This study is sponsored by the National Natural Science Foundation of China (81301600), K. C. Wong Magna Fund in Ningbo University, National Social Science Foundation of China (16BTY085), the Zhejiang Social Science Program "Zhi Jiang youth project" (16ZJQN021YB), Loctek Ergonomic Technology Corp, and Anta Sports Products Limited.

This study has been approved by the Human Ethics Committee of Ningbo University (ARGH20150356). All subjects gave their informed consent for inclusion in the study, and they were informed of the goal, requirements, and experimental procedures of the study.
1. Gait Laboratory Preparation
<ol>
	<li>Switch off any incandescent lights and leave a reasonable fluorescent lighting level in the laboratory. Remove all markers and unwanted objects of reflection that may be misinterpreted as passive retro-reflective markers from the capture volume.</li>
	<li>Plug the appropriate dongle into the parallel port of the computer. Turn on the motion-capture cameras, proprietary tracking software, force platform amplifiers, and external analog-to-digital converter (ADC).
	<ol>
		<li>Allow time for the 8 cameras to initialize. Click the &#34;Local System&#34; node on the &#34;System&#34; tab of the &#34;Resources&#34; pane. In the &#34;Properties&#34; pane of the &#34;Local System&#34; node, type &#34;100&#34; into the &#34;Requested Frame Rate&#34; property in the &#34;System&#34; section to set sample rate at 100 Hz.</li>
	</ol>
	</li>
	<li>Select &#34;Camera&#34; from the view list in the &#34;View&#34; pane. Place the T-frame, which consists of 5 markers located a fixed distance from each other, on the force platform.
	<ol>
		<li>In the &#34;System Resources&#34; tree, expand the &#34;Cameras&#34; node and press and hold the CTRL key while clicking each camera listed in the node. In the &#34;Properties&#34; pane of the &#34;Cameras&#34; node, move the &#34;Strobe Intensity&#34; bar in the &#34;Settings&#34; section to the left or right for each camera to ensure that data from each camera is completely, clearly, and steadily visible in the &#34;View&#34; pane.</li>
	</ol>
	</li>
	<li>Click the &#34;System Preparation&#34; button in the &#34;Tool&#34; pane. Click the &#34;Start&#34; button in the &#34;Calibrate Cameras&#34; section and thenphysically wave the calibration wand (T-frame) in the capture volume in a vertical figure eight whilst moving around the area intended for the capture of 3D data. Stop waving when the blue status lights on the front of the cameras stop flashing.</li>
	<li>In the &#34;Cameras Calibration Feedback&#34; section in the &#34;Tool&#34; pane, monitor the progress bar until the camera calibration process is complete. Review the &#34;Image Error&#34; data; the acceptable image error of each camera should be less than 0.3.</li>
	<li>Place the T-frame on the floor, with the central marker on the top-left corner of the force platform (60 cm &#215; 90 cm) and the axes of the frame along the edges of the force platform. Ensure that the long axis of the frame points in the travel direction (anterior direction).</li>
	<li>Select &#34;3D Perspective&#34; from the view list in the &#34;View&#34; pane. In the &#34;Set Volume Origin&#34; section, click the start button and click the &#34;Set Origin&#34; button to set the origin of the capture volume.</li>
	<li>Ask a subject to step onto the force platform. Verify that the direction of the ground reaction vector displayed in the view pane is upward and that the magnitude of the vertical force component is equal to the body mass x 9.81. Ask the subject to walk away from the force platform.</li>
	<li>In the &#34;System Resources&#34; tree, right-click on the &#34;Force Platform&#34; node and select &#34;Zero Level&#34; from the &#34;Context&#34; menu to calibrate the force platform. Click the &#34;Connectivity&#34; node on the &#34;System&#34; tab in the &#34;Resources&#34; pane. In the &#34;Properties&#34; pane of the &#34;Connectivity&#34; node, type &#34;1,000&#34; into the &#34;Requested Frame Rate&#34; property in the &#34;Settings&#34; section to set the sample rate at 1,000 Hz.</li>
	<li>Prepare 16 passive retro-reflective markers (diameter: 14 mm) by pre-attaching them individually to one side of double-sided adhesive tape.</li>
</ol>
2. Subject Preparation
<ol>
	<li>Organize the results of the survey about high-heel shoe-wearing experience, including frequency, duration, heel types, and heel heights, which should be given to each volunteer. 
	NOTE: Questions in the survey: (i) How often do you wear your high-heeled shoes? (ii) How many h/min do you wear your high-heeled shoes each time? (iii) What kind of high-heeled shoes do you usually wear? Wedge heel or stiletto heel? (iv) How high is the shoe that you usually wear? Here, 36 young females volunteered to participate in this test, but 14 of them were excluded for assorted reasons: feeling uncomfortable with the experimental shoe (4), hallux valgus (3), only having wedge-heel experience (3), abnormal gait in the experimental environment (2), and absence on the testing day (2).</li>
	<li>Obtain written informed consent from subject who fulfill the inclusion criteria. 
	NOTE: The inclusion criteria are as follows: no musculoskeletal disorders that might affect normal jogging and running gait; feeling comfortable with the experimental shoe offered; right-foot dominant; and size 37 (EUR) EW (age: 24.2 &#177; 1.2 years; height: 160 &#177; 2.2 cm; mass: 51.6 &#177; 2.6 kg) wear shoes with narrow heels 3-6 cm-high for a minimum of three days per week (6 h per day) for at least two years, while IEW (age: 23.7 &#177; 1.3 years; height: 162.3 &#177; 2.3 cm; mass: 52.6 &#177; 4.5 kg) wear high-heeled shoes less than twice per month.</li>
	<li>Ask the subjects to change into tight-fitting pants and a t-shirt.</li>
	<li>Measure subjects&#39; standing height (mm) and body mass (kg). Measure the leg length (i.e., the distance between the superior iliac spine and the ankle internal condyle, in mm), knee width (i.e., the distance between the medial and lateral knee condyle, in mm) and ankle width (i.e., the distance between the medial and lateral ankle condyle, in mm) using measuring calipers.</li>
	<li>Prepare skin areas of anatomical bony landmarks for marker placement.
	<ol>
		<li>Shave body hair as appropriate and use alcohol wipes to remove excess sweat and moisturizer. 
		NOTE: The marker locations include: anterior-superior iliac spine (LASI/RASI), posterior-superior iliac spine (LPSI/RPSI), lateral mid-thigh (LTHI/RTHI), lateral knee condyle (LKNE/RKNE), lateral mid-shank (LTIB/RTIB), lateral malleolus (LANK/RANK), second metatarsal head (LTOE/RTOE), and calcaneus (LHEE/RHEE), where the L and R prefixes indicate the left and ride legs, respectively.</li>
	</ol>
	</li>
	<li>Palpate to identify anatomical landmark. Circle each landmark on the skin using a marking pen. Attach the 16 passive retro-reflective markers on the landmarks of both sides of the lower limbs with double-sided adhesive tape.</li>
	<li>Ask the subjects to change into the experimental shoe (heel height: 4.5 cm) and then walk, jog, and run freely along the runway until they are physiologically and psychologically comfortable with the cameras and markers on their lower limbs (i.e., no influence on the participants) and they feel like they are walking, jogging, and running naturally.</li>
	<li>Ask the subjects to practice jogging along the runway at a comfortable low speed until they are able to jog steadily. Instruct the subjects to perform some progressive training (e.g., making an effort to jog at a progressively increasing speed on a treadmill within a safe and comfortable range).</li>
	<li>Ask them to practice running on the ground along the runway at a comfortable high speed until they are able to run steadily at this speed.</li>
	<li>Instruct the subjects to try to start jogging/running from different starting lines within the starting area several times to find an appropriate starting position, ensuring that the right foot naturally strikes and completely contacts the force platform when passing by.</li>
</ol>
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/55714/55714fig1.jpg" /> 
Figure 1: Experimental protocol. 8 infrared cameras capture lower-limb motion while the subject jogs and runs along the runway. The right foot naturally strikes and completely contacts the force platform when passing by. Kinematic and kinetic data were collected synchronically. <a href="//cloudfront-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55714/55714fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
3. Static Calibration
<ol>
	<li>Click the &#34;New Database&#34; button in the toolbar to create a new database. Click the &#34;Data Management&#34; button in the toolbar to open the &#34;Data Management&#34; pane. In the &#34;Data Management&#34; pane, click the &#34;New Patient Classification,&#34; &#34;New Patient,&#34; and &#34;New Session&#34; buttons, in order. Return to the &#34;Resources&#34; pane, click the &#34;Create a new subject&#34; button to create a new subject, and enter the values for all anthropometric measurements (e.g., height, weight, leg length, knee width, and ankle width) in the &#34;Properties&#34; pane for the newly created subject.</li>
	<li>Click the &#34;Go Live&#34; button in the &#34;Resources pane.&#34; Click the &#34;Split horizontally&#34; button in the &#34;View&#34; pane and select &#34;Graph&#34; in the view list in the new &#34;View&#34; pane. Select &#34;Trajectory Count&#34; in the &#34;Model Output&#34; pulldown list.
	<ol>
		<li>Confirm that the count of markers in the &#34;Graph&#34; view pane is 16 and that the same number of markers is visible in the &#34;3D Perspective&#34; view pane, meaning that no markers on the lower limb have failed to be captured.</li>
	</ol>
	</li>
	<li>Click the &#34;Subject Preparation&#34; button in the &#34;Tool&#34; pane.</li>
	<li>Ask the subject to stand in a stationary neutral pose in the center of the capture volume to capture the static data.
	<ol>
		<li>Click the &#34;Start&#34; button in the subject capture section, capture approximate 150 frames, and click the &#34;Stop&#34; button. 
		NOTE: The &#34;Start&#34; button switches to &#34;Stop&#34; automatically after clicking it.</li>
	</ol>
	</li>
	<li>Click the &#34;Reconstruct&#34; button in the toolbar to display the captured markers. Click the &#34;Label&#34; button in the &#34;Tool&#34; pane and manually assign the labels (16 in total) listed in the &#34;Manual Labeling&#34; section to the corresponding markers in the &#34;3D Perspective&#34; view pane. Press the &#34;Esc&#34; key on the keyboard to exit.</li>
	<li>Select &#34;Static&#34; in the &#34;Pipeline&#34; pulldown list in the &#34;Subject Calibration&#34; section. Check the &#34;Left Foot&#34; and &#34;Right Foot&#34; options in the &#34;Static Settings&#34; pane. Click the &#34;Start&#34; button in the &#34;Subject Calibration&#34; section.</li>
</ol>
4. Dynamic Trials
<ol>
	<li>Ask the subject to stand at the appropriate starting position.</li>
	<li>Click the &#34;Go Live&#34; button in the &#34;Resources&#34; pane. Click the &#34;Capture&#34; button in the &#34;Tool&#34; pane. Edit the &#34;Trial Name&#34; in the &#34;Next Trial Setup&#34; section.</li>
	<li>Click the &#34;Start&#34; button in the &#34;Capture&#34; section to begin capturing and then immediately give the subject the oral instruction to &#34;Go jogging/Go running.&#34; Ensure that the right foot naturally strikes and completely contacts the force platform when passing by ( Figure 1).
	<ol>
		<li>For jogging trials, ask the subjects to jog at the comfortable low speed that they were familiar with during preparation; for running trials, ask the subjects to run at the comfortable high speed that they had been familiar with during preparation. Allow for a 2-min rest between two trials.</li>
		<li>Capture at least 3 complete successive steps, including the step on the force platform. 
		NOTE: Jogging and running trials are performed randomly. For each speed, ask the subjects to repeat 5 trials. Cancel the capture in the event of a marker moving/falling or if abnormal gait occurs. In the event of markers moving/falling, re-attach to the predetermined skin mark.</li>
	</ol>
	</li>
</ol>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/55714/55714fig2.jpg" /> 
Figure 2: User interface for dynamic data collection. <a href="//cloudfront-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55714/55714fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<ol start="4">
	<li>Click the &#34;Stop&#34; button in the &#34;Capture&#34; section after the subject jogs/runs to the end of the runway. See Figure 2. 
	NOTE: The &#34;Start&#34; button in the &#34;Capture&#34; section switches to &#34;Stop&#34; automatically after clicking it.</li>
</ol>
5. Post-processing using Proprietary Tracking Software
<ol>
	<li>Click the &#34;Data Management&#34; button in the toolbar. In the &#34;Data Management&#34; pane, double-click the trial name. Click the &#34;Reconstruct&#34; and &#34;Label&#34; buttons in the toolbar to reconstruct the 3D dynamic model and to obtain the filmed data.</li>
	<li>On the time bar, move the left-range indicator (blue triangle) on the timeline to the frame at which the right foot strikes the force platform. Select this frame according to the instant when the vertical force vector in the view pane arises.
	<ol>
		<li>Move the right-range indicator (blue triangle) on the timeline to the frame at which the next heel-strike event of the right foot occurs. 
		NOTE: The selection of this frame depends on the elaborative subjective estimate of the researchers according to the instant when there is no superior-inferior displacement of the right heel marker.</li>
	</ol>
	</li>
	<li>Right-click on the time bar and select &#34;Zoom to Region-of-Interest&#34; from the &#34;Context&#34; menu to define the desired frames.</li>
	<li>Click the &#34;Label&#34; button in the &#34;Tool&#34; pane. In the &#34;Gap Filling&#34; section, click on the markers whose trajectories contain gaps listed in the &#34;Trajectory&#34; column and then click the &#34;Fill&#34; button of the &#34;Spline Fill&#34; tool. 
	NOTE: The number of gaps are listed in the &#34;#Gaps&#34; column. Clicking on the &#34;Fill&#34; button of the &#34;Spline Fill&#34; tool fills one gap. The &#34;Spline Fill&#34; method can generally be used for gap instances less than or equal to 60 frames.</li>
	<li>Click the &#34;Pipeline&#34; button in the &#34;Tool&#34; pane. Select &#34;Dynamic&#34; from the &#34;Current Pipeline&#34; list. Move the indicator (blue slider) along the timeline to the last frame. Click the &#34;Run&#34; button to start the pipeline process and export dynamic trials in.csv format for post-processing in the data analysis software.</li>
</ol>
6. Data Analysis
<ol>
	<li>Low-pass filter the kinematic and kinetic data using 4th-order Butterworth filters with cut-off frequencies at 10 Hz and 25 Hz, respectively13 (see the Table of Materials).</li>
	<li>Divide the anterior-superior displacement of the marker on the right anterior superior iliac spine by the corresponding time to calculate the jogging/running speed.
	<ol>
		<li>Define the anterior-posterior displacement of the marker on right heel between the successive heel-strike events as the stride length. Define the reciprocal of the duration of the gait cycle as the stride frequency.</li>
	</ol>
	</li>
	<li>Define the difference between the peak angle and valley angle during the stance phase as the joint range of motion (ROM).</li>
	<li>Calculate the vertical average loading rate by defining the slope of the vertical GRF-time curve from 20-80% of the stance time from initial contact to impact force14. 
	NOTE: Define the initial contact as the instant when the vertical GRF consistently measured more than 0 N.</li>
	<li>Normalize the vertical GRF to bodyweight (BW%).</li>
	<li>First average the 5 trials from each subject and then average these results for all subjects. 
	NOTE: The parameters include jogging and running speed, stride length, stride frequency, joint (i.e., ankle, knee and hip) 3D (ROM) and peak angle during stance phase, angle at heel-strike in the sagittal plane, impact force (Fi), peak force (Fp), and vertical average loading rate (VALR).</li>
	<li>Transfer the data to a statistical software for statistical analysis.</li>
</ol>
7. Statistical Analysis
<ol>
	<li>Perform two separate independent samples t-tests to assess the effects of wearing experience. Perform two separate paired-samples t-tests to assess the effects of running speed on lower-limb kinematics and GRF. Consider statistical results as significant if p &#60;0.05.</li>
</ol>

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B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Walking+on+high+heels+changes+muscle+activity+and+the+dynamics+of+human+walking+significantly.">Walking on high heels changes muscle activity and the dynamics of human walking significantly.</a> J Appl Biomech. 28 (1), 20-28 (2012).</li><li>Stefanyshyn, D. J., Nigg, B. M., Fisher, V., O'Flynn, B., Liu, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+influence+of+high+heeled+shoes+on+kinematics,+kinetics,+and+muscle+EMG+of+normal+female+gait.">The influence of high heeled shoes on kinematics, kinetics, and muscle EMG of normal female gait.</a> J Appl Biomech. 16 (3), 309-319 (2000).</li><li>Kerrigan, D. C., Lelas, J. L., Karvosky, M. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Women's+shoes+and+knee+osteoarthritis.">Women's shoes and knee osteoarthritis.</a> Lancet. 357 (9262), 1097-1098 (2001).</li><li>Kerrigan, D. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Moderate-heeled+shoes+and+knee+joint+torques+relevant+to+the+development+and+progression+of+knee+osteoarthritis.">Moderate-heeled shoes and knee joint torques relevant to the development and progression of knee osteoarthritis.</a> Arch Phys Med Rehabil. 86 (5), 871-875 (2005).</li><li>Beynnon, B. D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+strain+behavior+of+the+anterior+cruciate+ligament+during+squatting+and+active+flexion-extension+a+comparison+of+an+open+and+a+closed+kinetic+chain+exercise.">The strain behavior of the anterior cruciate ligament during squatting and active flexion-extension a comparison of an open and a closed kinetic chain exercise.</a> Am J Sports. 25 (6), 823-829 (1997).</li><li>Fleming, B. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+gastrocnemius+muscle+is+an+antagonist+of+the+anterior+cruciate+ligament.">The gastrocnemius muscle is an antagonist of the anterior cruciate ligament.</a> J Orthop Res. 19 (6), 1178-1184 (2001).</li><li>Schipplein, O., Andriacchi, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Interaction+between+active+and+passive+knee+stabilizers+during+level+walking.">Interaction between active and passive knee stabilizers during level walking.</a> J Orthop Res. 9 (1), 113-119 (1991).</li><li>Baliunas, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Increased+knee+joint+loads+during+walking+are+present+in+subjects+with+knee+osteoarthritis.">Increased knee joint loads during walking are present in subjects with knee osteoarthritis.</a> Osteoarthr Cartil. 10 (7), 573-579 (2002).</li><li>Payne, C., Munteanu, S., Miller, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Position+of+the+subtalar+joint+axis+and+resistance+of+the+rearfoot+to+supination.">Position of the subtalar joint axis and resistance of the rearfoot to supination.</a> J Am Podiatr Med Assoc. 93 (2), 131-135 (2014).</li><li>Cheung, R. T., Rainbow, M. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Landing+pattern+and+vertical+loading+rates+during+first+attempt+of+barefoot+running+in+habitual+shod+runners.">Landing pattern and vertical loading rates during first attempt of barefoot running in habitual shod runners.</a> Hum Mov Sci. 34, 120-127 (2014).</li><li>Lieberman, D. E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Foot+strike+patterns+and+collision+forces+in+habitually+barefoot+versus+shod+runners.">Foot strike patterns and collision forces in habitually barefoot versus shod runners.</a> Nature. 463 (7280), 531-535 (2010).</li><li>Voloshin, A., Loy, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biomechanical+evaluation+and+management+of+the+shock+waves+resulting+from+the+high-heel+gait:+I-temporal+domain+study.">Biomechanical evaluation and management of the shock waves resulting from the high-heel gait: I-temporal domain study.</a> Gait Posture. 2 (2), 117-122 (1994).</li><li>Kerrigan, D. C., Todd, M. K., Riley, P. O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Knee+osteoarthritis+and+high-heeled+shoes.">Knee osteoarthritis and high-heeled shoes.</a> Lancet. 351 (9113), 1399-1401 (1998).</li><li>Gu, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Plantar+pressure+distribution+character+in+young+female+with+mild+hallux+valgus+wearing+high-heeled+shoes.">Plantar pressure distribution character in young female with mild hallux valgus wearing high-heeled shoes.</a> J Med Mech Biol. 14 (01), (2014).</li><li>Yu, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Development+of+a+finite+element+model+of+female+foot+for+high-heeled+shoe+design.">Development of a finite element model of female foot for high-heeled shoe design.</a> Clinical Biomechanics. 23, S31-S38 (2008).</li></ol>

The authors have nothing to disclose.

One defect of most studies that analyze high-heeled gait biomechanics is ignoring the possible importance of experience wearing high heels12. This study divided subjects into groups of regular and occasional wearers to explore the effects of high-heeled shoe wearing experience on lower-limb kinematics and GRF during moderate high-heeled jogging and running.
EW and IEW showed comparable jogging/running speeds. Compared with EW, IEW adopted a higher stride frequency and a...

High-heel design has always been one of the popular features of women&#39;s footwear. Forcing the ankle into a passive plantar-flexed state, high-heeled shoes considerably alter walking kinematics and kinetics. Despite reported adverse effects on the musculoskeletal system1, social and fashion customs encourage the continued use of high-heeled shoes2.
Optical tracking systems, currently used in the majority of gait-analysis laboratories for both clinical and research purposes, give accurate and reliable measurement of 3D lower-limb joint motions3. This technology provides a &#34;gold standard&#34; for gait analysis4. Consistent results based on the technique have revealed that higher heel heights lead to larger knee flexion and ankle inversion when compared with flat shoes5,6,7. GRF is another commonly used parameter in gait analysis. The shift of GRF toward the medial forefoot, reduced GRF during mid-stance, increased vertical GRF at heel-strike, and increased peak anterior-posterior GRF have also been observed in high-heeled walking1,6,7,8.
Previous studies referenced above use methods based mainly on level walking. In modern society, running for a bus, darting across a busy street, or dashing to catch the last train push more and more women to use higher speeds every now and then. There are limited studies concerning lower-limb biomechanics during high-heeled jogging and running. Gu et al. noted that the joint motion range of knee abduction-adduction and hip flexion-extension increased significantly as the heel height increased during jogging9. The limitation of this study is that they only recruited habitual high-heel wearers. The frequent use of high-heeled shoes can potentially induce structural adaptions in lower-limb muscles. Z&#246;llner et al. created a multiscale computational model revealing that muscle is able to gradually adjust to its new functional length due to the use of high heels after a chronic loss of sarcomeres in series10. Evidence also demonstrates that kinematic accommodations in gait caused by high-heeled shoes vary between experienced and inexperienced wearers11. Data collected from both experienced and inexperienced subjects may mask statistical results12. It is important to explore whether the biomechanical changes are similarly obvious in inexperienced and experienced users.
The purpose of this study was to investigate the differences in lower-limb kinematics and vertical GRF between experienced wearers (EW) and inexperienced wearers (IEW) during moderate high-heeled jogging and running. It was hypothesized that EW would show faster self-preferred jogging and running speeds, less joint motion, and larger vertical GRF during jogging and running.

<table><tbody><tr><td>Motion Tracking Cameras</td><td>Oxford Metrics Ltd., Oxford, UK</td><td>MX cameras</td><td>n= 8</td></tr><tr><td>Vicon Nexus&amp;nbsp;</td><td>Oxford Metrics Ltd., Oxford, UK</td><td>Version 1.4.116</td><td>Proprietary tracking software (PlugInGait template)</td></tr><tr><td>Dongle</td><td>Oxford Metrics Ltd., Oxford, UK</td><td>-</td><td>-</td></tr><tr><td>MX Ultranet HD</td><td>Oxford Metrics Ltd., Oxford, UK</td><td>-</td><td>-</td></tr><tr><td>Vicon Datastation ADC&amp;nbsp;</td><td>Oxford Metrics Ltd., Oxford, UK</td><td>-</td><td>External ADC</td></tr><tr><td>Passive Retro-reflective Marker</td><td>Oxford Metrics Ltd., Oxford, UK</td><td>-</td><td>n=16; Diametre=14 mm&amp;nbsp;</td></tr><tr><td>Force Platform Amplifier</td><td>Kistler, Switzerland</td><td>5165A</td><td>n=1</td></tr><tr><td>Force Platform</td><td>Kistler, Switzerland</td><td>9287C</td><td>n=1</td></tr><tr><td>T-Frame</td><td>Oxford Metrics Ltd., Oxford, UK</td><td>-</td><td>-</td></tr><tr><td>Double Adhesive Tape</td><td>Oxford Metrics Ltd., Oxford, UK</td><td>-</td><td>For fixing markers to skin</td></tr><tr><td>moderate high-heeled shoe</td><td>Daphne, Hong Kong</td><td>13085015</td><td>Heel height: 4.5cm; Size:37EURO</td></tr><tr><td>Microsoft Excel&amp;nbsp;</td><td>Microsoft Corporation, United States</td><td>Version 2010</td><td>For low pass filtering data and calculations; Add-in:Butterworth.xla</td></tr><tr><td>Origin&amp;nbsp;</td><td>OriginLab Corporation, United States</td><td>Version 9.0</td><td>Plot GRF-time curve</td></tr><tr><td>Stata&amp;nbsp;</td><td>Stata Corp, College station, TX</td><td>Version 12.0</td><td>Statistical analysis</td></tr></tbody></table>

using gold-standard gait analysis methods to assess experience effects on lower-limb mechanics during moderate high-heeled jogging and running

A limited number of studies have explored lower-limb biomechanics during high-heeled jogging and running, and most studies have failed to clarify the wearing experience of subjects. This protocol describes the differences in lower-limb kinematics and ground reaction force (GRF) between experienced wearers (EW) and inexperienced wearers (IEW) during moderate high-heeled jogging and running. A three-dimensional (3D) motion analysis system with a configured force platform was used to synchronously capture lower-limb joint movements and GRF. 36 young females volunteered to participate in this study and were asked about high-heeled shoe-wearing experience, including frequency, duration, heel types, and heel heights. Eleven who had the experience of 3 to 6 cm heels for a minimum of three days per week (6 h per day) for at least two years and eleven who wore high heels less than twice per month participated. Subjects performed jogging and running at comfortable low and high speeds, respectively, with the right foot completely stepping onto a force platform when passing by along a 10 m walkway. EW and IEW adopted different biomechanical adaptations while jogging and running. IEW exhibited a generally larger range of joint movement, while EW showed a dramatically larger loading rate of GRF during running. Hence, further studies on the lower-limb biomechanics of high-heeled gait should strictly control the wearing experience of the subjects.

All results are presented here as the mean &#177; standard deviation. The running speed was significantly greater than the jogging speed, regardless of wearing experience (EW: Jog vs. Run: 2.50 &#177; 0.14 vs. 3.05 &#177; 0.14, p = 0.010; IEW: Jog vs. Run: 2.24 &#177; 0.26 vs. 2.84 &#177; 0.29, p = 0.028; in m/s) (Table 1). No significant difference in the corresponding jogging/running speeds between EW and IEW was fou...

Watch this Scientific Journal Video about Using Gold-standard Gait Analysis Methods to Assess Experience Effects on Lower-limb Mechanics During Moderate High-heeled Jogging and Running at JoVE.com

Using Gold-standard Gait Analysis Methods to Assess Experience Effects on Lower-limb Mechanics During Moderate High-heeled Jogging and Running

This study investigated lower-limb kinematics and ground reaction force (GRF) during moderate high-heeled jogging and running. Subjects were divided into groups of experienced wearers and inexperienced wearers. A three-dimensional motion analysis system with a configured force platform captured lower-limb joint movements and GRF.

A limited number of studies have explored lower-limb biomechanics during high-heeled jogging and running, and most studies have failed to clarify the ...

using-gold-standard-gait-analysis-methods-to-assess-experience

Universidad San Sebastian

Research

JoVE Journal

Behavior

9.1K Views.  Ningbo University. This study investigated lower-limb kinematics and ground reaction force (GRF) during moderate high-heeled jogging and running. Subjects were divided into groups of experienced wearers and inexperienced wearers. A three-dimensional motion analysis system with a configured force platform captured lower-limb joint movements and GRF. 

Video: Using Gold-standard Gait Analysis Methods to Assess Experience Effects on Lower-limb Mechanics During Moderate High-heeled Jogging and Running

Substantiating Appropriate Motion Capture Techniques for the Assessment of Nordic Walking Gait and Posture in Older Adults

Nordic walking (NW) has become a safe and simple form of exercise in recent years, and in studying this gait pattern, various data collection techniques have been employed, each with positives and negatives. The aim was to determine the effect of NW on older adult gait and posture and to determine optimal use of different data collection systems in both short and long duration analysis. Gait and posture during NW and normal walking were assessed in 17 healthy older adults (age: 69 &#177; 7.3). Participants performed two trials of 6 Minute Walk Tests (6MWT) (1 with poles (WP) and 1 without poles (NP)) and 6 trials of a 5m walk (3 WP and 3 NP). Motion was recorded using two systems, a 6-sensor accelerometry system and an 8-camera 3-dimensional motion capture system, in order to quantify spatial-temporal, kinematic, and kinetic parameters.
With both systems, participants demonstrated increased stride length and double support and decreased gait speed and cadence WP compared to NP (p &#60;0.05). Also, with motion capture, larger single support time was found WP (p &#60;0.05). With 3-D capture, smaller hip power generation and moments of force were found at heel contact and pre-swing as well as smaller knee power absorption at heel contact, pre-swing, and terminal swing WP compared to NP, when assessed over one cycle (p &#60;0.05). Also, WP yielded smaller moments of force at heel contact and terminal swing along with larger moments at mid-stance of a gait cycle (p &#60;0.05). No changes were found for posture.
NW seems appropriate for promoting a normal gait pattern in older adults. Three-dimensional motion capture should primarily be used during short duration gait analysis (i.e. single gait cycle), while accelerometry systems should be primarily employed in instances requiring longer duration analysis such as during the 6MWT.

The aim was to substantiate optimal use of data collection techniques for Nordic walking gait and posture analysis. Three-dimensional motion capture should be used during short duration analysis (i.e. single gait cycle), while accelerometry should be employed for longer duration analysis (i.e. repeated cycles) like a 6 Minute Walk Test.

Nordic walking (NW) has become a safe and simple form of exercise in recent years, and in studying this gait pattern, various data collection techniques ...

Oscillation and Reaction Board Techniques for Estimating Inertial Properties of a Below-knee Prosthesis

The purpose of this study was two-fold: 1) demonstrate a technique that can be used to directly estimate the inertial properties of a below-knee prosthesis, and 2) contrast the effects of the proposed technique and that of using intact limb inertial properties on joint kinetic estimates during walking in unilateral, transtibial amputees. An oscillation and reaction board system was validated and shown to be reliable when measuring inertial properties of known geometrical solids. When direct measurements of inertial properties of the prosthesis were used in inverse dynamics modeling of the lower extremity compared with inertial estimates based on an intact shank and foot, joint kinetics at the hip and knee were significantly lower during the swing phase of walking. Differences in joint kinetics during stance, however, were smaller than those observed during swing. Therefore, researchers focusing on the swing phase of walking should consider the impact of prosthesis inertia property estimates on study outcomes. For stance, either one of the two inertial models investigated in our study would likely lead to similar outcomes with an inverse dynamics assessment.

Body segmental inertial properties are required for inverse dynamics modeling. Using an oscillation and reaction board technique, inertial properties of below-knee prostheses were measured. Using direct measures of prosthesis inertia in the inverse dynamics model of the prosthetic leg resulted in lower magnitudes of resultant joint forces and moments.

The purpose of this study was two-fold: 1) demonstrate a technique that can be used to directly estimate the inertial properties of a below-knee ...

Bioengineering

Clinical-oriented Three-dimensional Gait Analysis Method for Evaluating Gait Disorder

Three-dimensional gait analysis (3DGA) is shown to be a useful clinical tool for the evaluation of gait abnormality due to movement disorders. However, the use of 3DGA in actual clinics remains uncommon. Possible reasons could include the time-consuming measurement process and difficulties in understanding measurement results, which are often presented using a large number of graphs. Here we present a clinician-friendly 3DGA method developed to facilitate the clinical use of 3DGA. This method consists of simplified preparation and measurement processes that can be performed in a short time period in clinical settings and intuitive results presentation to facilitate clinicians&#39; understanding of results. The quick, simplified measurement procedure is achieved by the use of minimum markers and measurement of patients on a treadmill. To facilitate clinician understanding, results are presented in figures based on the clinicians&#39; perspective. A Lissajous overview picture (LOP), which shows the trajectories of all markers from a holistic viewpoint, is used to facilitate intuitive understanding of gait patterns. Abnormal gait pattern indices, which are based on clinicians&#39; perspectives in gait evaluation and standardized using the data of healthy subjects, are used to evaluate the extent of typical abnormal gait patterns in stroke patients. A graph depicting the analysis of the toe clearance strategy, which depicts how patients rely on normal and compensatory strategies to achieve toe clearance, is also presented. These methods could facilitate implementation of 3DGA in clinical settings and further encourage development of measurement strategies from the clinician&#39;s point of view.

In this study, a clinician-friendly three-dimensional gait analysis method, which was designed to be performed in the rehabilitation clinic, is presented. The method consists of a simplified measurement method and intuitive figures to facilitate clinicians&#39; understanding of the results.

Three-dimensional gait analysis (3DGA) is shown to be a useful clinical tool for the evaluation of gait abnormality due to movement disorders. However, ...

3D Kinematic Gait Analysis for Preclinical Studies in Rodents

The utility of three-dimensional (3D) kinematic motion analysis systems is limited in rodents. Part of the reason for this inadequacy is the use of complex algorithms and mathematical modeling that accompany 3D data collection and analysis procedures. This work provides a simple, user-friendly, step-by-step detailed methodology for 3D kinematic gait analysis during treadmill locomotion in healthy and neurotraumatic rats using a six-camera motion capture system. Also provided are details on 1) calibration of the system in an experimental set-up customized for quadrupedal locomotion, 2) data collection for treadmill locomotion in adult rats using markers positioned on all four limbs, 3) options available for video tracking and processing, and 4) basic 3D kinematic data generation and visualization and quantification of data using the built-in data collection software. Finally, it is suggested that the utility of this motion capture system be expanded to studying a variety of motor behaviors before and after neurotrauma.

Presented here is a protocol to collect and analyze three-dimensional kinematics of quadrupedal locomotion in rodents for preclinical studies.

The utility of three-dimensional (3D) kinematic motion analysis systems is limited in rodents. Part of the reason for this inadequacy is the use of ...

Comparative Analysis of Lower Limb Kinematics between the Initial and Terminal  Phase  of 5km Treadmill Running

Running is beneficial for physical health, but it is also accompanied by many injuries. However, the main factors leading to running injury remain unexplained. This study investigated the effects of long running distance on lower-limb kinematic variables and the lower limb kinematic difference of between the initial (IR) and terminal phase (TR) of 5 km running was compared. Ten amateur runners ran on a treadmill at the speed of 10 km/h. Dynamic kinematic data was collected at the phase of IR (0.5 km) and TR (5 km), respectively. The peak angle, peak angular velocities, and range of motion were recorded in this experiment. The main results demonstrated the following: ankle eversion and knee abduction were increased at TR; ROMs of ankle and knee were increased in the frontal plane at TR than IR; a larger peak angular velocity of ankle dorsiflexion and hip interrotation were found in TR compared to IR. These changes during the long distance running may provide some specific details for exploring potential reasons of running injuries.

This study investigated the biomechanical characteristics of the lower extremity kinematic variables between the initial and terminal phase of 5 km treadmill running. The lower-limb kinematic data of 10 runners were collected using a three-dimensional motion capture system on a treadmill at the initial phase (0.5 km) and the terminal phase (5 km), respectively.

Running is beneficial for physical health, but it is also accompanied by many injuries. However, the main factors leading to running injury remain ...

Lower-Limb Biomechanical Characteristics Associated with Unplanned Gait Termination Under Different Walking Speeds

Gait termination caused by unexpected stimulus is a common occurrence in everyday life. This study presents a protocol to investigate the lower-limb biomechanical changes that occur during unplanned gait termination (UGT) under different walking speeds. Fifteen male participants were asked to perform UGT on a walkway at normal walking speed (NWS) and fast walking speed (FWS), respectively. A motion analysis system and plantar pressure platform were applied to collect lower-limb kinematic and plantar pressure data. Paired-sampled T-test was used to examine the differences in lower-limb kinematics and plantar pressure data between two walking speeds. The results showed larger range of motion in the hip, knee, and ankle joints in the sagittal plane as well as plantar pressure in forefoot and heel regions during UGT at FWS when compared with NWS. With the increase in walking speed, subjects exhibited different lower-limb biomechanical characteristics that show FWS associated with greater potential injury risks.

This study compared the biomechanical characteristics of the lower extremity during unplanned gait termination under different walking speeds. The lower-limb kinematic and kinetic data from fifteen subjects with normal and fast walking speeds were collected using a motion analysis system and plantar pressure platform.

Gait termination caused by unexpected stimulus is a common occurrence in everyday life. This study presents a protocol to investigate the lower-limb ...

Clinical Assessment of Spatiotemporal Gait Parameters in Patients and Older Adults

Spatial and temporal characteristics of human walking are frequently evaluated to identify possible gait impairments, mainly in orthopedic and neurological patients1-4, but also in healthy older adults5,6. The quantitative gait analysis described in this protocol is performed with a recently-introduced photoelectric system (see&#160;Materials table) which has the potential to be used in the clinic because it is portable, easy to set up (no subject preparation is required before a test), and does not require maintenance and sensor calibration. The photoelectric system consists of series of high-density floor-based photoelectric cells with light-emitting and light-receiving diodes that are placed parallel to each other to create a corridor, and are oriented perpendicular to the line of progression7. The system simply detects interruptions in light signal, for instance due to the presence of feet within the recording area. Temporal gait parameters and 1D spatial coordinates of consecutive steps are subsequently calculated to provide common gait parameters such as step length, single limb support and walking velocity8, whose validity against a criterion instrument has recently been demonstrated7,9. The measurement procedures are very straightforward; a single patient can be tested in less than 5 min&#160;and a comprehensive report can be generated in less than 1&#160;min.

This protocol is used to evaluate spatial and temporal gait variables of neurological/orthopedic patients and older persons by means of a recently-introduced floor-based photocell system.

Spatial and temporal characteristics of human walking are frequently evaluated to identify possible gait impairments, mainly in orthopedic and ...

Medicine

Evaluation of Patients' Posture and Gait Profile After Lumbar Fusion Surgery by Video Rasterstereography and Treadmill Gait Analysis

This protocol provides guidance on how to perform high resolution video rasterstereography and treadmill gait analysis on patients after lumbar fusion surgery to obtain results about altered variables of gait and posture. These observed changes can then be correlated with the patient-reported outcome measure of pain relief. The rasterstereographic device projects lines of parallel light onto the surface of the tested subject&#39;s back. The deformation of these lines is recognized by the device. From these data, a special software then generates a 3-D profile based on the principle of triangulation. With an inaccuracy of only 0.2 mm it can measure changes in posture at very high precision. Gait and stance parameters are recorded using a treadmill equipped with an electric sensor mat that contains 10,200 miniature force sensors in the registering zone under the belt. Initial walking speed on the treadmill is 0.5 km/h. Speed is then gradually increased by increments of 0.1 km/h until each subject reaches his or her individual maximum well tolerable walking speed. At this speed, parameters are recorded during a 20 s measurement interval. Subjects are tested barefoot and without holding a handrail. Among various other parameters, stride width, step length, stance phase and foot rotation are measured. Both methods used reportedly have a high intra- and inter-observer reliability. The advantage of these highly accurate techniques is that they offer an objective and very detailed perspective on changes in the patient&#39;s posture and gait. Due to the amount of data generated, these techniques are, however, not so much suitable for everyday routine use, but rather interesting to scientifically evaluate long term alterations in posture and gait in patients like for example after lumbar fusion surgery.

Here, we present a protocol to analyze the posture and the gait of patients after lumbar fusion surgery by means of high-resolution video rasterstereography and a treadmill equipped with an integrated sensor mat. Allowing critical functional postoperative evaluation on a less subjective level may enhance accuracy and reliability of indication for surgery.

This protocol provides guidance on how to perform high resolution video rasterstereography and treadmill gait analysis on patients after lumbar fusion ...

Lower Limb Biomechanical Analysis of Healthy Participants

Biomechanical analysis techniques are useful in the study of human movement. The aim of this study was to introduce a technique for the lower limb biomechanical assessment in healthy participants using commercially available systems. Separate protocols were introduced for the gait analysis and muscle strength testing systems. To ensure maximum accuracy for gait assessment, attention should be given to the marker placements and self-paced treadmill acclimatization time. Similarly, participant positioning, a practice trial, and verbal encouragement are three critical stages in muscle strength testing. The current evidence suggests that the methodology outlined in this article may be effective for the assessment of lower limb biomechanics.

This article introduces a comprehensive experimental methodology on two of the latest technologies available to measure the lower limb biomechanics of individuals.

Biomechanical analysis techniques are useful in the study of human movement. The aim of this study was to introduce a technique for the lower limb ...

Influence of Step-Width Manipulation on Running Biomechanics

Step width is a critical factor influencing lower limb biomechanics during running, significantly affecting stability, performance, and injury risk. Understanding these effects is essential for optimizing running performance and minimizing injury risk. This study evaluated the effects of varying step widths on lower limb biomechanics at different running speeds. Thirteen healthy Chinese males (aged 20-24) participated in the study, running at speeds of 3.0 m/s and 3.7 m/s using six distinct step widths: the preferred step width and five variations (reductions of 13% and 6.5%, and increases of 6.5%, 13%, and 25%, based on leg length). Data were collected using a motion capture system and force plates and analyzed through repeated measures ANOVA and correlation tests. The results indicated that wider step widths significantly reduced peak knee abduction moments and hip adduction angles, whereas narrower step widths increased knee joint loading. These findings have important implications for clinicians and runners, suggesting that careful step width selection can help reduce injury risk and enhance running efficiency. This study contributes a new dataset that lays the foundation for future research into the relationship between step width and running biomechanics and serves as a reference for training and rehabilitation practices.

The present protocol outlines an experimental setup designed to investigate the influence of step width manipulation on running biomechanics using a motion capture system. The objective is to expand relevant datasets and examine the effects of varying step widths on the kinematic chain of the human lower limb.

Step width is a critical factor influencing lower limb biomechanics during running, significantly affecting stability, performance, and injury risk. ...