This study was funded by Fujita Health University [Grant Number 2015100341].

1. Preparation
NOTE: The measurement method proposed herein utilizes a simplified marker set consisting of twelve markers, as outlined below. The entire measurement process, including preparation, can be performed within 20 min. The feasibility of this protocol in real clinical settings has been verified in previous studies13,14,15,16,17.
<ol>
	<li>Perform the calibration process according to manufacturer&#39;s protocol.</li>
	<li>Instruct patients to wear easy fit, skintight legwear, and place the colored markers on the patient, as outlined below.
	<ol>
		<li>Place markers (30 mm in diameter) at the following points on the patient&#39;s body: both acromia, hips (at points one-third of the way from the greater trochanter of the femur along a line joining each anterior superior iliac spine with each greater trochanter), knees (on the midline of the anterior-posterior diameter of each lateral epicondyle of the femur), ankles (lateral malleoli), toes (fifth metatarsal heads), and iliac crests (at the position of each iliac crest on a vertical line passing through the hips).</li>
	</ol>
	</li>
</ol>
2. Measurement
<ol>
	<li>Set the speed of treadmill and measure gait patterns.
	<ol>
		<li>Instruct the patient to perform the 10 m walk test.</li>
		<li>Set a subjectively comfortable gait speed. Set the treadmill speed, starting at 70% of the over ground gait and gradually increasing the speed, to find the comfortable gait speed on the treadmill.</li>
		<li>Measure walking. For a single session it takes 20 s. If the different conditions (e.g. gait speed, orthosis etc.) need to be compared, perform several sessions. In that case, have patients rest for 1 minute between the sessions. 
		NOTE: Although 3DGA systems with infrared cameras are commonly used in 3DGA research, a video-based simplified motion analysis system (sampling frequency: 60 Hz; e.g., Kinematracer) is used in this protocol to shorten the calibration process.</li>
	</ol>
	</li>
</ol>
3. Data Analysis
<ol>
	<li>Time-distance Factors 
	NOTE: Time-distance parameters are common and basic parameters used in gait analysis studies. Events of foot initial contact and foot-off are determined automatically by the system based on toe and ankle marker trajectories.
	<ol>
		<li>To avoid errors in step detection, have two experienced physical therapists verify the accuracy of timing and adjust it if there are errors in step timing.</li>
		<li>From these detected step timings, calculate the following:</li>
		<li>Calculate Cadence (steps/min) = 60 &#215; 2 / SC (s)</li>
		<li>Calculate Stride length (m) = GS (m/s) &#215; SC (s) + (The displacement of ankle marker from foot contact to foot contact of the same side)</li>
		<li>Calculate Step length (m) = GS (m/s) &#215; (The time from foot contact of one side to foot contact of the other side) + (The average difference in the ankle position at foot contact of one side and the other side)</li>
		<li>Calculate Step width (m) = The average lateral distance between both ankle markers during double stance phase</li>
		<li>Calculate Duration of double stance: The sum of double stance phase that appears twice during a gait cycle; the time between foot contact of one side and subsequent foot off on the other side.</li>
		<li>Calculate Duration of single stance: The average time between foot off and subsequent foot contact on the opposite side. 
		NOTE: SC (Step cycle): The average time from heel contact of one side to heel contact of the same side. **GS (Gait speed)</li>
	</ol>
	</li>
	<li>Lissajous Overview Picture (LOP) 
	NOTE: LOPs are designed as a figure consisting of marker joint trajectories on major joints with the aim of facilitating understanding rehabilitation patients&#39; holistic gait patterns14 (see Figure 1).
	<ol>
		<li>Generate LOPs from trajectories at the coordinates of ten markers and the virtual center of gravity (COG) in the horizontal (x-y), sagittal (y-z), and coronal (z-x) planes (x: left/right, y: anterior/posterior, z: superior/inferior).
		<ol>
			<li>Draw the LOP with the software or by constructing a scatterplot that covers the motion range of all the markers on a spreadsheet software. Calculate the virtual COG by hypothesizing each body segment to be as follows: trunk, 0.66; thigh, 0.1; lower thigh, 0.05; and foot, 0.02. Subsequently, calculate COG as the composition center of the segments.</li>
		</ol>
		</li>
		<li>At each marker, extract raw data for the three components (x, y, and z) for each gait cycle, normalize these by gait cycle, and average the values. Set mean values of the x- and y-components of the virtual COG to 0 and use these as references for the x- and y-components of the markers.</li>
	</ol>
	</li>
	<li>Calculation of Abnormal Gait Index for Hemiparetic Gait 
	NOTE: Several common gait patterns are known to be features of hemiparetic gait after stroke. These include hip hiking, circumduction, and lateral shift of the trunk18. Indices for abnormal gait patterns have been developed to quantify the extent of these gait patterns13,16,17. To date, ten abnormal gait indices (hip hiking, circumduction, forefoot contact, retropulsion of the hip, excessive hip external rotation, excessive lateral shift of the trunk over the unaffected side, knee extensor thrust, flexed-knee gait, insufficient knee flexion during the swing phase and medial whip) have been reported. The formula for each index is shown in Table 1.
	<ol>
		<li>Calculate the raw value of the indices according to the formulas. For example, calculate the raw value of the index for hip hiking as the difference between the maximum value of the z-coordinate of the hip joint marker during the swing phase and the concurrent z-coordinate of the contralateral hip joint marker, corrected for the mean left-right difference of the z-coordinate during the double support phase.</li>
		<li>Calculate the deviation score (t-score) based on measurement data of healthy subjects. Calculate the standardized score as follows: T = 50 + 10 &#215; (X&#8722;&#181;) / &#948; (T: deviation score; X: individual data; &#181;: mean raw value of the healthy subjects; &#948;: standard deviation).</li>
	</ol>
	</li>
	<li>Analysis of Toe Clearance Strategy 
	NOTE: Strategies for toe clearance during swing vary greatly between healthy subjects and patients with lower limb paresis. In healthy subjects, toe clearance is achieved by limb shortening, with minimal movements of the pelvis or trunk. On the other hand, patients with paresis cannot shorten their limbs to the same extent. For these patients, the resulting compensatory strategies such as pelvic tilt or circumduction also affect toe clearance19. In this analysis, the height of toe clearance at mid-swing is divided into two parts: the vertical gain achieved by limb shortening and that gained by compensatory movements, which directly affect toe clearance. The components that comprise toe clearance (vertical component of limb shortening, pelvic obliquity, hip abduction, and vaulting) are calculated as outlined below.
	<ol>
		<li>Calculate total toe clearance from the z-coordinate of the fifth metatarsal head as an index of toe clearance.</li>
		<li>Calculate the vertical component of limb shortening as the z-coordinate of the change in the distance between the hip and the fifth metatarsal head.</li>
		<li>Calculate the vertical component of compensatory movement by summing three subcomponents, as follows.
		<ol>
			<li>Calculate the vertical component of pelvic obliquity as the difference in height (z-coordinate) of hip markers.</li>
			<li>Calculate the vertical component of hip abduction as the distance between the hip and the fifth metatarsal head and the abduction angles. This reflects the upward distance that the foot would have moved as a result of hip abduction if there had been no change in lower limb length.</li>
			<li>Calculate the vertical component of vaulting from the change in z-coordinate of the contralateral hip between mid-stance and mid-swing20.</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>

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S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Frontal+plane+compensatory+strategies+associated+with+self-selected+walking+speed+in+individuals+post-stroke.">Frontal plane compensatory strategies associated with self-selected walking speed in individuals post-stroke.</a> Clin Biomech. 29 (5), 518-522 (2014).</li><li>Nadeau, S., Betschart, M., Bethoux, F. <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+for+poststroke+rehabilitation:+the+relevance+of+biomechanical+analysis+and+the+impact+of+gait+speed.">Gait analysis for poststroke rehabilitation: the relevance of biomechanical analysis and the impact of gait speed.</a> Phys Med Rehabil Clin N Am. 24 (2), 265-276 (2013).</li><li>Balaban, B., Tok, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Gait+disturbances+in+patients+with+stroke.">Gait disturbances in patients with stroke.</a> PM&amp; R. 6 (7), 635-642 (2014).</li><li>Roche, N., Pradon, D., Cosson, J., Robertson, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Categorization+of+gait+patterns+in+adults+with+cerebral+palsy:+a+clustering+approach.">Categorization of gait patterns in adults with cerebral palsy: a clustering approach.</a> Gait Posture. 39 (1), 235-240 (2014).</li><li>Baker, R., Esquenazi, A., Benedetti, M. 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R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+gait+analysis+data+collection+and+reduction+technique.">A gait analysis data collection and reduction technique.</a> Hum Mov Sci. 10 (5), 575-587 (1991).</li><li>Cappozzo, A., Catani, F., Della Croce, U., Leardini, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Position+and+orientation+in+space+of+bones+during+movement:+anatomical+frame+definition+and+determination.">Position and orientation in space of bones during movement: anatomical frame definition and determination.</a> Clin Biomech. 10 (4), 171-178 (1995).</li><li>Leardini, A., Biagi, F., Merlo, A., Belvedere, C., Benedetti, M. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multi-segment+trunk+kinematics+during+locomotion+and+elementary+exercises.">Multi-segment trunk kinematics during locomotion and elementary exercises.</a> Clin Biomech. 26 (6), 562-571 (2011).</li><li>Cimolin, V., Galli, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Summary+measures+for+clinical+gait+analysis:+a+literature+review.">Summary measures for clinical gait analysis: a literature review.</a> Gait posture. 39 (4), 1005-1010 (2014).</li><li>Itoh, 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=Quantitative+assessment+of+circumduction,+hip+hiking,+and+forefoot+contact+gait+using+Lissajous+figures.">Quantitative assessment of circumduction, hip hiking, and forefoot contact gait using Lissajous figures.</a> Japanese J Compr Rehabil Sci. 3, 78-84 (2012).</li><li>Ohtsuka, K., 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=Application+of+Lissajous+overview+picture+in+treadmill+gait+analysis.">Application of Lissajous overview picture in treadmill gait analysis.</a> Japanese J Compr Rehabil Sci. 6, 33-42 (2015).</li><li>Mukaino, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Feasibility+of+a+Simplified,+Clinically+Oriented,+Three-dimensional+Gait+Analysis+System+for+the+Gait+Evaluation+of+Stroke+Patients.">Feasibility of a Simplified, Clinically Oriented, Three-dimensional Gait Analysis System for the Gait Evaluation of Stroke Patients.</a> Prog Rehabil Med. 1, (2016).</li><li>Tanikawa, H., Ohtsuka, K., Mukaino, M., Inagaki, K., Matsuda, F., Teranishi, T., 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=Quantitative+assessment+of+retropulsion+of+the+hip,+excessive+hip+external+rotation,+and+excessive+lateral+shift+of+the+trunk+over+the+unaffected+side+in+hemiplegia+using+three-dimensional+treadmill+gait+analysis.">Quantitative assessment of retropulsion of the hip, excessive hip external rotation, and excessive lateral shift of the trunk over the unaffected side in hemiplegia using three-dimensional treadmill gait analysis.</a> Top Stroke Rehabil. 23 (5), 311-317 (2016).</li><li>Hishikawa, N., Tanikawa, H., Ohtsuka, K., Mukaino, M., Inagaki, K., Matsuda, F., 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=Quantitative+assessment+of+knee+extensor+thrust,+flexed-knee+gait,+insufficient+knee+flexion+during+the+swing+phase,+and+medial+whip+in+hemiplegia+using+three-dimensional+treadmill+gait+analysis.">Quantitative assessment of knee extensor thrust, flexed-knee gait, insufficient knee flexion during the swing phase, and medial whip in hemiplegia using three-dimensional treadmill gait analysis.</a> Top Stroke Rehabil. , .</li><li>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+mechanics+of+walking+in+hemiplegia.">The mechanics of walking in hemiplegia.</a> Clin Orthop Relat Res. 63, 23-31 (1969).</li><li>Matsuda, F., Mukaino, M., Ohtsuka, K., Tanikawa, H., Tsuchiyama, K., Teranishi, T., 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=Biomechanical+factors+behind+toe+clearance+during+the+swing+phase+in+hemiparetic+patients.">Biomechanical factors behind toe clearance during the swing phase in hemiparetic patients.</a> Top Stroke Rehabil. 24 (3), 177-182 (2016).</li><li>Matsuda, F., Mukaino, M., Ohtsuka, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+strategies+used+by+hemiplegic+stroke+patients+to+achieve+toe+clearance.">Analysis of strategies used by hemiplegic stroke patients to achieve toe clearance.</a> Japanese J Compr Rehabil Sci. 7, 111-118 (2015).</li><li>Perry, J., Burnfield, J. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Gait analysis: normal and pathological function. , (1992).</li><li>Olney, S., Monga, T., Costigan, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mechanical+energy+of+walking+of+stroke+patients.">Mechanical energy of walking of stroke patients.</a> Arch Phys Med Rehabil. 67 (2), 92-98 (1986).</li></ol>

The authors have nothing to disclose.

In the current report, a simplified 3DGA method was proposed. This system was designed to be used in daily practice and involves a simplified measurement method and clinician-friendly presentation of results.
Several previous reports have used 3DGA and a basic knowledge of human gait has been previously established21. 3DGA has the potential to contribute to rehabilitation clinics, for example, by improving the understanding of the pathology of gait disorders, for use in treatment planning, or in monitoring intervention effects. However, the use of 3DGA in rehabilitation clinics remains fairly low. There are several possible barriers to the use of 3DGA in clinical settings. The time required is likely a major obstacle, as research-based 3DGA usually requires considerable preparation time (i.e., for calibration of the system and mounting of the markers). Another issue is that results interpretation can be challenging. Gait disorders usually comprise several movement abnormalities, and understanding the various graphs resulting from analysis requires experience. In terms of clinical feasibility, analysis systems with simplified methods and intuitive data presentation would be helpful.
The considerable preparation time required to perform existing analysis methods is related to the pursuit of high measurement accuracy. However, the motion speed of patients with gait disorders is limited and in daily rehabilitation practice we may not require this level of accuracy. In the current method, the protocol is simplified and can be performed in a time period that should be short enough for feasibility in daily rehabilitation practice while maintaining the requirements for evaluating patients with movement disorders13,15,16,17.
In the current method, the method of results presentation meets clinical requirements. In rehabilitation clinics, therapists generally begin by evaluating holistic gait patterns. The LOP is designed to help clinicians evaluate holistic gait patterns intuitively using a representative depiction (i.e., a figure) in which marker trajectories are placed according to actual positional relationships. The development of abnormal gait indices used herein was also based on clinical experience. Indices were developed to quantify the extent of clinically common abnormal gait patterns observed in stroke patients, and the concurrent validities of all indices have been confirmed via clinical observation by physical therapists13,15,16.
In addition to being an objective evaluation method that reflects clinical experience, the proposed method will ideally contribute to the development of new rehabilitation strategies. The analysis of toe clearance strategies goes beyond conventional clinical evaluation and has the potential to contribute to the planning of targeted rehabilitation treatments. In the proposed method and analysis, clinicians are presented with two targets for rehabilitation; the extent of toe clearance and the extent of compensation to achieve it. In itself, increasing toe clearance is important for safe walking; however, reducing compensation may also improve walking efficiency22. In the current method, clinicians would have access to both sets of information as indices of safe walking and walking efficiency, which may contribute to developing targeted rehabilitation strategies to improve the safety and efficiency of walking in rehabilitation patients.
Given the abovementioned qualities, this measurement and analysis method could facilitate the use of 3DGA in the rehabilitation clinic by providing an objective method with which to evaluate gait patterns in rehabilitation patients. Moreover, it could enable more accurate estimation of the effect of intervention than of ordinary scales used in the clinic, which could contribute to further improvement of intervention quality in the rehabilitation field.
This study was not without limitations. Considering the reduced number of markers and relatively low sampling rate, the accuracy of measurement in this system may be limited compared to existing systems. This may be a critical consideration when analyzing quick movements such as those of sports professionals. In particular, when evaluating joint angles or joint movements, the simplified marker set used in this method may be insufficient to accurately estimate joint positions. Accordingly, the analysis which emphasizes on the joint movement, such as the analysis for planning cerebral palsy surgery, could also be limited with this simplified system. Although the system was validated by the clinical evaluation, the psychometric properties of this method have not yet been defined in comparison with the gold standard method. The technical limitations should be further confirmed in future studies.
However, in patients with gait disorders, motion speed is limited and differences in performance are evident when compared with healthy subjects. Therefore, in daily practice, we may not require the level of accuracy provided by existing methods. Further, in this method, results are presented as an averaged gait pattern for a 20 s measurement period, which is longer than that of most conventional methods of measuring overground gait. This feature could enhance the accuracy and reliability of measurement.
To conclude, in this study, a simplified and intuitive 3DGA method was introduced. To facilitate the use of 3DGA in improving the quality of rehabilitation clinics, a clinically feasible measurement method should be developed. The clinician-friendly method introduced here may encourage further development of clinically feasible measurement models and the implementation of 3DGA in daily rehabilitation clinics.

Previous studies have shown the usefulness of three-dimensional gait analysis (3DGA) for the evaluation of gait after stroke1,2,3. Studies with high-quality motion analysis systems have provided substantial insight into human gait patterns, not only of those of healthy subjects but also those due to various movement disorders such as stroke or cerebral palsy4,5. Understanding pathology, assessing patients prior to treatment for planning, or monitoring intervention effects could all be promoted with 3DGA6. Further, several recent studies have demonstrated the potential of 3DGA to provide a guide for rehabilitative training7,8.
However, the use of 3DGA in daily clinical practice is still limited. One of the major issues is its time-consuming process. Marker sets commonly used in gait analysis9,10,11 consist of more than 30 markers for whole-body measurement. These marker sets enable very precise estimation of limb and trunk movement. This contributes to accuracy of the analysis, which is usually done from the data of limited number of steps that could be captured by cameras placed around a walkway. However, this requires a time-consuming preparation and measurement processes, which impedes the use of 3DGA in daily clinical practice.
Another drawback to using 3DGA in a clinical setting is that it can be difficult to interpret the results provided12. The results of 3DGA are commonly shown in graphs depicting parameters such as joint angles and displacement of body parts. However, gait evaluation in the rehabilitation clinics not only involves evaluating the movement of body parts but also holistic movement patterns. The latter can only be understood by assessing the relationships between those parameters, and the difficulty involved in doing so makes clinicians less willing to use 3DGA.
To address these problems and facilitate the use of 3DGA in the rehabilitation clinic, we propose a simplified and intuitive measurement method for 3DGA. The measurement method consists of the following: (1) a simplified marker set with 12 markers; (2) measurement of patients on the treadmill; (3) an intuitive holistic figure of gait patterns; (4) abnormal gait pattern indices validated through clinical observation; and (5) visualization of the features of gait strategy. The protocol shown in this study follows the guidelines of Medical Ethics Committee of the institution.

<table><tbody><tr><td>KinemaTracer</td><td>KisseiComtec Co., Ltd.</td><td>KinemaTracer-6Cam</td><td>A simple video-based 3D motion analysis system that consists of camera, workstation and softwares.</td></tr></tbody></table>

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.

The method presented herein is used to evaluate patients with gait disorders. The results of the analysis are presented in Figure 2, Figure 3, and Figure 4. These figures show the results of the simplified 3DGA of a patient with hemiparesis and a healthy control. Figure 2 shows a representative LOP of a stroke patient&#39;s complete gait pattern. In this patient, typical gait patterns such as circumduction, hip elevation, and trunk lateral movement were observed. Figure 3 is a radar chart showing stroke patients&#39; abnormal gait index (deviation score). Standardized scores of circumduction and hip elevation were high, indicating that those movements in stroke patients were much greater than the standard of healthy subjects. Finally, Figure 4 is a graph depicting toe clearance strategies of a stroke patient and an age-matched healthy subject. In the healthy subject, toe clearance is usually achieved by limb shortening, whereas in the stroke patient, it is achieved mainly by compensatory movements such as pelvic obliquity and vaulting.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/57063/57063fig1.jpg" /> 
Figure 1: Lissajous overview picture (LOP) consisting of three figures: (A) sagittal plane, (B) coronal plane, and (C) horizontal plane. Each trajectory shows the averaged gait-cycle movements of joint markers and hypothesized center of gravity. <a href="https://cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/57063/57063fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/57063/57063fig2.jpg" /> 
Figure 2: Lissajous overview picture (LOP) of a representative stroke patient: (A) sagittal plane, (B) coronal plane, and (C) horizontal plane. Increased trunk movement (white arrow), hip hiking (black arrow), and circumduction (gray arrow) were observed from a holistic overview using LOP. <a href="https://cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/57063/57063fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/57063/57063fig3.jpg" /> 
Figure 3: Radar chart of abnormal gait indices. The average score of healthy subjects is set to 50. A high standard score represents high abnormality. <a href="https://cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/57063/57063fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/57063/57063fig4.jpg" /> 
Figure 4: Graph showing toe clearance strategies in a stroke patient vs. a healthy subject. Toe clearance is achieved solely by limb shortening in the healthy subject, whereas compensatory movements (hip hiking, hip abduction, and vaulting) also affect toe clearance in the stroke patient. <a href="https://cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/57063/57063fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Gait patterns</td>
			<td colspan="2">Formula</td>
		</tr>
		<tr>
			<td>Hip hiking</td>
			<td colspan="2">the difference between the maximum value of the Z coordinate of the hip joint marker during the swing phase and the Z coordinate of the contralateral hip joint marker at the same time, corrected for the mean left-right difference of the Z coordinate during the double support phase</td>
		</tr>
		<tr>
			<td>Circumduction</td>
			<td colspan="2">the difference in distance between the lateral-most X coordinate of the ankle joint marker during 25 - 75 % of the swing phase and the medial-most X coordinate during 25 - 75 % of the stance phase</td>
		</tr>
		<tr>
			<td>Forefoot contact</td>
			<td colspan="2">the difference in distance between the Z coordinate of the ankle joint marker and the Z coordinate of the toe marker at initial contact, minus the difference in distance between the Z coordinates of the ankle joint marker and toe marker during standing</td>
		</tr>
		<tr>
			<td>Retropulsion of the hip</td>
			<td colspan="2">the average distance between the Y coordinate of the ankle joint and the Y coordinate of the hip joint in the single stance phase</td>
		</tr>
		<tr>
			<td>Excessive hip external rotation</td>
			<td colspan="2">the average distance between the X coordinate of the&#12288;ankle joint and the X coordinate of the toe in the swing phase</td>
		</tr>
		<tr>
			<td>Excessive lateral shift of 
			the trunk over the unaffected side</td>
			<td colspan="2">the average distance between 
			(1) the lateral most X coordinate of the midpoint between the bilateral acromions in the part of the double stance phase in which the affected leg is located behind the unaffected leg and the swing phase of affected leg&#160; and 
			(2) the average X coordinate of the midpoint between the bilateral ankle joints in the part of the double stance phase in which the affected leg is located behind the unaffected leg</td>
		</tr>
		<tr>
			<td>Knee extensor thrust</td>
			<td colspan="2">the difference between the maximum Y coordinate velocity of the knee in the single stance&#8232;phase of the affected leg and the treadmill gait speed</td>
		</tr>
		<tr>
			<td>Flexed-knee gait</td>
			<td colspan="2">the maximum knee extension angle in the single stance phase of the affected leg</td>
		</tr>
		<tr>
			<td>Insufficient knee flexion during the swing phase</td>
			<td colspan="2">the maximum knee flexion angle in the swing phase compared to the angle of knee flexion for the healthy subjects</td>
		</tr>
		<tr>
			<td>Medial whip</td>
			<td colspan="2">the distance between the lateral-most X coordinate of the ankle joint during 75 - 100 % of the stance phase and the medial-most X coordinate of the ankle joint during 25 - 75 % in the stance phase of the affected leg</td>
		</tr>
		<tr>
			<td></td>
			<td colspan="2">X, Y, and Z coordinate indicates lateromedial, anteroposteriol, and vertical, respectively</td>
		</tr>
	</tbody>
</table>
Table 1: Formulas for abnormal gait patterns

Watch this Scientific Journal Video about Clinical-oriented Three-dimensional Gait Analysis Method for Evaluating Gait Disorder at JoVE.com

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

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, ...

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Universidad San Sebastian

Research

JoVE Journal

Behavior

14.0K Views.  Fujita Health University. 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' understanding of the results.

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

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 ...

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.

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 ...

Paw-Print Analysis of Contrast-Enhanced Recordings (PrAnCER): A Low-Cost, Open-Access Automated Gait Analysis System for Assessing Motor Deficits

Gait analysis is used to quantify changes in motor function in many rodent models of disease. Despite the importance of assessing gait and motor function in many areas of research, the available commercial options have several limitations such as high cost and lack of accessible, open code. To address these issues, we developed PrAnCER, Paw-Print Analysis of Contrast-Enhanced Recordings, for automated quantification of gait. The contrast-enhanced recordings are produced by using a translucent floor that obscures objects not in contact with the surface, effectively isolating the rat&#8217;s paw prints as it walks. Using these videos, our simple software program reliably measures a variety of spatiotemporal gait parameters. To demonstrate that PrAnCER can accurately detect changes in motor function, we employed a haloperidol model of Parkinson&#8217;s disease (PD). We tested rats at two doses of haloperidol: high dose (0.30 mg/kg) and low dose (0.15 mg/kg). Haloperidol significantly increased stance duration and hind paw contact area in the low dose condition, as might be expected in a PD model. In the high dose condition, we found a similar increase in contact area but also an unexpected increase in stride length. With further research, we found that this increased stride length is consistent with the bracing-escape phenomenon commonly observed at higher doses of haloperidol. Thus, PrAnCER was able to detect both expected and unexpected changes in rodent gait patterns. Additionally, we confirmed that PrAnCER is consistent and accurate when compared with manual scoring of gait parameters.

Paw-Print Analysis of Contrast-Enhanced Recordings PrAnCER: A Low-Cost, Open-Access Automated Gait Analysis System for Assessing Motor Deficits

We describe a novel gait analysis system, Paw-Print Analysis of Contrast-Enhanced Recordings (PrAnCER), an open-access automated system for the quantification of gait characteristics in rats that utilizes a novel semitransparent floor to automatically quantify gait. This system was validated using the haloperidol model of Parkinson&#8217;s Disease.

Gait analysis is used to quantify changes in motor function in many rodent models of disease. Despite the importance of assessing gait and motor function ...

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 ...

Gait Analysis of Age-dependent Motor Impairments in Mice with Neurodegeneration

Motor behavior tests are commonly used to determine the functional relevance of a rodent model and to test newly developed treatments in these animals. Specifically, gait analysis allows recapturing disease relevant phenotypes that are observed in human patients, especially in neurodegenerative diseases that affect motor abilities such as Parkinson&#39;s disease (PD), Alzheimer&#39;s disease (AD), amyotrophic lateral sclerosis (ALS), and others. In early studies along this line, the measurement of gait parameters was laborious and depended on factors that were hard to control (e.g., running speed, continuous running). The development of ventral plane imaging (VPI) systems made it feasible to perform gait analysis at a large scale, making this method a useful tool for the assessment of motor behavior in rodents. Here, we present an in-depth protocol of how to use kinematic gait analysis to examine the age-dependent progression of motor deficits in mouse models of neurodegeneration; mouse lines with decreased levels of endophilin, in which neurodegenerative damage progressively increases with age, are used as an example.

In this study, we demonstrate the use of kinematic gait analysis based on ventral plane imaging to monitor the subtle changes in motor coordination as well as the progression of neurodegeneration with advancing age in mouse models (e.g., endophilin mutant mouse lines).

Motor behavior tests are commonly used to determine the functional relevance of a rodent model and to test newly developed treatments in these animals. ...

Developmental Biology

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

Video Movement Analysis Using Smartphones (ViMAS): A Pilot Study

The use of smartphones in clinical practice is steadily increasing with the availability of low cost/freely available &#34;apps&#34; that could be used to assess human gait. The primary aim of this manuscript is to test the concurrent validity of kinematic measures recorded by a smartphone application in comparison to a 3D motion capture system in the sagittal plane. The secondary aim was to develop a protocol for clinicians on the set up of the smartphone camera for video movement analysis.
The sagittal plane knee angle was measured during heel strike and toe off events using the smart phone app and a 3D motion-capture system in 32 healthy subjects. Three trials were performed at near (2-m) and far (4-m) smartphone camera distances. The order of the distances was randomized. Regression analysis was performed to estimate the height of the camera based on either the subject&#39;s height or leg length.
Absolute measurement errors were least during toe off (3.12 &#177; 5.44 degrees) compared to heel strike (5.81 &#177; 5.26 degrees). There were significant (p &#60; 0.05) but moderate agreements between the application and 3D motion capture measures of knee angles. There were also no significant (p &#62; 0.05) differences between the absolute measurement errors between the two camera positions. The measurement errors averaged between 3 - 5 degrees during toe off and heel strike events of the gait cycle.
The use of smartphone apps can be a useful tool in the clinic for performing gait or human movement analysis. Further studies are needed to establish the accuracy in measuring movements of the upper extremity and trunk.

Video Movement Analysis Using Smartphones ViMAS: A Pilot Study

This manuscript describes the method to test the concurrent validity of kinematic measures recorded by the smartphone application in comparison to a 3D motion capture system in the sagittal plane. This protocol will enable clinicians to set up smartphones for video capture of human movement.

The use of smartphones in clinical practice is steadily increasing with the availability of low cost/freely available &#34;apps&#34; that could be used to ...

3D Kinematic Analysis for the Functional Evaluation in the Rat Model of Sciatic Nerve Crush Injury

Compared to the Sciatic Functional Index (SFI), kinematic analysis is a more reliable and sensitive method for performing functional evaluations of sciatic nerve injury rodent models. In this protocol, we describe a novel kinematic analysis method that uses a three-dimensional (3D) motion capture apparatus for functional evaluations using a rat sciatic nerve crush injury model. First, the rat is familiarized with treadmill walking. Markers are then attached to the designated bone landmarks and the rat is made to walk on the treadmill at the desired speed. Meanwhile, the posterior limb movements of the rat are recorded using four cameras. Depending on the software used, marker tracings are created using both automatic and manual modes and the desired data are produced after subtle adjustments. This method of kinematic analysis, which uses a 3D motion capture apparatus, offers numerous advantages, including superior precision and accuracy. Many more parameters can be investigated during the comprehensive functional evaluations. This method has several shortcomings that require consideration: The system is expensive, can be complicated to operate, and may produce data deviations due to skin shifting. Nevertheless, kinematic analysis using a 3D motion capture apparatus is useful for performing functional anterior and posterior limb evaluations. In the future, this method may become increasingly useful for generating accurate assessments of various traumas and diseases.

We introduce a kinematic analysis method that uses a three-dimensional motion capture apparatus containing four cameras and data processing software for performing functional evaluations during fundamental research involving rodent models.

Compared to the Sciatic Functional Index (SFI), kinematic analysis is a more reliable and sensitive method for performing functional evaluations of ...

Neuroscience

Motor Dual-Tasks for Gait Analysis and Evaluation in Post-Stroke Patients

Eighteen stroke patients were recruited for this study involving the evaluation of cognition and walking ability and multitask gait analysis. Multitask gait analysis consisted of a single walking task (Task 0), a simple motor dual-task (water-holding, Task 1), and a complex motor dual-task (crossing obstacles, Task 2). The task of crossing obstacles was considered to be equivalent to the combination of a simple walking task and a complex motor task as it involved more nervous system, skeletal movement, and cognitive resources. To eliminate heterogeneity in the results of the gait analysis of the stroke patients, the dual-task gait cost values were calculated for various kinematic parameters. The major differences were observed in the proximal joint angles, especially in the angles of the trunk, pelvis, and hip joints, which were significantly larger in the dual motor tasks than in the single walking task. This research protocol aims to provide a basis for the clinical diagnosis of gait function and an in-depth study of motor control in stroke patients with motor control deficits through the analyses of dual-motor walking tasks.

This paper presents a protocol specifically for dual motor task gait analysis in stroke patients with motor control deficits.

Eighteen stroke patients were recruited for this study involving the evaluation of cognition and walking ability and multitask gait analysis. Multitask ...

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 ...