European Journal of Applied Physiology (2019) 119:85–90 https://doi.org/10.1007/s00421-018-4001-1 ORIGINAL ARTICLE Spatiotemporal parameters in sprinters with unilateral and bilateral transfemoral amputations and functional impairments Hiroaki Hobara1 · Satoru Hashizume1 · Yoshiyuki Kobayashi1 · Yuta Namiki1 · Ralf Müller2 · Johannes Funken2 · Wolfgang Potthast2 Received: 11 April 2018 / Accepted: 25 September 2018 / Published online: 8 October 2018 © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract Purpose Although sprinters with unilateral (UTF) and bilateral transfemoral (BTF) amputations and functional impairments (FIs) without amputation were allocated into different classifications because of the recent revision of the International Paralympic Committee Athletics Rules and Regulations, it is unclear whether running mechanics differ among the three groups. The aim of this study was to investigate the differences in the spatiotemporal parameters of the three groups during 100-m sprint in official competitions. Methods Using publicly available Internet broadcasts, we analyzed 11 elite-level sprinters with UTF amputation, 4 sprinters with BTF amputation, and 5 sprinters with FI without amputation. The best personal times for nearly all individuals were included. For each sprinter’s race, the average speed, step frequency, and step length were calculated using the number of steps in conjunction with the official race time. Results Although there were no significant differences in the average speed among the UTF, BTF, and FI groups (7.95 ± 0.22, 7.90 ± 0.42, and 7.93 ± 0.14 m/s, respectively, p = 0.87), those with BTF amputation showed significantly lower step frequency (UTF: 4.20 ± 0.20 Hz, BTF: 3.71 ± 0.32 Hz, FI: 4.20 ± 0.10 Hz, p < 0.05) and longer step length (UTF: 1.90 ± 0.08 m, BTF: 2.14 ± 0.02 m, FI: 1.89 ± 0.06 m, p < 0.05) than the other two groups. Conclusion These results suggest that the step characteristics during sprinting are not the same among sprinters with UTF amputation, BTF amputations, or FI without amputations. Keywords Running-specific prostheses · Paralympics · Athletics · Classification · Amputees Abbreviations S100 Average speed BTF Bilateral transfemoral trace Official race times ES Effect size UTF Unilateral transfemoral FI Functional impairments fstep Average step frequency Lstep Average step length Introduction Lfratio Step length/step frequency ratio Nstep Number of steps Paralympic classifications for track events in athletics are gen- erally based on sex, level of amputation, and/or similar levels Communicated by Jean-René Lacour. of activity limitations due to disabilities. For example, prior to 2018, athletes with single unilateral transfemoral (UTF) ampu- * Hiroaki Hobara tation and those with all other impairments that were thought [email protected] to be comparable to athletes with UTF amputation were clas- 1 Human Informatics Research Institute, National Institute sified into the T42 class [International Paralympic Commit- of Advanced Industrial Science and Technology (AIST), tee (IPC) Athletics Rules and Regulations 2016–2017], which AIST Tokyo Waterfront 3F, 2-3-26, Aomi, Koto-ku, also included athletes with limb deficiency, leg length differ- Tokyo 135-0064, Japan ence, impaired muscle power, and impaired passive range 2 Institute of Biomechanics and Orthopaedics, German of movement in the lower limbs (without leg amputation). Sport University Cologne, Am Sportpark Müngersdorf 6, Consequently, the previous T42 class included athletes with 50933 Cologne, Germany Vol.:(0123456789)1 3 86 European Journal of Applied Physiology (2019) 119:85–90 UTF amputation, bilateral transfemoral (BTF) amputation, FIs without amputations from publicly available Internet and functional impairments (FIs) without leg amputations. broadcasts (YouTube; https ://www.youtu be.com/). These Although each population is now allocated into a different races included several Paralympic Games, the IPC World classification because of the recent revision of the IPC Athlet- Para Athletics Championships, World Para Athletics Junior ics Rules and Regulations (as of January 1, 2018; T42 for FI, Championships, and other international-level competitions T61 for BTF, and T63 for UTF), it is unclear whether run- from 2008 to 2017. Data were collected only from the finals ning mechanics differ among the three groups. An increased or semifinals in each competition with a sampling rate of understanding of running mechanics in these populations will 60 Hz. To ensure homogeneity of data in all classes, we provide a basis for better evaluating assistive technology that only included sprinters who satisfied the A-qualification accompanies training methods and to develop evidence-based standards of previous men’s T42 (13.40 s). Each perfor- classification system in Para sport. mance was the personal best time for a 100-m sprint for Theoretically, the average speed during a 100-m sprint nearly each individual (Table 1). On average, relative differ- (S100) is the product of the average step frequency (fstep) and ences between analyzed race times and personal best times average step length (Lstep). Although both parameters are were 100.74%, 100.61%, or 100.51% for sprinters with inversely correlated, an increase in one factor will result in UTF amputation, BTF amputation, or FI without amputa- an improvement in sprint speed, as long as the other fac- tion, respectively. Individual athletes were excluded from tor does not undergo a proportionately similar or larger the analysis if the athlete did not complete the race or if decrease. According to previous studies, spatiotemporal the athlete’s body was not visible throughout the race. In patterns during walking vary with amputation levels and our current dataset, sprinters with BTF amputation did not FIs (Eke-Okoro 1999; Javis et al. 2017). The Lfratio, which use prosthetic knee joints for either leg (i.e., no-knee condi- is the ratio of Lstep–fstep, is a simple and quantitative index tions, in which a straight pylon attaches to the prosthetic with which one can assess a deviation from a particular gait socket and foot components). A similar approach of ana- pattern (Sekiya and Nagasaki 1998). Furthermore, previous lyzing publicly available data from sports competitions for studies have demonstrated that Lfratio is useful for describing research purposes has been performed by Salo et al. (2011) pathological gait (Eko-Okoro 1999; Rota et al. 2011; How- for sprint running using 52 able-bodied sprinters; by Hobara ard et al. 2013), predicting falls in the elderly (Barak et al. et al. (2015) for prosthetic sprinting using 36 able-bodied, 25 2006; Egerton et al. 2011; Callisaya et al. 2012), and better unilateral amputee, and 17 bilateral amputee sprinters; and understanding the neurocontrol of gait (Egerton et al. 2011; by Senefeld et al. (2016) for the finishing times of the top Rota et al. 2011). However, little is known about these spa- 10 men and women world record swimming performances tiotemporal parameters in sprinters with UTF amputation, (freestyle, backstroke, breaststroke, and butterfly) from 1986 BTF amputation, or FI without amputation. to 2011 in swimmers between 25 and 89 years old. The aim of this study was to investigate the spatiotem- poral parameters in sprinters with UTF amputation, BTF Data analyses amputation, or FI without amputation during a 100-m sprint. A recent study demonstrated that athletes with BTF amputa- Based on previous studies (Hobara et al. 2015, 2016), we tion exhibited lower fstep but longer Lstep than athletes with determined the average speed (S100) of each individual by UTF during 200-m sprint (Hobara et al. 2018). Further, knee dividing the race distance (100 m) with the official race joint function is crucial for the stance and swing phase dur- times (trace), which were obtained from each competition’s ing sprinting (Kuitunen et al. 2002; Nagahara et al. 2017), official website. Thus, indicating that loss of unilateral knee power would induce S100 = 100∕trace. comparable activity limitation between sprinters with UTF (1) f amputation and those with FI without amputation. There- In the present study, we calculated the average step as fore, we hypothesized that athletes with BTF amputation fstep = Nstep∕trace, (2) would exhibit lower f but longer L than athletes with step step where N is the number of steps, which was manually UTF or FI during 100-m sprint. step counted by the authors. If we could not count the number of steps, we excluded the data from our analyses. The last step Methods before the finish line was considered to be the last step. If an athlete’s foot was on the finish line, we considered it as S f Data collection a step (Hobara et al. 2015). Since 100 is the product of step and average Lstep, we calculated Lstep by We analyzed 11 elite-level sprinters with UTF amputa- Lstep = S100∕fstep. (3) tion, 4 sprinters with BTF amputation, and 5 sprinters with 1 3 European Journal of Applied Physiology (2019) 119:85–90 87 Table 1 Spatiotemporal parameters of athletes with unilateral transfemoral (UTF) amputations, bilateral transfemoral (BTF) amputations, and functional impairment (FI) without amputation during a 100-m sprint Athletes Group Competitions and years trace (s) S100 (m/s) fstep (Hz) Lstep (m) %PB A1 UTF IPC Athletics World Championships (final) 2015 12.13 8.24 4.45 1.85 100.00 A2 UTF IPC European Championship (final) 2016 12.27 8.15 3.99 2.04 100.00 A3 UTF IPC Athletics World Championships (semifinal)