Author s Accepted Manuscript

Author s Accepted Manuscript The High Frequency Component of the Vertical Ground Reaction Force is a Valid Surrogate Measure of the Impact Peak Tim Blackmore, Richard W. Willy, Mark W. Creaby www.elsevier.com/locate/jbiomech PII: DOI: Reference: To appear in: S00219290(15)007253 http://dx.doi.org/10.1016/j.jbiomech.2015.12.019 BM7485 Journal of Biomechanics Received date: 24 April 2015 Revised date: 22 October 2015 Accepted date: 14 December 2015 Cite this article as: Tim Blackmore, Richard W. Willy and Mark W. Creaby, The High Frequency Component of the Vertical Ground Reaction Force is a Valid Surrogate Measure of the Impact Peak, Journal of Biomechanics http://dx.doi.org/10.1016/j.jbiomech.2015.12.019 This is a PDF file of an unedited manuscript that has been accepted fo publication. As a service to our customers we are providing this early version o the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain

1 2 3 4 5 6 7 8 22 nd October 2015 Short Communication The High Frequency Component of the Vertical Ground Reaction Force is a Valid Surrogate Measure of the Impact Peak a Tim Blackmore MSc, Ph.D, b Richard W. Willy Ph.D, PT and a Mark W. Creaby Ph.D. a School of Exercise Science, Australian Catholic University, Brisbane, Australia. b Department of Physical Therapy, College of Allied Health Sciences, East Carolina University, Greenville, NC, USA. 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 Keywords: Proxy, running, rearfoot strikers. Word count: 1990 (excluding references). Number of tables: 2 Number of figures: 2 Supplementary material: 5 Correspondence address: Dr. Tim Blackmore School of Exercise Science Australian Catholic University 1100 Nudgee Road Banyo Brisbane, 4014 Australia Phone: +61 (0) 7 3623 7692 Email: Tim.Blackmore@acu.edu.au Abstract

34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 Identification of the impact peak (IP) from the vertical ground reaction force (vgrf) is required to calculate indices of impact loading during running. The IP, however, is not always clearly discernible. Previous researchers have estimated the timing of the IP using surrogate methods, the most common of which is a set time point of 13% stance (TPS). Information contained within the high frequency (HiF) component of the vgrf may also have a utility as a surrogate measure, but the validity of either approach is currently unknown. The purpose of this study is to evaluate the criterion validity for a newly proposed HiF method and the previously used TPS method against a criterion measure for a group of rearfoot striking runners. Fifty participants ran at a standardized speed (3.3m. s 1 ) on an instrumented treadmill. Five consecutive stance phases were analyzed for the participant s dominant limb. BlandAltman was used to assess agreement between the criterion method and each surrogate method. Good agreement of the HiF and TPS methods with the criterion method indicate that both methods are likely to be valid surrogate approaches to estimate vgrf impact loading indices. For all impact loading indices, smaller bias and limits of agreement (LOA) were observed with the HiF method when compared to the TPS method. Therefore, it is concluded that the HiF method should be used in preference to the TPS method when it is available. 51 52 53 Symbols 54 55 56 57 58 AVLR = average vertical loading rate BW = bodyweight cm = centimeter HiF = high frequency Hz = Hertz

59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 IP = impact peak IVLR = instantaneous vertical loading rate kg = kilogram km = kilometer LOA = limits of agreement LoF = low frequency m = meter ms = millisecond N = Newton s = second SD = standard deviation TPS = thirteen percent (13%) stance vgrf = vertical ground reaction force Introduction 86 87 88 89 90 When running, rearfoot strikers typically demonstrate an impact peak (IP) in the vertical ground reaction force (vgrf) within the first 50ms of stance (Nigg et al., 1995). Identification of the IP is required to determine its magnitude and timing, and to calculate loading rate. These measures, calculated from the early part of stance (Nigg et al., 1995) are widely studied and have been linked with both injuries (Noehren et al., 2013; Zadpoor and

91 92 93 94 95 96 97 Nikooyan, 2011) and performance (Munro et al., 1987) in rearfoot striking runners. Not all runners exhibit a discernible IP, and gait modifications, such as an increase in running cadence, reduce the incidence of the IP (Heiderscheit et al., 2011). Thus directly calculating these indices of impact loading is not always possible. To address this, researchers have utilized alternative methods to predict the timing of the IP where one is not clearly discernible (Goss and Gross, 2013; Lieberman et al., 2010; Samaan et al., 2014; Willy et al., 2008). 98 99 100 101 102 103 104 105 106 107 When an IP was present in some trials, but not others, Lieberman et al., (2010) used the timing of the IP for each participant from the IP observed in the participants other trials. This was then used as a surrogate for the timing of the IP in trials without a discernible IP. This method, however, relies on the IP being present in at least some trials. An alternative method presented by Willy et al. (2008), and used by others (Samaan et al., 2014), does not require the IP in any trials. Based on the timing of the IP, Willy et al. (2008) concludes that a set time point of 13% stance (TPS) in the absence of an IP could be used. However, this approach does not account for changes in the timing of the IP, which may occur between individuals and between conditions. While the relationship between the time of the IP and the TPS method has been evaluated, the validity of this approach is not known. 108 109 110 111 112 113 114 115 Although a clearly discernible IP in the vgrf may not be present, characteristics of this peak appear to be present in the high frequency signal of the vgrf. This is visible when the vgrf is separated into its high (HiF) and low (LoF) frequency components via the frequency domain (Shorten and Mientjes, 2011). Once separated, the LoF components (0Hz to 10Hz) resemble a half sinusoidal wave with a peak that appears to coincide with that of the passive peak of the vgrf, whereas the HiF components (10Hz to ~50Hz) are characterized primarily by a single peak, which occurs early in stance and appears to coincide with the IP of the vgrf. Therefore, identification of the timing of the HiF peak may provide a more

116 117 118 119 120 appropriate surrogate measure for identifying the timing of the IP and thus other indices of impact loading, such as loading rate. Whilst in theory the peak in the HiF component of the vgrf may coincide with the IP, the agreement between these two approaches has not been evaluated. If they coincide, this may provide a valid estimation of impact loading indices in participants where a discernible IP does not exist. 121 122 123 124 125 The purpose of this study was to evaluate the criterion validity for the HiF method and a previously used surrogate measure (TPS) against the criterion measure for the determination of the IP for a group of rearfoot striking runners. We then sought to assess the criterion validity across these various methods for the calculation of average vertical loading rate (AVLR) and instantaneous vertical loading rate (IVLR) in the same group of runners. 126 Methods 127 Participants 128 129 130 131 132 Fifty runners participated in this study (Table 1). The study was approved by the East Carolina University Human Subjects Research Board. Written and verbal consent were obtained from all participants. Inclusion criteria for study participation were: rearfoot strikers, consistently running at least 10 km/week for at least the previous 6 months, free of lower extremity injuries for the past three months and no previous lower extremity surgery. 133 Procedures 134 135 136 137 138 Following an eightminute, selfpaced treadmill accommodation period, GRF data were acquired (MotionMonitor, Innovative Sports, Chicago, Ill, USA) as participants ran at a standardized speed (3.3 m. s 1 ) on an instrumented treadmill (TM09, Bertec Corp., Worthington, OH, USA) with the integrated force plate sampling at 1000 Hz. Five consecutive stance phases were analyzed independently for the right and left legs.

139 Data analysis 140 141 142 143 144 145 146 147 148 149 The threshold for footstrike and toeoff was set at 20N. Data were separated into individual stance phases using a custom MATLAB script (version 7.10.0.499, Mathworks, Cambridge, UK) and lowpass filtered at 50Hz (Butterworth, 4 th order). The HiF and LoF signals were isolated using a custom MATLAB script (Supplementary Material 1). The vgrf for each stance phase was spectrally decomposed into the frequency domain using the discrete Fourier transform. The HiF components of the signal were separated from LoF components by isolating frequencies equal to or greater than 10Hz (i.e. 10Hz to ~50Hz), while LoF components were constructed from the remaining lower frequencies (Shorten and Mientjes, 2011). Both HiF and LoF signals were recomposed into the time domain using the inverse Fourier transform to form two new signals (Figure 1). 150 **** Figure 1 near here **** 151 152 153 154 155 156 157 158 159 160 The IP, IVLR and AVLR were calculated from the vgrf and form the criterion variables for this study. The IP was defined as the first peak in the vgrf (within the first 50ms of stance)(nigg et al., 1995). Both IVLR and AVLR were calculated between 20% and 80% of the period between footstrike and the occurrence of the IP (Milner et al., 2006). The IVLR was the steepest point in the slope of the vgrf during this period calculated using the first central difference method. The AVLR was calculated as the average slope in the vgrf between the 20% and 80% points. For each participant, a minimum of three trials with a clear IP were required to be included in the IP group for further analyses. Those without a clear IP in at least three trials were allocated to the NO IP group and were subsequently excluded from further analyses. 161 162 In the IP group, the timings of the peak magnitude of the HiF loads and of TPS were identified and used to calculate the surrogate measures in the same way as those used for the

163 164 165 criterion measures. The surrogate timings and the corresponding magnitude from the vgrf was used to calculate the surrogate measures to form three new variables (IP, IVLR & AVLR) for each surrogate method (HiF & TPS). 166 Statistical analysis 167 168 169 170 171 172 173 All data were normally distributed except for age (Supplementary Material 2). An alpha level was set at 0.05 (SPSS v.20, IBM Corp, Armonk, NY). Criterion validity was examined in the IP group by assessing the agreement between the criterion approach and the two surrogate methods using the BlandAltman method (Bland and Altman, 2010) in SigmaPlot (v.12, Systat Software, San Jose, CA). This was performed by plotting the difference for each dependent variable between the criterion and surrogate method against the mean data for the criterion and surrogate methods. 174 Results 175 176 Fortytwo participants were assigned to the IP group, and 8 to the NO IP group. Mean demographic data were similar between the IP and NO IP groups. 177 **** Table 1 near here **** 178 179 180 181 182 183 For the right leg data, when compared to the criterion measure using BlandAltman, no obvious relationship between the difference and the mean was observed for the IP, AVLR or IVLR using either surrogate method (Figure 2). Both approaches showed a bias towards a lower mean in all but one case: the IVLR in the HiF method. In all measures the biases and limits of agreement (LOA) were smaller with the HiF method (Table 2). Analyses of the left leg data were consistent with the findings for the right leg (Supplementary Material 3 & 4). 184 **** Table 2 near here **** 185 **** Figure 2 near here ****

186 Discussion 187 188 189 190 191 192 193 194 195 196 The focus of this study was to assess the criterion validity of two surrogate methods to determine vgrf IP characteristics. Bland and Altman (2010) state that if the values that fall within the LOA are not clinically important then the methods can be used interchangeably, with the decision as to what is important being clinical and not statistical. Broadly considering our findings, it would appear that both methods performed well due to the small bias and LOA, but as these measures were lower in the HiF method when compared to the TPS method, it would suggest that the HiF method was superior. The validity of either surrogate approach must be made in the context of the population, or populations, studied (Bland and Altman, 2010), and therefore it is not possible to broadly conclude whether either surrogate method has acceptable agreement with the criterion method. 197 198 199 200 201 202 203 204 205 206 207 208 209 210 One approach to evaluating the validity of the surrogate methods would be to consider the error introduced by the use of the surrogate (characterized by the LOA) relative to the variation normally observed within the studied population (e.g. SD). For example, in the running literature indices of impact loading are frequently characterized in the study of lower limb stress fractures. Examination of this literature indicates typical IP magnitudes of approximately 2BW, with a within group SD ranging from 0.13BW to 0.45BW (Zadpoor and Nikooyan, 2011). Given a normal distribution, the LOA suggest that 95% of the time we can expect a bias of between 0.06BW and 0.01BW for the HiF method (an error of up to 3.64%) and between 0.21BW and 0.07BW for the TPS method (an error of up to 12.73%). Thus, the LOA for the HiF method do not overlap the smallest within group SD suggesting that it could be considered valid for use in this population. The LOA associated with the TPS method however, do overlap suggesting that it may not be a valid approach. Similarly, in considering the validity of the two approaches for estimating loading rates, the smallest within group SD from the literature (Zadpoor and Nikooyan, 2011) for both the AVLR

211 212 213 214 (15.03BW. s 1 ) and IVLR (17.33BW. s 1 ) are greater than the LOA for both surrogate methods suggesting that both methods are valid in this population. For both AVLR and IVLR, the LOA are less when using the HiF method, suggesting that this approach is more appropriate when compared to the TPS method. 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 Given the IP is a summation of both the HiF and LoF components the IP is always delayed when compared to the timing of the HiF peak (Supplementary Material 5A). A visual examination of the IP magnitude highlights that the HiF method consistently underestimates the IP magnitude (Supplementary Material 5B), but the TPS method is less systematic. This systematic underestimation is attributed to the use of the HiF method. As the timing of the HiF signal is calculated from the acquired vgrf, and not from a time relative value such as TPS, it responds more accurately to changes in the timing of the IP. Ultimately, correct identification of the IP enables a more accurate estimation of AVLR, but is less pertinent to IVLR due to the nature of its instantaneous calculation. As the IVLR is defined as the steepest point in the slope of the vgrf between 20% and 80% of the time between heelstrike and the IP, small changes in identification of the time of the IP will only alter the start and end point of the window in which the IVLR is calculated. This is a key reason why both the HiF and TPS methods result in a smaller bias for the IVLR than they do for the AVLR (which is dependent upon the steepness of the entire slope for 20% to 80%) and the IP (which is dependent upon the time of the IP). 230 231 232 233 234 The validation of the HiF and TPS surrogate methods in the situation where it would be used (e.g. in a trial with no discernible IP) is challenging. In such situations, the IP is absent, and therefore the criterion method cannot be used. We have therefore examined the criterion validity of this approach in runners with a discernible IP and this could be a limitation. In addition, we have examined the validity of this approach in rearfoot striking runners and as

235 236 such, the outcomes from this study do not apply during forefoot running or to other populations e.g. other athletic groups or to other tasks e.g. walking. 237 238 239 240 241 242 243 244 To our knowledge this is the only published study to assess the validity of surrogate methods to determine IP indices, yet such methods are currently being used in the literature (Goss and Gross, 2013; Lieberman et al., 2010; Samaan et al., 2014). Good agreement of the HiF and TPS methods with the criterion method indicate both methods are likely to be valid surrogate approaches to estimate vgrf impact loading characteristics during rearfoot striking running. This, however, will be dependent upon the population studied. The smaller LOA and bias associated with the HiF method indicate that it should be used in preference to the TPS method when it is available. 245 Acknowledgements 246 Thank you to Dr. Michael Cole for proof reading the manuscript. 247 248 249 Conflicts of interest statement There are no known conflicts of interest. 250 251 252 253 254 255 References 256 257 258 259 260 Bland, J.M., Altman, D.G., 2010. Statistical methods for assessing agreement between two methods of clinical measurement. Int. J. Nurs. Stud. 47, 931936. Goss, D.L., Gross, M.T., 2013. A comparison of negative joint work and vertical ground reaction force loading rates in chi runners and rearfootstriking runner. J. Orthop. Sports Phys. Ther. 43, 685692.

261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 Heiderscheit, B.C., Chumanov, E.S., Michalski, M.P., Wille, C.M., Ryan, M.B., 2011. Effects of step rate manipulation on joint mechanics during running. Med. Sci. Sports Exerc. 43, 296302. Lieberman, D.E., Venkadesan, M., Werbel, W.A., Daoud, A.I., D Andrea, S., Davis, I.S., Mang Eni, R.O., Pitsiladis, Y., 2010. Foot strike patterns and collision forces in habitually barefoot versus shod runners. Nature 463, 531535. Milner, C.E., Ferber, R., Pollard, C.D., Hamill, J., Davis, I.S., 2006. Biomechanical factors associated with tibial stress fracture in female runners. Med. Sci. Sports Exerc. 38, 323. Munro, C.F., Miller, D.I., Fuglevand, A.J., 1987. Ground reaction forces in running: a reexamination. J. Biomech. 20, 147155. Nigg, B.M., Cole, G.K., Bruggemann, G.P., 1995. Impact Forces during Heel Toe Running. J. Appl. Biomech. 11, 407432. Noehren, B., Wilson, H., Miller, C., Lattermann, C., 2013. Longterm gait deviations in anterior cruciate ligamentreconstructed females. Med. Sci. Sports Exerc. 45, 13401347. Samaan, C.D., Rainbow, M.J., Davis, I.S., 2014. Reduction in ground reaction force variables with instructed barefoot running. J. Sport Health Sci. 3, 143151. Shorten, M., Mientjes, M.I.V., 2011. The heel impact force peak during running is neither heel nor impact and does not quantify shoe cushioning effects. Footwear Sci. 3, 4158. Willy, R., Pohl, M.B., Davis, I.S., 2008. Calculation of Vertical Load Rates in the Absence of Vertical Impact Peaks, Proceedings Of The North American Congress Of Biomechanics, Ann Arbor, MI, USA. Zadpoor, A.A., Nikooyan, A.A., 2011. The relationship between lowerextremity stress fractures and the ground reaction force: A systematic review. Clin. Biomech. 26, 2328. 285 286 287 288 289 290 Figure captions 291 292 293 Figure 1: Example plots of the vgrf and their respective high (HiF) and low frequency (LoF) components for a rearfoot striker when running at 3.3 m.s 1 on an instrumented treadmill. The figure highlights the three possible vgrf signal profiles: (A) an IP is easily

294 295 296 identifiable; (B) an IP is not discernible and (C) where an IP does not exist. Note that in all cases a peak in the HiF signal still exists and is easily identifiable, but occurs earlier than the vgrf IP. 297 298 299 Figure 2: BlandAltman plots for the right leg to assess agreement between the criterion measure and the HiF and TPS surrogate methods for the IP, AVLR and IVLR, respectively. 300 301 302

303 304

305 306 307 308 309 310 311 312 313 314 315 316 317 Table 1: Mean (SD) participant demographics for the IP group and the NO IP group. IP grou p (n = 42) NO IP grou p (n=8 ) Mea n 21.6 24.4 BMI = body mass index. Meth od Crite rion HiF TPS Age (yrs) 95% CI 20.9 22.3 20.7 28.3 Mea n Running volume (km/week) 58.5 57.7 95% CI 44.3 72.6 31.5 83.8 Mea n BMI Height Mass (kg/m 2 ) (m) (kg) 22.5 23.5 95% CI 21.6 23.4 21.7 25.3 Mea n 173. 2 176. 1 95% CI 170.3 176.1 163.8 188.3 Mea n 68 72.9 95% CI 64.0 72.0 64.0 81.7 Male:Fe male 24:18 Table 2: Mean, standard deviation (SD), BlandAltman bias and BlandAltman limits of agreement (LOA) for the IP, AVLR and IVLR for the right leg when assessed using the criterion, HiF and TPS methods, respectively. Me an (B W) 1.6 5 1.6 1 1.5 8 SD (B W) Impact peak AVLR Peak IVLR Bia LOA Me Bia LOA Me Bia SD s (BW)^ an s (BW. s 1 SD )^ an s (B (B (B (B W) W. W. (B (B (B Lo Up s s ^ 1 1 W. Lo Up s W. W.s s ) ) 1 )^ 1 1 W. s wer per wer per ) ) 1 )^ 0.2 4 0.2 0.0 0.0 0.0 4 4 6 1 0.2 6 0.0 7 0.2 1 0.0 7 61. 32 57. 71 57. 62 13. 31 13. 3.6 6.5 0.6 64 1 8 4 14. 51 3.7 0 10. 28 ^compared to criterion in BlandAltman analyses; LOA = limits of agreement. 2.8 9 96. 25 97. 05 94. 99 0.8 0 1.2 6 2:6 LOA (BW. s 1 )^ Lo wer Up per 17. 07 17. 4.4 6.0 16 7 7 18. 43 7.4 7 4.9 5