), 2 stance panels, 1 stepping panel in front of each foot, and 1 stepping panel to the side of each foot (fig 1B).4 One stepping panel for each trial was illuminated and participants were instructed to step onto this panel as quickly as possible. The previously reported intraclass correlation coefficient (ICC) for test-retest reliability of this device in a similar sample of community-dwelling older people was .84 (95% confidence interval [CI], .69 –.93).17

Table 1: Study Population Characteristics Variable

Value

Mean age (y) ⫾ SD Age range Women (%) Fallen past year (%) Multiple fallers (%) Walking aids (%) No. of chronic diseases (minimum–maximum) People with pain (%) PPA score FES-I score ABC Scale score Incidental activity score DSST score* TMT A score* TMT B score*

78.87⫾5.90 65–90 55 35 50 13 2.78 (0–6) 26 0.62⫾0.89 24.28⫾9.98 77.04⫾23.10 26.52⫾14.88 52.43⫾12.76 44.79⫾14.81 118.69⫾54.62

NOTE. N⫽47. Values expressed as mean ⫾ SD (range) or % unless noted otherwise. *N⫽46.

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Outcome Measures CSRT outcome measures. For both MAT and LAB, the respective software programs recorded (in milliseconds) step RT, time between stimulus presentation and liftoff of either the left or right foot from the central stance panels; movement time (MT), time between foot liftoff and touchdown on a panel; response time, the sum of RT and MT. In addition, the experimenter categorized (yes/no) stepping strategies of participants as “weight shifters” and “eye movers.” Weight shifters visibly transferred their center of mass over the stepping foot in most trials, whereas non–weight shifters executed mostly tapping step responses. Eye movers made multiple eye movements between the screen and mat during most trials. Non– eye movers made few, if any, such eye movements and instead looked mainly at the display screen. Physical, psychological, and cognitive measures of fall risk. Physical fall risk was assessed by using the Physiological Profile Assessment (PPA), a test battery that predicts the risk for multiple falls in community-dwelling older people with 75% accuracy.18 The PPA consists of 5 tests of sensorimotor

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Fig 1. (A) MAT. Each panel on the mat contains a switch that could be read by the controlling computer software. Participants stand on the 2 central stance panels and respond (step) to stimuli presented on the computer display screen, in this case, a front left step for the MAT version of the test. (B) LAB. Participants stand on the black footplates and step onto 1 of the 4 illuminated foot plates to the left, front left, front right, or right.4

functions, including contrast sensitivity, simple hand RT, sway on a foam as measure of balance, joint position sense as a measure of peripheral sensation, and knee extension strength. A weighted z-transformed overall score is computed from these 5 tests, with higher scores indicating higher fall risk.19 Psychological measures were fear of falling (FOF) and fallsrelated self-efficacy. FOF was assessed by using the Falls Efficacy Scale International (FES-I),20 and falls-related selfefficacy, by using the Activities-specific Balance Confidence (ABC) Scale.21 Both questionnaires consist of 16 items and have excellent psychometric properties.20,21 To assess the amount of physical activity, we used the Incidental and Planned Exercise Questionnaire (IPEQ), which measures activity levels relating to both basic and more demanding activities and has excellent psychometric properties.22 To evaluate cognitive performance, the Digit Symbol Substitution Test (DSST) and Trail Making Test (TMT) were chosen. Both tests are very sensitive to changes in cognitive function during aging and have good to excellent measurement properties.23 The DSST assesses attention, response speed, visuomotor coordination, and incidental memory. The number of correct marks after 120 seconds was counted. The TMT as a test of cognitive processing and executive functioning evaluates scanning, visuomotor tracking, divided attention, and cognitive flexibility. The TMT consists of 2 parts; A and B. Time in seconds to complete the test was measured. Participants who could not complete the TMT B in 5 minutes were assigned a time of 300 seconds.24 We also computed the difference in execution time between TMT B and TMT 〈 because it is much less dependent on individual differences in

visuomotor speed and gives a good estimate of executive function.23 Finally, people were asked whether they experienced falls in the 12 months before the assessment. Participants were classified as either multiple fallers or single/nonfallers. Because 1 fall during a 12-month period may be due to chance rather than reflecting a true increased fall risk, we put single and nonfallers in 1 group for analysis. Procedure Testing was performed on 2 occasions in a laboratory at Neuroscience Research Australia or in the gymnasium of a retirement village. To minimize some of the potential threats to repeated measurements of CSRT, all tests were performed on each participant at the same location and time for each test occasion. On the first occasion, participants were given questionnaires relating to demographic, health, activity, and fallrelated information and underwent cognitive ability tests. Thereafter, stepping performance was measured using MAT and LAB in randomized order. After completion of the stepping tests, the PPA was conducted. On the second occasion (7.03⫾0.97d after the first), participants returned all questionnaires and completed the dance mat stepping tests for computation of test-retest reliability. Data Analysis The mean value of the 5 repeats for each mat panel was computed for each of the 3 time variables (RT, MT, and response time). Shapiro-Wilk test was used to assess the disArch Phys Med Rehabil Vol 92, June 2011

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Table 2: Reliability - ICCs for Stepping Test Within 1 Week

Table 3: Validity - Correlation Coefficients for Stepping Tests

Instrument

Outcome

ICC (95% CI)*

Instrument

Outcome

Correlation (95% CI)*

MAT

RT MT Response time

.86 (.75–.92) .91 (.84–.95) .90 (.82–.94)

LAB⫺MAT

RT MT Response time

.81 (.69⫺.89) .82 (.70⫺.90) .86 (.75⫺.92)

NOTE. N⫽47. *All (P⬍.001).

NOTE. N⫽47. *All P⬍.001.

tributions of timing variables. A 2-way mixed-effects averagemeasure ICC model (intraclass correlation coefficient model 3,k [ICC3,k]) was used to assess test-retest reliability,25 which was rated poor (⬍.40), fair to good (.40 –.75), and excellent (⬎0.75).26 Convergent validity was determined by using Bland-Altman plots and assessing correlation coefficients between MAT and LAB.27 Concurrent validity was assessed by investigating the ability of the CSRT test to distinguish between subgroups with different risk profiles. Pearson/Spearman rank correlation coefficients and Student t tests/Mann-Whitney U tests were used for normally/non–normally distributed data. Type I error rate was set to 5%, and 95% CIs were computed for all parameters. Processing and analysis of data were conducted using Matlab Version 7.10d and PASW Version 18 for Windows.e

significant associations with the MAT test of moderate size (table 4). Age was a discriminator of step performance, with people 80 years and older having slower RTs (824⫾119ms) and response times (1103⫾167ms) than people younger than 80 years (753⫾97ms; P⫽.030; 1008⫾145ms; P⫽.046, respectively). Furthermore, the MAT was able to discriminate between people with different levels of fall risk. Comparisons between multiple fallers and single/nonfallers showed significant differences in RTs (883⫾137 vs 770⫾100ms; P⫽.009) and response times (1180⫾195 vs 1031⫾145ms; P⫽.017), but not MTs. People with moderate/high (PPA score ⬎1) and low/mild fall-risk scores (PPA score ⬍1) also were significantly different in response times (1146⫾182 vs 1010⫾132ms; P⫽.005). Weight transfer and eye movements toward the mat significantly influenced performance (table 5). Participants who transferred their body weight while stepping had longer MTs (281⫾64ms) than people who tapped the target panel (243⫾61ms; P⫽.048). People who looked from the screen to the mat before or while they were stepping also had longer RTs and MTs (865⫾138ms; P⫽.042; 320⫾71ms; P⫽.046) compared with participants who did not transfer their gaze (774⫾104ms; P⫽.040; 257⫾67ms; P⫽.046). The group of participants who transferred their gaze also showed trends to poorer scores on cognitive tests (DSST, P⫽.068; TMT A, P⫽.057; TMT B, P⫽.026; TMT A⫺TMT B, P⫽.079).

RESULTS Log-transformed time-based measures of CSRT and other outcome measures with the exception of psychological selfreports were normally distributed (Wilk-Shapiro normal test ⬍.05). Test-retest results are listed in table 2. ICCs for the MAT were excellent, with parameters ranging from .86 to .91 (P⬍.001). Figure 2 shows Bland-Altman plots for RT and MT for LAB versus MAT. Although almost all values were between the limits of agreement, there was a systematic shift to slower RT and faster MT for MAT. On average, participants needed 175 milliseconds longer for the MAT test compared with the LAB test. Pearson correlation coefficients comparing times between LAB and MAT were excellent (table 3). With the exception of physical activity (Pearson r⫽⫺.28; 95% CI, ⫺.004 to 0.53; P⫽.054), all fall-risk measures showed

DISCUSSION This study shows that the dance mat step timing device provides a satisfactorily reliable measurement of CSRT in community-dwelling older people. Correlations between the old and new measure were high, but did not agree completely,

Fig 2. Bland-Altman plots representing comparisons between LAB and our MAT. (A) RT for LAB-MAT, (B) MT for LAB-MAT. In each plot, the mean line represents the mean difference between any 2 measures, with upper and lower lines representing the limits of agreement (2SD).

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VIDEO GAME DEVICE FOR MEASURING STEPPING AND FALL RISK, Schoene Table 4: Validity - Correlation Coefficients (95% CI) for RT for MAT and Fall-Risk Measures Physical Fall Risk (PPA)*

Cognition†‡

FOF*§

Physical Activity

Overall score .42 (.15 to .63) R2⫽17.4% Knee extension ⫺.48 (⫺.67 to ⫺.22) R2⫽23.0% Sway .38 (.10 to .60) R2⫽14.4% Contrast sensitivity ⫺.39 (⫺.61 to ⫺.12) R2⫽15.2% Hand RT储 .34 (.06 to .57) R2⫽11.6%

DSST ⫺.53 (⫺.71 to ⫺.28) R2⫽28.1% TMT A .61 (.39 to .77) R2⫽37.6% TMT B .55 (.31 to .72) R2⫽30.1% TMT B⫺A* .46 (.20 to .66) R2⫽21.4%

FES-I .50 (.25 to .69) R2⫽24.9% ABC Scale ⫺.58 (⫺.74 to ⫺.35) R2⫽33.2%

IPEQ ⫺.28 (⫺.53 to .004) R2⫽8%

NOTE. R2 is coefficient of determination. *P⬍.01; †P⬍.001; ‡N⫽46; §Spearman rank correlation; 储P⬍.05.

as shown in the Bland-Altman plot, indicating a new measure of CSRT that is cognitively more demanding. Furthermore, the MAT test correlated moderately with a range of fall-risk measures. Adults older than 80 years recorded slower times than those 80 years and younger, and multiple fallers recorded slower times (⬃150ms slower in their response time, 110ms of which was in RT) than non–multiple fallers, differences that likely reflect perceptual and cognitive impairments. The data presented show that RT for the MAT was significantly longer than for the LAB. It is likely that this difference may be accounted for by extra processing time required to translate from the spatial coordinates of the display screen, where the stimulus was presented to the spatial coordinates of the mat on which the response was executed. However, in the case of the LAB task, the spatial location of stimulus appearance and response execution was coincident; both were under the feet of the participant. It is well known that spatial coordinate frame transformations introduce significant processing latencies in object recognition tasks,28 and as such, a cost in step RT may result from sensorimotor transformations involved in dance mat CSRT tasks.29 It was also observed that MT was faster for the MAT compared to the LAB device. The LAB consisted of a wooden frame in which the plastic switch plates were built. Each switch plate on the laboratory device was separated from the others by small raised edges, which may have caused participants to be more cautious in making their steps to avoid a possible trip on the edges of switch and frame. However, for the dance mat device, all step-sensitive panels were contained within a single smooth flat surface, and participants may have felt more confident to step faster on the even 1-piece structure of the mat. Table 5: RTs for MAT and Subgroups Group or Subgroup

Mean ⫾ SD RTs (ms)

Overall mean (n⫽47) Age ⱖ80y (n⫽24) Multiple fallers (n⫽8) PPA score ⱖ1 (n⫽16) Watch mat (n⫽8) Transfer mat (n⫽21)

1056⫾162 1102⫾167* 1179⫾194* 1145⫾181* 1184⫾186* 1083⫾158*

*Significantly different from overall mean value (P⬍.05).

Correlations between cognitive measures and the dance mat step timing measures were moderate. People who transferred their gaze needed more time to step onto the correct panel and had trends to poorer performance in cognitive tests. These results are consistent with other studies reporting that compared with single/nonfallers, multiple fallers performed worse on a number of cognitive measures, including choice RT, executive function, and visual attention, compared with single/ nonfallers, indicating a general cognitive decline in recurrent fallers.30 Cognitive function also has been predictive for future falls in community-dwelling old people,31 and cognitive impairment and dementia are known risk factors for falls.32,33 Visuospatial processing introduces a greater challenge for postural tasks than nonspatial tasks.17 Translation of task-relevant perceptual information from screen-based to dance mat– based frames of reference therefore may provide a technique by which impairments in visuospatial processing can be measured. The MAT presented here correlated significantly with measures of sensorimotor function assessed by using the PPA, an instrument shown to predict the risk for multiple falls in community-dwelling older people with 75% accuracy.18 The response time of the MAT test correlated moderately with knee extension strength, balance control measured by using postural sway, contrast sensitivity, and simple RT, all independent risk factors for falls.34 These measures also are likely to reflect underlying processes involved in the generation of protective stepping responses because they represent perceptual encoding of the environment, information processing, and response generation. This therefore suggests the possibility that CSRT performance measured by using the dance mat system may provide a proxy measure of fall-risk. In addition, this study also investigated the relationship with psychological processes and self-reported levels of physical activity related to the incidence of falls in older people. It was found that the measures of FOF and falls efficacy, FES-I and ABC, respectively, moderately correlated with response times measured by using the dance mat system. Studies have shown that both FOF and falls efficacy are associated with previous and prospective falls.35,36 Falls efficacy is associated with objective measures of physical fall risk, such as balance and strength,35 and moreover, concerns about falling elicit greater gait adjustments under conditions of postural threat.37 The study also examined the relationship between self-reported Arch Phys Med Rehabil Vol 92, June 2011

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activity, measured by using the incidental activity subscore of the IPEQ,22 and step timing. The relationship between activity level and fall risk generally is held to be U shaped, with very active and very inactive people at a higher risk38 than those who participate in moderate levels of activity. More active and therefore fitter people are likely to show better performances in tests of physical39-41 and cognitive42,43 ability. Although correlation between IPEQ scores and MAT was low, the data suggest that people who self-report higher levels of physical activity performed better on the MAT. Study Limitations This study has several limitations. First, although sample size was sufficiently powered to show the validity and stability of measurement of the dance mat system, some comparisons showed only trends toward statistical significance with wide CIs (eg, physical activity and overall step response time, r⫽⫺.28; 95% CI, ⫺.004 to .53; P⫽.054). In an extension to the present study, these issues will be investigated in a larger random (rather than convenience) sample. Second, the study was performed in 2 different testing locations; a laboratorybased environment and a general-purpose hall in a retirement facility. Any factors that change error variance across testing occasions or testing location have implications for reporting of the stability of measurements over time. Third, it is acknowledged that this study was conducted in a nonrandom sample of independently living adults 65 years and older without serious cognitive impairment. As a consequence, conclusions drawn from the results are limited to this population. Finally, a computer is required for this test and it has yet to be shown that older people can perform it by themselves. CONCLUSIONS This study reports on a new MAT as a proxy of fall risk that is satisfactorily valid and reliable in a population of independently living older adults without severe cognitive and physical impairment. The system offers a safe, low-cost, portable, easyto-use measure of CSRT in clinical settings and homes of older people to determine fall risk and monitor long-term changes. To improve the measure, future research should address how well the validity and reliability of this device generalizes to a wider range of older adults and outcome measures (eg, tests of mobility and daily function). Acknowledgments: We thank Jamie Lennox and Thomas Davies for software programming and Ulrike Bruns for assisting with the figures. References 1. Shumway-Cook A, Woollacott MH. Motor control: theory and practical applications. Baltimore: Williams & Wilkins; 1995. 2. Maki BE. Postural strategies. In: Binder MD, Hirokawa N, Windhorst U, editors. Encyclopedia of neuroscience. Berlin: Springer; 2009. p 3222-7. 3. Maki BE, McIlroy WE. Control of rapid limb movements for balance recovery: age-related changes and implications for fall prevention. Age Ageing 2006;35:ii12-8. 4. Lord SR, Fitzpatrick RC. Choice stepping reaction time. J Gerontol A Biol Sci Med Sci 2001;56:M627-32. 5. McIlroy WE, Maki BE. Age-related changes in compensatory stepping in response to unpredictable perturbations. J Gerontol A Biol Sci Med Sci 1996;51A:M289-96. 6. Maki BE, Edmondstone MA, McIlroy WE. Age-related differences in laterally directed compensatory stepping behavior. J Gerontol A Biol Sci Med Sci 2000;55:M270-7. Arch Phys Med Rehabil Vol 92, June 2011

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Suppliers a. Falls and Balance Research Group, Neuroscience Research Australia, Hospital Rd, Randwick NSW 2031, Australia. b. Microsoft Corp, One Microsoft Way, Redmond, WA 98052-6399. c. Python Software Foundation, PO Box 37, Wolfeboro Falls, NH 03896-0037. d. The Mathworks Inc, 3 Apple Hill Dr, Natick, MA 01760-2098. e. SPSS Inc, 233 Wacker Dr, 11th Fl, Chicago, IL 60606.

Arch Phys Med Rehabil Vol 92, June 2011