A public dataset of running biomechanics and the effects of running speed on lower extremity kinematics and kinetics Peer. JIntroduction. Long distance running has become a very popular form of physical activity among individuals pursuing a healthy lifestyle Stamatakis Chaudhury, 2. Good Game Farmer there. The health benefits of regular running are well known, however worrisome rates of running related injuries have been reported and have associated burdens and economic costs Hespanhol Jr et al., 2. Running biomechanics has been claimed to be associated with both running injury etiology Hreljac, 2. Moore, 2. 01. 6. Impact forces, foot pronation and shoes have all been linked to injuries although the literature is inconclusive about their role in the risk of running injuries Nigg et al., 2. Running foot strike patterns have also been the focus of great interest in the discussion pertaining to biomechanical injury factors which has resulted in an increased number of studies examining their effects on the rate of injuries and on running biomechanics Daoud et al., 2. Hall et al., 2. 01. Another factor that has been related to running injuries is the excessive pace or excessive training volume Nielsen et al., 2. However, only a handful of studies have focused on examining the effect of running speed on gait biomechanics Petersen et al., 2. Schache et al., 2. Download Basic Biomechanics Pdf Free Software' title='Download Basic Biomechanics Pdf Free Software' />ATOS Professional is a processreliable software solution that controls ATOS 3D scanners, produces precise 3D surface data, and offers complete inspection and. Issuu is a digital publishing platform that makes it simple to publish magazines, catalogs, newspapers, books, and more online. Easily share your publications and get. Www. airsoftsafetyfoundation. Sound Worship A Guide To Making Musical Choices In A Noisy World 20171029 UTC 151212 0000. This can be partly explained by the fact that running biomechanics has been examined either without controlling the gait speed or by obtaining the data for a single controlled gait speed. In addition, although these studies added new data, they typically used small sample sizes and limited sets of biomechanical variables and considered only one part of the gait cycle either the stance or swing phase, not to mention that the raw data from these studies are typically not freely available. Therefore, there is a need for studies that examine a larger set of runners across a range of gait speeds and that consider a larger set of biomechanical variables e. Although a study including these features would greatly contribute to advancing knowledge about the effect of gait speed, some challenges are likely to be encountered. The complex, multivariate nature of biomechanics data challenges traditional data analysis methods and, therefore, limits the ability of clinical gait researchers to interpret these results and apply this knowledge to intervention procedures. To overcome these challenges and encourage the development of innovative tools that can address the nature of gait biomechanics data, data sharing has been advocated Ferber et al., 2. Unfortunately, there are few publicly available datasets in the human movement science area see, for example, Moore, Hnat Van den Bogert, 2. Santos Duarte, 2. In fact, to our knowledge, there is no running biomechanics data sets with varying gait speeds available to the public. Therefore, a public data set of raw running biomechanics data would address this limitation and would welcome international research groups to use this data set to provide further insights about the related changes in biomechanics under varying running speed conditions. Therefore, the purposes of this study were 1 to present the set of raw and processed data on running biomechanics made available at Figshare DOI 1. Materials and Methods. This study aimed to examine the effect of running speed on selected gait biomechanics variables and to make the resulting dataset available in a public repository. The study was conducted at the Laboratory of Biomechanics and Motor Control BMClab http demotu. Federal University of ABC UFABC. The data collection was performed by experienced physiotherapist researchers. A pilot study with five subjects was conducted prior to the beginning the principal study. This study was approved by the local ethics committee of the UFABC CAAE 5. The data collection was designed to record the following measurements, which are described in detail later three dimensional 3. D kinematics of the two lower limbs and pelvis, ground reaction forces GRF during running on a treadmill at various speeds, and the strength and flexibility of selected muscle groups and joints. Participants. The study analyzed a convenience sample of 2. BMClab Internet home page http demotu. The inclusion criteria included being a regular runner with a weekly mileage greater than 2. The exclusion criteria were the presence of any neurological or musculoskeletal disorder that compromises its locomotion or the use of any assistive devices. The data related to demographics, running training characteristics, previous injuries, and other relevant information were made available in the public dataset see also the Table S1. Equipment. The running kinematics were collected via a 3. D motion capture system with 1. Mb of resolution and the Cortex 6. Raptor 4, Motion Analysis, Santa Rosa, CA, USA. The GRF data were collected via an instrumented, dual belt treadmill FIT, Bertec, Columbus, OH, USA. The cameras were distributed around the laboratory such that they aimed at the instrumented treadmills motion capture volume Fig. The cameras were mounted in a metallic truss setup structure with a length of 1. Global Quality Risk Management Manual. This structure allowed positioning some cameras with varying elevations however, most were placed atop the truss setup to optimize capturing the markers during the running trials Fig. Hopper &Amp; Sons Manual Roll Bender. The instrumented treadmill was mounted over a pit, with the treadmill surface at the same level as the laboratory floor Fig. Figure 1 Overview of the Laboratory of Biomechanics and Motor Control. Expanded view of the Laboratory of Biomechanics and Motor Control BMClab, showing 1. The Cortex 6. 0 software Motion Analysis, Santa Rosa, CA, USA was used to 1 calibrate the motion capture volume 2 capture and identify the reflective markers and 3 prepare the data and export it to the c. To provide an unbiased, raw dataset having marker trajectories and force signals, no further processing e. The motion capture volume consisted of an area 3. The system was deemed properly calibrated only if the length of the calibration wand, which was measured by the capture system, was within 0. The rates of acquisition of the kinematics and kinetics data were set at 1. Hz and 3. 00 Hz, respectively. The laboratory coordinate system used for the study was the same as that proposed by the International Society of Biomechanics Wu Cavanagh, 1. Fig. 1, contained the following X axis in the direction of gait progression and positive pointing forward. Y axis in the vertical direction and positive pointing upward. Z axis in the medial lateral direction and positive pointing to the right. To record the strength and flexibility measures of selected muscle groups and joints, a hand held dynamometer HHD range 01,3. N accuracy 1 resolution 1 N Nicholas MMT, Lafayette Instruments, Lafayette, IN, USA and a magnetic angle locator Model 7. Johnson Level Tool Mfg. Co., Inc., Mequon, WI, USA were used, respectively. Protocol. The data collection protocol involved the following procedures 1. Interview. Upon arrival, the participant was introduced to the laboratory and given a brief explanation of the experimental procedures. Then, the participant was asked to provide written informed consent and undergo a brief interview regarding eligibility criteria, demographic data, and running habits. Preliminary measurements.