Name: lower-limb biomechanical characteristics associated with unplanned gait termination under different walking speeds
Uploaded: 2020-08-25T14:00:00.000+00:00
Duration: 5 min 52 s
Description: Watch this Scientific Journal Video about Lower-Limb Biomechanical Characteristics Associated with Unplanned Gait Termination Under Different Walking Speeds at JoVE.com

NSFC-RSE Joint Project (81911530253), National Key R&#38;D Program of China (2018YFF0300905), and K. C. Wong Magna Fund in Ningbo University.

The Human Ethics Committee of Ningbo University approved this experiment. All written informed consent was obtained from all subjects after they were told about the goal, requirements, and experimental procedures of the UGT experiment.
1. Laboratory preparation for gait
<ol>
	<li>Kinematics: Motion capture system
	<ol>
		<li>When calibrating the system, turn off the incandescent lights and remove any possible reflective objects that can be mistaken for passive retro-reflective markers. Ensure that eight infrared cameras are properly aimed and have a clear and reasonable view.</li>
		<li>Plug the appropriate USB dongle into the PC&#8217;s parallel port. Switch on the motion-capture infrared cameras and analog-to-digital converter.</li>
		<li>Open the tracking software in the PC and allow time for the eight infrared cameras to initialize. Select &#8220;Local System&#8221; node of the &#8220;Resources&#8221; pane. Every camera node will show a green light if the hardware connection is true.</li>
		<li>Adjust the system parameters in the Camera view pane: set the Strobe Intensity to 0.95 - 1, Threshold to 0.2 - 0.4, Gain to times 1 (x1), Grayscale Mode to Auto, Minimum Circularity Ratio to 0.5, and Max Blob Height to 50.</li>
		<li>Put the T-frame consisting of 5 markers in the center of the motion capture area. Select all cameras using 2D mode and confirm that they can view the calibration wand (T-frame) without any interference and/or artefacts. Click the &#8220;System Preparation&#8221; item in the toolbar and select the 5 marker Wand &#38; T-Frame calibration object from the T-Frame drop-down list.</li>
		<li>In the &#8220;Tool&#8221; pane, select the &#8220;System Preparation&#8221; button, and click the &#8220;Start&#8221; button in the &#8220;Calibrate Cameras&#8221; section. Then physically wave the T-frame in the capture range. Stop the action when the blue lights on the infrared cameras stop flashing. Monitor the progress bar until the Calibration Process is completed at &#8220;100%&#8221;and returns to &#8220;0%&#8221;. 
		NOTE: Ensure the values of the Image Error are less than 0.3.</li>
		<li>Put the T-frame on the floor (the center of the motion capture area) and ensure the axes of T-frame are consistent with the heading direction.</li>
		<li>Select the &#8220;Start&#8221; button under the &#8220;Set Volume Origin&#8221; section in the Tool pane.</li>
	</ol>
	</li>
	<li>Plantar pressure: Pressure platform
	<ol>
		<li>Put the 2 m pressure platform in the center of the test area. Notice the eight infrared cameras displayed around the pressure platform.</li>
		<li>Divide the pressure platform into four average areas, A, B, C and D (each area is 50 cm * 50 cm) in a linear fashion and distinguish them with an alphabet label / sticker (Figure 1).</li>
		<li>Keep the PC and pressure platform connected via the proprietary data cable.</li>
		<li>Double-click the software icon on the desktop.</li>
		<li>Click the &#8220;Weight Calibration&#8221; on the Calibration Screen and input the body mass of a staff. Ask him or her to stand on the pressure platform, waiting until the system completes the calibration automatically before he/she can leave the pressure platform.</li>
	</ol>
	</li>
</ol>
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/61558/61558fig01.jpg" /> 
Figure 1: Experimental protocol.&#160;If subjects received the termination signal as the heel touched area (A), the UGT was executed so that the subject stopped in area (B). Kinematic and plantar pressure data were collected synchronically. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/61558/61558fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
2. Participant preparation
<ol>
	<li>Before the UGT test, interview all subjects and provide them with a simple explanation about the experimental goals and procedures. Obtain written informed consent from subjects who meet the key inclusion criteria.
	<ol>
		<li>Include participants who are physically active male adults, have the right leg as dominant, do not have any hearing disorder, do not have lower-limb disorders, and have not incurred injuries in the last six months. 
		NOTE: 15 male subjects (age: 24.1 &#177; 0.8 years; height: 175.7 &#177; 2.8 cm; body weight: 68.3 &#177; 3.3 kg; foot length: 252.7 &#177; 2.1 mm) who met the experimental conditions were included in this test.</li>
	</ol>
	</li>
	<li>Allow all subjects fill in a questionnaire survey. 
	NOTE: Questions include: Have you had a history of running or other physical activities? How often do you do physical activities in a week? Do you have any professional athletic training? Have you suffered any lower-limb disorders and injuries in the last six months?</li>
	<li>Ensure that all subjects wear identical t-shirts and tight-fitting pants.</li>
	<li>Measure subjects&#8217; standing height (mm) and body weight (kg), lower limb length (mm), knee width (mm) and ankle width (mm) of both left and right leg using Vernier caliper or small anthropometer. 
	NOTE: Measure the lower limb length from the superior iliac spine to the ankle medial condyle; the knee width from the lateral to the medial knee condyle; the ankle width from the lateral to the medial ankle condyle.</li>
	<li>Shave off the body hair as appropriate and remove excess sweat using alcohol wipes. Prepare skin areas of anatomical bony landmarks for marker placement on joints and segments. 
	NOTE: This study used 16 reflective markers18, including anterior-superior iliac spine (LASI/RASI), posterior-superior iliac spine (LPSI/RPSI), lateral mid-thigh (LTHI/RTHI), lateral knee (LKNE/RKNE), lateral mid-shank (LTIB/RTIB), lateral malleolus (LANK/RANK), second metatarsal head (LTOE/RTOE) and calcaneus (LHEE/RHEE) (Figure 2).</li>
	<li>Identify 16 anatomical landmarks. On the landmarks, attach passive retro-reflective markers with double-sided adhesive tapes.</li>
	<li>Give each subject 5 min to adapt to the test environment and warm up with light running and stretching.</li>
</ol>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/61558/61558fig02.jpg" /> 
Figure 2: The reflective markers attached to the lower limbs.&#160;(A) side, (B) front and (C) rear. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/61558/61558fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
3. Static calibration
<ol>
	<li>Kinematics: Motion capture system
	<ol>
		<li>In the tracking software, find the &#8220;New Database&#8221; in the toolbar to build a database. Click the &#8220;Data Management&#8221; to open the &#8220;Data Management&#8221; pane and click in order the &#8220;New Patient Classification&#8221;, &#8220;New Patient&#8221; and &#8220;New Session&#8221; button. Return to the &#8220;Resources&#8221; window, select &#8220;Create A New Subject&#8221; button to create a subject, and enter the values of height (mm), body weight (kg), leg length (mm), knee width (mm), and ankle width (mm) in the &#8220;Properties&#8221; pane.</li>
		<li>Click the &#8220;Go Live&#8221; and then click the &#8220;Split Horizontally&#8221; in the &#8220;View&#8221; pane. Then select the graph to view the Trajectory count. 
		NOTE: Check the &#8220;3D Perspective&#8221; pane to ensure that all 16 markers are visible.</li>
		<li>Ask subjects to stand still in the area A. Click &#8220;Start&#8221; in the subject capture section to capture the static model. About 200 frames of images were captured before clicking the &#8220;Stop&#8221; button.</li>
		<li>In the &#8220;Tools&#8221; pane, find the &#8220;Pipeline&#8221; button, and click on &#8220;Run the reconstruct pipeline&#8221; to build a new 3D image of all captured markers. Identify in the markers&#39; list, and manually apply the corresponding labels to the markers. Save and press &#8220;ESC&#8221; key to exit.</li>
		<li>Select &#8220;Subject Preparation&#8221; and &#8220;Subject Calibration&#8221; in the toolbar and choose the &#8220;Static plug-in gait&#8221; option in the drop-down menu.</li>
		<li>Select the &#8220;Left Foot&#8221; and &#8220;Right Foot&#8221; in the &#8220;Static Settings&#8221; pane and click the &#8220;Start&#8221;. Then save the static model.</li>
	</ol>
	</li>
	<li>Plantar pressure: Pressure platform
	<ol>
		<li>In the software, click &#8220;Database&#8221; to add a new patient. And enter the assigned subject number in the &#8220;Add Patient&#8221; pane. Then, click &#8220;Add&#8221;.</li>
		<li>Click &#8220;Dynamic&#8221; and enter body weight and shoe size. Then, click &#8220;OK&#8221;.</li>
	</ol>
	</li>
</ol>
4. Dynamic trials
<ol>
	<li>Ask the subject to be at the starting position.</li>
	<li>Software Operations 
	NOTE: The two kinds of software start (Motion capture system: click &#8220;Capture&#8221; button; Pressure platform: click &#8220;Capture&#8221; button) and end (Motion capture system: click &#8220;Stop&#8221; button; Pressure platform: click &#8220;Save Measurement&#8221; button), simultaneously.
	<ol>
		<li>Kinematics: Motion capture system
		<ol>
			<li>Select the &#8220;Go Live&#8221; button in the &#8220;Resources&#8221; pane and click &#8220;Capture&#8221; in the right toolbar. Find &#8220;Trial Type&#8221; and &#8220;Session&#8221; from top to bottom and edit &#8220;Trial&#8221; description.</li>
			<li>Ask subjects to perform UGT test as described in 4.3.</li>
			<li>After finishing the UGT test, click &#8220;Stop&#8221; to end the data collection trial. Repeat the above steps for 5 times.</li>
		</ol>
		</li>
		<li>Plantar pressure: Pressure platform
		<ol>
			<li>Select the &#8220;Measure&#8221; button before starting the UGT trials.</li>
			<li>After finishing the UGT test, click &#8220;Save Measurement&#8221; button to save data. Repeat the above steps for 5 times.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>UGT trials
	<ol>
		<li>Ask subjects to walk along a walkway at their NWS and instruct them to use the dominant leg and non-dominant leg to pass area A and B, respectively, and finally stop at area D on the pressure platform.</li>
		<li>Let the subject know when the termination signal is provided they need to quickly stop on area B.</li>
		<li>Randomly provide the termination signal as the heel touches area A, ensure that the UGT is executed and subjects stop quickly on area B (Figure 1). The staff sends the termination signal by randomly ringing a red bell, and the probability of ringing was controlled at about 20%. Capture at least five successive UGT trials. 
		NOTE: There is a 2-min rest interval between both trials.</li>
		<li>Calculate each subject&#8217;s walking speed using the pressure platform software. Then, calculate the FWS as 125% of the NWS.</li>
		<li>Repeat the above UGT test for the FWS. Capture at least 5 successive UGT trials using the FWS protocol.</li>
	</ol>
	</li>
</ol>
5. Post-processing
<ol>
	<li>Kinematics: Motion capture system
	<ol>
		<li>Find the &#8220;Data Management&#8221; button in the toolbar and double-click the trial name in the &#8220;Data Management&#8221; pane. Then select &#8220;Reconstruct&#8221; and &#8220;Label&#8221; to reconstruct the 3D dynamic model.</li>
		<li>On the &#8220;Time&#8221; bar, move the blue triangles to set the required range of time (for the stance phase during UGT).</li>
		<li>Click on the &#8220;Time&#8221; bar. Then click &#8220;Zoom to Region-of-Interest&#8221; in the &#8220;Context&#8221; menu.</li>
		<li>Click the &#8220;Label&#8221; button to identify and check the label points. Ensure the steps are the same as the static identification process. 
		NOTE: Fill in some incomplete identification markers and delete the unlabeled markers (if necessary).</li>
		<li>Choose the &#8220;Dynamic Plug-in Gait&#8221; in the &#8220;Subject Calibration&#8221; pane. Then click the &#8220;Start&#8221; button to run the data. Export dynamic trials in &#8220;.csv&#8221; format for following data analysis.</li>
		<li>Use a fourth-order low pass Butterworth filter with cut off frequency of 10 Hz and export the data of the joint angle.</li>
		<li>Calculate the range of motion (ROM) of three joints (hip, knee, and ankle) in sagittal plane. 
		NOTE: Define the differences between the maximum angles and minimum angles of the hip, knee, and ankle on the sagittal movement planes as the ROMs.</li>
		<li>Calculate means (M) and standard deviations (SD) of the ten trials (5 for NWS, and 5 for FWS) from each subject.</li>
	</ol>
	</li>
	<li>Plantar pressure: Pressure platform
	<ol>
		<li>Select the trial name from the &#8220;Measurements&#8221; menu of the corresponding subjects. Click the &#8220;Dynamic&#8221; button to open data.</li>
		<li>Click the &#8220;Manual&#8221; selection. Use the &#8220;Left Mouse&#8221; button to select the step of interest (the stance phase during GT). Click the &#8220;OK&#8221; button to save.</li>
		<li>Click the &#8220;Zone Division&#8221; and &#8220;Manual Zone Selection&#8221; to make adjusts. Then click the &#8220;Accept&#8221; button to save.</li>
		<li>Open &#8220;Pressures-Forces&#8221; screen and click the &#8220;Graph Composition&#8221; button to open the &#8220;Zone Graph Composition&#8221; window. Divide 10 anatomical regions, including Big Toe (BT), Other Toes (OT), First Metatarsal (M1), Second Metatarsals (M2), Third Metatarsal (M3), Fourth Metatarsal (M4), Fifth Metatarsal (M5), Mid-Foot (MF), Medial Heel (MH) and Lateral Heel (LH). Then click the &#8220;OK&#8221; button to save.</li>
		<li>Click &#8220;Parameter Table&#8221; to export plantar pressure data, including maximum pressure, maximum force and contact area.</li>
		<li>Calculate Means and SDs for 10 trials (5 for NWS, and 5 for FWS) from each subject.</li>
	</ol>
	</li>
</ol>
6. Statistical analysis
<ol>
	<li>Perform the Shapiro&#8211;Wilks tests to check normal distribution for all variables. Use Paired-sampled T-tests to compare lower limb kinematics and plantar pressure data during UGT at NWS and FWS. Set the significance level at p &#60; 0.05.</li>
</ol>

<ol>
	<li>Cappozzo, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Gait+analysis+methodology.">Gait analysis methodology.</a> Human Movement Science. 3 (1), 27-50 (1984).</li><li>Gao, Z., Mei, Q., Fekete, G., Baker, J., Gu, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Effect+of+Prolonged+Running+on+the+Symmetry+of+Biomechanical+Variables+of+the+Lower+Limb+Joints.">The Effect of Prolonged Running on the Symmetry of Biomechanical Variables of the Lower Limb Joints.</a> Symmetry. 12, 720 (2020).</li><li>Sparrow, W. A., Tirosh, O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Gait+termination:+a+review+of+experimental+methods+and+the+effects+of+ageing+and+gait+pathologies.">Gait termination: a review of experimental methods and the effects of ageing and gait pathologies.</a> Gait &amp; Posture. 22 (4), 362-371 (2005).</li><li>Conte, 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=Planned+Gait+Termination+in+Cerebellar+Ataxias.">Planned Gait Termination in Cerebellar Ataxias.</a> The Cerebellum. 11 (4), 896-904 (2012).</li><li>Bishop, M. D., Brunt, D., Pathare, N., Patel, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+interaction+between+leading+and+trailing+limbs+during+stopping+in+humans.">The interaction between leading and trailing limbs during stopping in humans.</a> Neuroscience Letters. 323 (1), 1-4 (2002).</li><li>Jaeger, R. J., Vanitchatchavan, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ground+reaction+forces+during+termination+of+human+gait.">Ground reaction forces during termination of human gait.</a> Journal of Biomechanics. 25 (10), 1233-1236 (1992).</li><li>Cen, X., Jiang, X., Gu, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Do+different+muscle+strength+levels+affect+stability+during+unplanned+gait+termination.">Do different muscle strength levels affect stability during unplanned gait termination.</a> Acta of Bioengineering and Biomechanics. 21 (4), 27-35 (2019).</li><li>O'Kane, F. W., McGibbon, C. A., Krebs, D. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Kinetic+analysis+of+planned+gait+termination+in+healthy+subjects+and+patients+with+balance+disorders.">Kinetic analysis of planned gait termination in healthy subjects and patients with balance disorders.</a> Gait &amp; Posture. 17 (2), 170-179 (2003).</li><li>Bishop, M., Brunt, D., Pathare, N., Patel, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+effect+of+velocity+on+the+strategies+used+during+gait+termination.">The effect of velocity on the strategies used during gait termination.</a> Gait &amp; Posture. 20 (2), 134-139 (2004).</li><li>Ridge, S. T., Henley, J., Manal, K., Miller, F., Richards, J. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biomechanical+analysis+of+gait+termination+in+11&#8211;17year+old+youth+at+preferred+and+fast+walking+speeds.">Biomechanical analysis of gait termination in 11&#8211;17year old youth at preferred and fast walking speeds.</a> Human Movement Science. 49, 178-185 (2016).</li><li>Sun, D., Fekete, G., Mei, Q., Gu, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+effect+of+walking+speed+on+the+foot+inter-segment+kinematics,+ground+reaction+forces+and+lower+limb+joint+moments.">The effect of walking speed on the foot inter-segment kinematics, ground reaction forces and lower limb joint moments.</a> PeerJ. 6, 5517 (2018).</li><li>Eerdekens, M., Deschamps, K., Staes, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+impact+of+walking+speed+on+the+kinetic+behaviour+of+different+foot+joints.">The impact of walking speed on the kinetic behaviour of different foot joints.</a> Gait &amp; Posture. 68, 375-381 (2019).</li><li>Wang, Z. p., Qiu, Q. e., Chen, S. h., Chen, B. c., Lv, X. t. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effects+of+Unstable+Shoes+on+Lower+Limbs+with+Different+Speeds.">Effects of Unstable Shoes on Lower Limbs with Different Speeds.</a> Physical Activity and Health. 3, 82-88 (2019).</li><li>Tirosh, O., Sparrow, W. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Age+and+walking+speed+effects+on+muscle+recruitment+in+gait+termination.">Age and walking speed effects on muscle recruitment in gait termination.</a> Gait &amp; Posture. 21 (3), 279-288 (2005).</li><li>Xiang, L., Mei, Q., Fernandez, J., Gu, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+biomechanical+assessment+of+the+acute+hallux+abduction+manipulation+intervention.">A biomechanical assessment of the acute hallux abduction manipulation intervention.</a> Gait &amp; Posture. 76, 210-217 (2020).</li><li>Zhou, H., Ugbolue, U. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Is+There+a+Relationship+Between+Strike+Pattern+and+Injury+During+Running:+A+Review.">Is There a Relationship Between Strike Pattern and Injury During Running: A Review.</a> Physical Activity and Health. 3 (1), 127-134 (2019).</li><li>Serrao, M., 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=Sudden+Stopping+in+Patients+with+Cerebellar+Ataxia.">Sudden Stopping in Patients with Cerebellar Ataxia.</a> The Cerebellum. 12 (5), 607-616 (2013).</li><li>Zhang, 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=Using+Gold-standard+Gait+Analysis+Methods+to+Assess+Experience+Effects+on+Lower-limb+Mechanics+During+Moderate+High-heeled+Jogging+and+Running.">Using Gold-standard Gait Analysis Methods to Assess Experience Effects on Lower-limb Mechanics During Moderate High-heeled Jogging and Running.</a> Journal of Visualized Experiments. (127), e55714 (2017).</li><li>Buddhadev, H. H., Barbee, C. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Redistribution+of+joint+moments+and+work+in+older+women+with+and+without+hallux+valgus+at+two+walking+speeds.">Redistribution of joint moments and work in older women with and without hallux valgus at two walking speeds.</a> Gait &amp; Posture. 77, 112-117 (2020).</li><li>Yu, P., 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=Morphology-Related+Foot+Function+Analysis:+Implications+for+Jumping+and+Running.">Morphology-Related Foot Function Analysis: Implications for Jumping and Running.</a> Applied Sciences. 9 (16), 3236 (2019).</li><li>Ridge, S. T., Henley, J., Manal, K., Miller, F., Richards, J. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Kinematic+and+kinetic+analysis+of+planned+and+unplanned+gait+termination+in+children.">Kinematic and kinetic analysis of planned and unplanned gait termination in children.</a> Gait &amp; Posture. 37 (2), 178-182 (2013).</li><li>Burnfield, J. M., Few, C. D., Mohamed, O. S., Perry, J. <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+walking+speed+and+footwear+on+plantar+pressures+in+older+adults.">The influence of walking speed and footwear on plantar pressures in older adults.</a> Clinical Biomechanics. 19 (1), 78-84 (2004).</li><li>Cen, X., Xu, D., Baker, J. S., Gu, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effect+of+additional+body+weight+on+arch+index+and+dynamic+plantar+pressure+distribution+during+walking+and+gait+termination.">Effect of additional body weight on arch index and dynamic plantar pressure distribution during walking and gait termination.</a> PeerJ. 8, 8998 (2020).</li><li>Chatzipapas, C. N., 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=Stress+Fractures+in+Military+Men+and+Bone+Quality+Related+Factors.">Stress Fractures in Military Men and Bone Quality Related Factors.</a> International Journal of Sports Medicine. 29 (11), 922-926 (2008).</li><li>Cen, X., Xu, D., Baker, J. S., Gu, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Association+of+Arch+Stiffness+with+Plantar+Impulse+Distribution+during+Walking,+Running,+and+Gait+Termination.">Association of Arch Stiffness with Plantar Impulse Distribution during Walking, Running, and Gait Termination.</a> International Journal of Environmental Research and Public Health. 17 (6), 2090 (2020).</li></ol>

No potential conflict of interest was reported by the authors.

Most previous studies that analyze gait biomechanics during UGT omit the importance of walking speed in their biomechanical assessment. Thus, this study investigated the lower-limb biomechanical changes that occur in UGT at NWS and FWS with the aim to reveal the speed-related effects.
Significant differences have been found on the ROM of the hip, knee, and ankle joints in the sagittal plane during UGT at NWS and FWS. Our findings showed greater ROMs of the 3 joints in the sagittal plane during...

Human locomotion is considered to be an extremely complex process that needs to be described by multidisciplinary methods1,2. The most representative aspect is the gait analysis by biomechanical approaches. Human gait aims to sustain progression from initiation to termination, and the dynamic balance should be maintained in position movement. Although gait termination (GT) has been extensively studied as a sub-task of gait, it has received less attention. Sparrow and Tirosh3 defined GT in their review as motor control period when both feet stop moving either forward or backward based on the displacement and time characteristics. Compared to steady-state gait, the process of executing GT demands higher control of postural stability and complex integration and cooperation of the neuromuscular system4. During GT, the body needs to rapidly increase the braking impulse and decrease propulsion impulse to form a new body balance5,6. Unplanned gait termination (UGT) is a stress response to an unknown stimulus6. When confronted by an unexpected stimulus that requires one to stop suddenly, initial dynamic balance will be disrupted. Because of the need for the continuous control of the body&#8217;s center of mass (COM) and feedback control, UGT poses a greater challenge to postural control and stablity3,7.
UGT has been reported to be an important factor leading to falls and injuries, especially in elderly people and patients with balance disorders3,8. Faster walking speeds may lead to an additional decline in motor control during UGT9. Ridge et al.10 investigated the peak joint angle and internal joint moment data of children during UGT at normal walking speed (NWS) and fast walking speed (FWS). The results showed larger knee flexion angles and extension moments at faster speeds compared with preferred speed. They indicated that strengthening the related muscles surrounding the lower extremity joints could be a useful intervention for injury prevention during UGT.
Although the effect of walking speed on the lower-limb biomechanical character during steady-state gait has been extensively studied11,12,13, the biomechanical mechanism of UGT under different walking speeds is limited. To our knowledge, only three studies have specifically evaluated healthy individuals&#8217; UGT performances with respect to velocity effects9,10,14. However, subjects in these studies were mainly the elderly14 and children10, the biomechanical mechanism of young adults during UGT is still unclear. Lower-limb kinematics and plantar pressure can provide a precise analysis of locomotion biomechanics, and these are also considered to be crucial components for clinical gait diagnoses15,16. For example, Serrao et al.17 used lower-limb kinematic data to detect the clinical differences between patients with cerebellar ataxia and healthy counterparts during sudden stopping. Besides, compared to planned gait termination (PGT), larger peak pressure and force in the lateral metatarsal during UGT could be observed7, which may be associated with higher injury risks.
Therefore, exploring the biomechanical mechanisms of UGT could provide insights for injury prevention and further clinical researches. This study presents a protocol to investigate any biomechanical alteration in young adults during UGT under different walking speeds. It is hypothesized that, with an increase in walking speed, participants would exhibit different lower-limb biomechanical characteristics during UGT.

<table><tbody><tr><td>14 mm Diameter Passive Retro-reflective Marker</td><td>Oxford Metrics Ltd., Oxford, UK</td><td>n=16</td><td></td></tr><tr><td>Double Adhesive Tape</td><td>Minnesota Mining and Manufacturing Corporation, Minnesota, USA</td><td>For fixing markers to skin</td><td></td></tr><tr><td>Motion Tracking Cameras</td><td>Oxford Metrics Ltd., Oxford, UK</td><td>n= 8</td><td></td></tr><tr><td>T-Frame</td><td>Oxford Metrics Ltd., Oxford, UK</td><td>-</td><td></td></tr><tr><td>Valid Dongle</td><td>Oxford Metrics Ltd., Oxford, UK</td><td>Vicon Nexus 1.4.116</td><td></td></tr><tr><td>Vicon Datastation ADC&amp;nbsp;</td><td>Oxford Metrics Ltd., Oxford, UK</td><td>-</td><td></td></tr><tr><td>Pressure platform</td><td>RSscan International, Olen, Belgium</td><td>-</td><td></td></tr></tbody></table>

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.

Mean &#38; SD values of NWS and FWS of 15 subjects were 1.33 &#177; 0.07m/s and 1.62 &#177; 0.11m/s, respectively.
Figure 3 shows the mean ROM of the hip, knee, and ankle joints in the sagittal plane during UGT at NWS and FWS. Compared with NWS, the ROM of three joints increased significantly at FWS (p&#60;0.05). In detail, the ROM of hip, knee and ankle joints increased from 22.26 &#177; 3.03, 29.72 &#177; 5.14 and 24.92 &#177; 4.17 to 25.98 &#177; 2.94, 31.61 &#...

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

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 ...

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4.5K Views.  Ningbo University. 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.

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

Asymmetric Walkway: A Novel Behavioral Assay for Studying Asymmetric Locomotion

Behavioral assays are commonly used for the assessment of sensorimotor impairment in the central nervous system (CNS). The most sophisticated methods for quantifying locomotor deficits in rodents is to measure minute disturbances of unconstrained gait overground (e.g., manual BBB score or automated CatWalk). However, cortical inputs are not required for the generation of basic locomotion produced by the spinal central pattern generator (CPG). Thus, unconstrained walking tasks test locomotor deficits due to motor cortical impairment only indirectly. In this study, we propose a novel, precise foot-placement locomotor task that evaluates cortical inputs to the spinal CPG. An instrumented peg-way was used to impose symmetrical and asymmetrical locomotor tasks mimicking lateralized movement deficits. We demonstrate that shifts from equidistant inter-stride lengths of 20% produce changes in the forelimb stance phase characteristics during locomotion with preferred stride length. Furthermore, we propose that the asymmetric walkway allows for measurements of behavioral outcomes produced by cortical control signals. These measures are relevant for the assessment of impairment after cortical damage.

Here, we present a protocol to quantify precise stepping in rodents. Cortical and the spinal central pattern generator signals are required for precise foot-placement during obstructed locomotion. We report here the novel constrained walking task that directly examines precise stepping behavior.

Behavioral assays are commonly used for the assessment of sensorimotor impairment in the central nervous system (CNS). The most sophisticated methods for ...

Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb

Individuals with sensorimotor pathology e.g., stroke have difficulty executing the common task of rising from sitting and initiating gait (sit-to-walk: STW). Thus, in clinical rehabilitation separation of sit-to-stand and gait initiation - termed sit-to-stand-and-walk (STSW) - is usual. However, a standardized STSW protocol with a clearly defined analytical approach suitable for pathological assessment has yet to be defined.
Hence, a goal-orientated protocol is defined that is suitable for healthy and compromised individuals by requiring the rising phase to be initiated from 120% knee height with a wide base of support independent of lead limb. Optical capture of three-dimensional (3D) segmental movement trajectories, and force platforms to yield two-dimensional (2D) center-of-pressure (COP) trajectories permit tracking of the horizontal distance between COP and whole-body-center-of-mass (BCOM), the decrease of which increases positional stability but is proposed to represent poor dynamic postural control.
BCOM-COP distance is expressed with and without normalization to subjects&#39; leg length. Whilst COP-BCOM distances vary through STSW, normalized data at the key movement events of seat-off and initial toe-off (TO1) during steps 1 and 2 have low intra and inter subject variability in 5 repeated trials performed by 10 young healthy individuals. Thus, comparing COP-BCOM distance at key events during performance of an STSW paradigm between patients with upper motor neuron injury, or other compromised patient groups, and normative data in young healthy individuals is a novel methodology for evaluation of dynamic postural stability.

Here, we present a novel protocol to measure positional stability at key events during the sit-to-stand-to-walk using the center-of-pressure to the whole-body-center-of-mass distance. This was derived from the force platform and three-dimensional motion-capture technology. The paradigm is reliable and can be utilized for the assessment of neurologically compromised individuals.

Individuals with sensorimotor pathology e.g., stroke have difficulty executing the common task of rising from sitting and initiating gait (sit-to-walk: ...

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, ...

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 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 ...

Medicine

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. ...

Comprehensive Understanding of Inactivity-Induced Gait Alteration in Rodents

It is well known that disuse affects neural systems and that joint motions become altered; however, which outcomes properly exhibit these characteristics is still unclear. The present study describes a motion analysis approach that utilizes three-dimensional (3D) reconstruction from video captures. Using this technology, disuse-evoked alterations of walking performances were observed in rodents exposed to a simulated microgravity environment by unloading their hindlimb by their tail. After 2 weeks of unloading, the rats walked on a treadmill, and their gait motions were captured with four charge-coupled device (CCD) cameras. 3D motion profiles were reconstructed and compared to those of control subjects using the image processing software. The reconstructed outcome measures successfully portrayed distinct aspects of distorted gait motion: hyperextension of the knee and ankle joints and higher position of the hip joints during the stance phase. Motion analysis is useful for several reasons. First, it enables quantitative behavioral evaluations instead of subjective observations (e.g., pass/fail in certain tasks). Second, multiple parameters can be extracted to fit specific needs once the fundamental datasets are obtained. Despite hurdles for broader application, the disadvantages of this method, including labor intensity and cost, may be alleviated by determining comprehensive measurements and experimental procedures.

The present protocol describes three-dimensional motion tracking/evaluation to depict gait motion alteration of rats after exposure to a simulated disuse environment.

It is well known that disuse affects neural systems and that joint motions become altered; however, which outcomes properly exhibit these characteristics ...

Neuroscience

Postural Organization of Gait Initiation for Biomechanical Analysis Using Force Platform Recordings

Gait initiation (GI), the transient phase between orthograde posture and steady-state locomotion, is a functional task and an experimental paradigm that is classically used in the literature to obtain insight into the basic postural mechanisms underlying body motion and balance control. Investigating GI has also contributed to a better understanding of the physiopathology of postural disorders in elderly and neurological participants (e.g., patients with Parkinson&#39;s disease). As such, it is recognized to have important clinical implications, especially in terms of fall prevention.
This paper aims to provide scholars, clinicians, and higher education students information on the material and method developed to investigate GI postural organization via a biomechanical approach. The method is based on force platform recordings and the direct principle of mechanics to compute the kinematics of the center of gravity and center of pressure. The interaction between these two virtual points is a key element in this method since it determines the conditions of stability and whole-body progression. The protocol involves the participant initially standing immobile in an upright posture and starting to walk until the end of an at least 5 m track.
It is recommended to vary the GI velocity (slow, spontaneous, fast) and the level of temporal pressure - gait may be initiated as soon as possible after the deliverance of a departure signal (high level of temporal pressure) or when the participant feels ready (low level of temporal pressure). Biomechanical parameters obtained with this method (e.g., duration and amplitude of anticipatory postural adjustments, step length/width, performance, and stability) are defined, and their computation method is detailed. In addition, typical values obtained in healthy young adults are provided. Finally, critical steps, limitations, and significance of the method with respect to the alternative method (motion capture system) are discussed.

This paper describes the material and method developed to investigate the postural organization of gait initiation. The method is based on force platform recordings and on the direct principle of mechanics to compute center of gravity and center of pressure kinematics.

Gait initiation (GI), the transient phase between orthograde posture and steady-state locomotion, is a functional task and an experimental paradigm that ...

Quantifying Locomotor Dysfunction in Spinal Cord Injury Mice Using MouseWalker

Using the MouseWalker to Quantify Locomotor Dysfunction in a Mouse Model of Spinal Cord Injury

The execution of complex and highly coordinated motor programs, such as walking and running, is dependent on the rhythmic activation of spinal and supra-spinal circuits. After a thoracic spinal cord injury, communication with upstream circuits is impaired. This, in turn, leads to a loss of coordination, with limited recovery potential. Hence, to better evaluate the degree of recovery after the administration of drugs or therapies, there is a necessity for new, more detailed, and accurate tools to quantify gait, limb coordination, and other fine aspects of locomotor behavior in animal models of spinal cord injury. Several assays have been developed over the years to quantitatively assess free-walking behavior in rodents; however, they usually lack direct measurements related to stepping gait strategies, footprint patterns, and coordination. To address these shortcomings, an updated version of the MouseWalker, which combines a frustrated total internal reflection (fTIR) walkway with tracking and quantification software, is provided. This open-source system has been adapted to extract several graphical outputs and kinematic parameters, and a set of post-quantification tools can be to analyze the output data provided. This manuscript also demonstrates how this method, allied with already established behavioral tests, quantitatively describes locomotor deficits following spinal cord injury.

Author Spotlight: Using the MouseWalker to Quantify Locomotor Dysfunction in a Mouse Model of Spinal Cord Injury  

An experimental pipeline to quantitatively describe the locomotor pattern of freely walking mice using the MouseWalker (MW) toolbox is provided, ranging from initial video recordings and tracking to post-quantification analysis. A spinal cord contusion injury model in mice is employed to demonstrate the usefulness of the MW system.