Name: video movement analysis using smartphones (vimas): a pilot study
Uploaded: 2017-03-14T12:30:00
Description: Watch this Scientific Journal Video about Video Movement Analysis Using Smartphones ViMAS: A Pilot Study at JoVE.com

The authors wish to thank all the participants who generously gave their time to participate in this study.

This protocol was approved by the Institutional Review Board of Wayne State University.
1. Experimental Preparation
<ol>
	<li>Position cameras to capture the entire 6-m walkway. Use a total of 4 3D motion captures cameras to capture walking over a 6-m walkway.
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		<li>Place each of the cameras at the 4 corners of the 6 m walkway. Orient each of the cameras at the diagonal ends of the walkway to face each other.</li>
	</ol>
	</li>
	<li>Collect height, weight and leg length measures of eac...

<ol>
	<li>Brunnekreef, J. J., van Uden, C. J., van Moorsel, S., Kooloos, 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=Reliability+of+videotaped+observational+gait+analysis+in+patients+with+orthopedic+impairments.">Reliability of videotaped observational gait analysis in patients with orthopedic impairments.</a> BMC Musculoskelet Disord. 6 (17), (2005).</li><li>Jette, D. U., Halbert, J., Iverson, C., Miceli, E., Shah, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Use+of+standardized+outcome+measures+in+physical+therapist+practice:+perceptions+and+applications.">Use of standardized outcome measures in physical therapist practice: perceptions and applications.</a> Phys Ther. 89 (2), 125-135 (2009).</li><li>Jette, D. U., 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=Evidence-based+practice:+beliefs,+attitudes,+knowledge,+and+behaviors+of+physical+therapists.">Evidence-based practice: beliefs, attitudes, knowledge, and behaviors of physical therapists.</a> Phys Ther. 83 (9), 786-805 (2003).</li><li>Stuberg, W. A., Colerick, V. L., Blanke, D. J., Bruce, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparison+of+a+Clinical+Gait+Analysis+Method+Using+Videography+and+Temporal-Distance+Measures+with+16-Mm+Cinematography.">Comparison of a Clinical Gait Analysis Method Using Videography and Temporal-Distance Measures with 16-Mm Cinematography.</a> Phys Ther. 68 (8), 1221-1225 (1988).</li><li>Norris, B. S., Olson, S. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Concurrent+validity+and+reliability+of+two-dimensional+video+analysis+of+hip+and+knee+joint+motion+during+mechanical+lifting.">Concurrent validity and reliability of two-dimensional video analysis of hip and knee joint motion during mechanical lifting.</a> Physiother Theory Pract. 27 (7), 521-530 (2011).</li><li>Robinson, J. L., Smidt, G. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+gait+evaluation+in+the+clinic.">Quantitative gait evaluation in the clinic.</a> Phys Ther. 61 (3), 351-353 (1981).</li><li>Krystkowiak, 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=Gait+abnormalities+induced+by+acquired+bilateral+pallidal+lesions:+a+motion+analysis+study.">Gait abnormalities induced by acquired bilateral pallidal lesions: a motion analysis study.</a> J Neurol. 253 (5), 594-600 (2006).</li><li>Grunt, S., 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=Reproducibility+and+validity+of+video+screen+measurements+of+gait+in+children+with+spastic+cerebral+palsy.">Reproducibility and validity of video screen measurements of gait in children with spastic cerebral palsy.</a> Gait Posture. 31 (4), 489-494 (2010).</li><li>Womersley, L., May, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sitting+posture+of+subjects+with+postural+backache.">Sitting posture of subjects with postural backache.</a> J Manipulative Physiol Ther. 29 (3), 213-218 (2006).</li><li>DeForge, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effect+of+4-aminopyridine+on+gait+in+ambulatory+spinal+cord+injuries:+a+double-blind,+placebo-controlled,+crossover+trial.">Effect of 4-aminopyridine on gait in ambulatory spinal cord injuries: a double-blind, placebo-controlled, crossover trial.</a> Spinal Cord. 42 (12), 674-685 (2004).</li><li>Lucareli, P. R., 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=Gait+analysis+following+treadmill+training+with+body+weight+support+versus+conventional+physical+therapy:+a+prospective+randomized+controlled+single+blind+study.">Gait analysis following treadmill training with body weight support versus conventional physical therapy: a prospective randomized controlled single blind study.</a> Spinal Cord. 49 (9), 1001-1007 (2011).</li><li>Lucareli, P. R., 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=[Gait+analysis+and+quality+of+life+evaluation+after+gait+training+in+patients+with+spinal+cord+injury].">[Gait analysis and quality of life evaluation after gait training in patients with spinal cord injury].</a> Rev Neurol. 46 (7), 406-410 (2008).</li><li>McFadyen, B. J., Swaine, B., Dumas, D., Durand, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Residual+effects+of+a+traumatic+brain+injury+on+locomotor+capacity:+a+first+study+of+spatiotemporal+patterns+during+unobstructed+and+obstructed+walking.">Residual effects of a traumatic brain injury on locomotor capacity: a first study of spatiotemporal patterns during unobstructed and obstructed walking.</a> J Head Trauma Rehabil. 18 (6), 512-525 (2003).</li><li>Shin, J. C., Yoo, J. H., Jung, T. H., Goo, H. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparison+of+lower+extremity+motor+score+parameters+for+patients+with+motor+incomplete+spinal+cord+injury+using+gait+parameters.">Comparison of lower extremity motor score parameters for patients with motor incomplete spinal cord injury using gait parameters.</a> Spinal Cord. 49 (4), 529-533 (2011).</li><li>Reid, S., Held, J. M., Lawrence, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Reliability+and+Validity+of+the+Shaw+Gait+Assessment+Tool+for+Temporospatial+Gait+Assessment+in+People+With+Hemiparesis.">Reliability and Validity of the Shaw Gait Assessment Tool for Temporospatial Gait Assessment in People With Hemiparesis.</a> Arch Phys Med Rehabil. 92 (7), 1060-1065 (2011).</li><li>Stokic, D. S., Horn, T. S., Ramshur, J. M., Chow, J. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Agreement+Between+Temporospatial+Gait+Parameters+of+an+Electronic+Walkway+and+a+Motion+Capture+System+in+Healthy+and+Chronic+Stroke+Populations.">Agreement Between Temporospatial Gait Parameters of an Electronic Walkway and a Motion Capture System in Healthy and Chronic Stroke Populations.</a> Am J Phys Med Rehabil. 88 (6), 437-444 (2009).</li><li>Arazpour, 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=Evaluation+of+a+novel+powered+hip+orthosis+for+walking+by+a+spinal+cord+injury+patient:+a+single+case+study.">Evaluation of a novel powered hip orthosis for walking by a spinal cord injury patient: a single case study.</a> J. Prosthet. Orthot. Int. 36 (1), 105-112 (2012).</li><li>Prado-Medeiros, C. L., 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=Effects+of+the+addition+of+functional+electrical+stimulation+to+ground+level+gait+training+with+body+weight+support+after+chronic+stroke.">Effects of the addition of functional electrical stimulation to ground level gait training with body weight support after chronic stroke.</a> Revista Brasileira De Fisioterapia. 15 (6), 436-444 (2011).</li><li>Sousa, C. O., Barela, J. A., Prado-Medeiros, C. L., Salvini, T. F., Barela, A. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Gait+training+with+partial+body+weight+support+during+overground+walking+for+individuals+with+chronic+stroke:+a+pilot+study.">Gait training with partial body weight support during overground walking for individuals with chronic stroke: a pilot study.</a> J Neuroeng Rehabil. 8 (48), (2011).</li><li>Krebs, D. E., Edelstein, J. E., Fishman, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Reliability+of+observational+kinamatic+gait+analysis.">Reliability of observational kinamatic gait analysis.</a> J Am Phys Ther Assoc. 65, 1027-1033 (1995).</li><li>Martin, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=More+than+half+of+MDs+under+age+35+now+using+PDAs.">More than half of MDs under age 35 now using PDAs.</a> Can. Med. Assoc. J. 169 (9), 952 (2003).</li><li>Mosa, A. M., Yoo, I., Sheets, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Systematic+Review+of+Healthcare+Applications+for+Smartphones.">A Systematic Review of Healthcare Applications for Smartphones.</a> BMC Med Inform Decis Mak. 12, (2012).</li><li>Ferriero, G., 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=Reliability+of+a+smartphone-based+goniometer+for+knee+joint+goniometry.">Reliability of a smartphone-based goniometer for knee joint goniometry.</a> Int J Rehabil Res. 36 (2), 146-151 (2013).</li><li>Vohralik, S. L., Bowen, A. R., Burns, J., Hiller, C. E., Nightingale, E. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Reliability+and+validity+of+a+smartphone+app+to+measure+joint+range.">Reliability and validity of a smartphone app to measure joint range.</a> Am J Phys Med Rehabil. 94 (4), 325-330 (2015).</li><li>Scholtes, S. S., Gretchen, <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ability+to+detect+change+in+single+leg+squat+movement+patterns+following+instruction+in+females+with+patellofemoral+pain+using+2D+motion+analysis+methods.">Ability to detect change in single leg squat movement patterns following instruction in females with patellofemoral pain using 2D motion analysis methods.</a> Combined Sections Meeting. , (2014).</li><li>Eltoukhy, M. A., Asfour, S., Thompson, C., Latta, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluation+of+the+performance+of+digital+video+analysis+of+human+motion:+dartfish+tracking+system.">Evaluation of the performance of digital video analysis of human motion: dartfish tracking system.</a> IJSER. 3 (3), 1-6 (2012).</li><li>Boone, D. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Reliability+of+goniometric+measurements.">Reliability of goniometric measurements.</a> Phys Ther. 58 (11), 1355-1360 (1978).</li><li>Bovens, A. M., van Baak, M. A., Vrencken, J. G., Wijnen, J. A., Verstappen, F. 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The purpose of this validation study was to determine the validity of a freely available smartphone application in order to be clinically used as an objective and cost effective means of using smartphone technology for kinematic gait analysis in the clinical setting. Existing validation studies that examined kinematic measures with a smartphone application are limited and have not assessed dynamic kinematic measures recorded during gait in the sagittal plane. This validation study is the first to have examined kinematic ...

Assessment of human gait is a key component of the physical therapy evaluation and clinical decision-making process.1 Gait assessment is a frequently used clinical tool to assess gait deficits in patients with neurological and musculoskeletal deficits. Reassessment of gait can then provide the clinician with information about the efficacy of an intervention in achieving the goals they had set at their initial evaluation. There is a nationally recognized need in the United States for physical therapists to utilize standardized outcome measurements when evaluating patients.2 This need stems from the rapidly changing landscape of insurance reimbursement policies, as well as an emphasized shift for physical therapists to rely more heavily on evidence based practices.3 There are numerous outcome measures to assess different aspects of gait, which can be observed in a number of ways including: visual observation by a clinician, functional assessments, video recorded measures, electronic walkways, three-dimensional motion analysis software, etc. In clinical settings, observational (visual) gait analysis is commonly performed, as it requires minimal equipment and time.
While observational gait analysis is commonly used within the clinic, it still remains a subjective assessment.4 Therefore, factors such as therapist experience, visual acuity, distance from the subject (camera distance), measurement tools, and any other such factors can introduce variability and error in the assessment. The potential for such variability presents a critical need for a more reliable means of measurement, which can ultimately be overcome by the use of valid instrumentation.5
Since its inception, videography and related technology has been used to examine various functional limitations resulting from impaired movement capability as well as a form of visual feedback. This is acutely true in regards to gait assessment. Stuberg et al. found that &#34;videography equipment is commonly available in the clinic&#8230;and provides the clinician with additional objective information on posture and joint position during the gait cycle.&#34;4 As technology has continued to improve, so have the capabilities of video analysis. These capabilities provide the physical therapist with greater ability to clinically assess the various parameters of gait.
The two key parameters that physical therapists focus on include kinematic and spatiotemporal parameters. As the name implies, spatiotemporal measures involve elements of distance and time. Specific to a gait cycle, spatiotemporal measures would include, but not be limited to, stride length, step length, cadence, and velocity.6 Kinematic measures on the other hand focus on the joint movements/rotations of the lower extremities observed during each gait cycle.
A number of peer-reviewed articles have been published that have cited the use of video motion analysis as an outcome measure, specifically 2D camera systems, to assess kinematic, spatiotemporal, or a combination of both types of parameters. These articles have evaluated various clinical populations including individuals with a history of a stroke (CVA), traumatic brain injuries (TBI), spinal cord injuries (SCI), Parkinson&#39;s disease (PD), cerebral palsy (CP), and healthy individuals. The schematic presented below (Figure 1) provides the framework that was adopted to identify relevant peer-reviewed literature that has been published on this topic.
<img alt="Figure 1" src="/files/ftp_upload/54659/54659fig1.jpg" /> 
Figure 1. Schematic for Article Selection Criteria. The schematic outlines the steps used in choosing peer-reviewed articles to ascertain the type of variables that were reported in gait analysis. <a href="http://cloudflare.jove.com/files/ftp_upload/54659/54659fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
The majority of the research studies that have used video motion analysis for recording gait parameters were validation studies. Kinematic validation studies can be further broken down into one of three categories: assessing abnormal motion resulting from a specific diagnosis/pathology,7 examining joint angles during specific functional motions,8,9 and evaluating the effectiveness of treatment via comparison of pre-intervention motion and post-intervention motion.10,11 Similarly, research studies assessing spatiotemporal parameters can also be broken down into three categories: assessment of abnormal motion resulting from a specific pathology,12,13,14 examination of a platform during a specific functional activity,15,16 and determination of the effect of a specific intervention.17 The research studies that evaluated both kinematic and spatiotemporal parameters were primarily aimed at determining the effectiveness of specific treatment interventions such as orthoses 17 or body weight/partial body weight supported treadmill training.18,19 A preliminary descriptive analysis of these articles determined that 52.1% of the studies (the sum of those looking solely at kinematics (30.4%) and those that examined a combination of parameters (21.7%)) researched kinematic parameters with a 2D camera system. This is in comparison to the 69.5% of the articles (sum of articles that researched spatiotemporal parameters (47.8%) and a combination of parameters (21.7%)) that assessed spatiotemporal parameters.
The methodological differences in recording and assessing kinematic and spatiotemporal gait parameters are also seen in clinical practice in terms of the type of observational gait analysis being used. Spatiotemporal parameters are assessed with much greater frequency as indicated by the research. There are three generally agreed upon reasons for this trend: low cost, ease of use, and the existence of a standard protocol to measure such parameters. Observational kinematic measurements have been shown to have very low intra-rater (60%) and inter-rater reliability (40% - 94%) in clinical settings.4 This wide range is understood to be due to the variation in the placement of markers on bony landmarks and the specific tools used to assess joint angles. Minute differences in location placement of the markers can significantly alter the resultant angles. Spatiotemporal measurements have much higher reliability (ranging 69% - 97%), especially when using the paper, pencil and stop clock method to assess gait.20
The technological advances in the last few decades have significantly changed the way healthcare is practiced. With the recent emergence of smartphones, access to the Internet, online research articles, and other electronic resources are now more readily available to clinicians at any time. Martin et al. reported that &#34;general use of smartphones is increasing in clinical practice, medical education and research.&#34;21 In this study, more than 50% of medical doctors under the age of 35 responded that they have implemented using a smartphone in clinical practice. This trend increased in 2009 when 64% of physicians in the United States were found to be using smartphones in their clinical practice. The Manhattan Review study further predicted that this growth would continue to climb to 81% of physicians and healthcare clinicians implementing smartphone usage in clinical practice by 2012.22 While further research has not been conducted to determine if this upward trend has indeed continued to climb, it is reasonable to assume, with the known implementation of technology in healthcare, that the use of smartphone platforms in clinical practice will become more commonplace.
The current use of smartphone applications in physical therapy practice has not been established. There have been no studies evaluating the use of smartphone video analysis applications by a physical therapist to date. However, various smartphone applications have been used by individual physical therapists as a breakthrough assistive tool in outpatient orthopedic settings for use in both rehabilitating and training athletes of various disciplines. Smartphone apps are also available that can measure joint angles, some of which have been validated.23,24 Individual therapists have begun using various analysis applications on smartphones for visual feedback for the patient and for easier breakdown of various components that may be lacking in a patient&#39;s gait cycle, based on anecdotal evidence. However, the validity of these measures remains unknown. The limited research that does exist regarding these smartphone video analysis applications has focused on the validation of kinematic gait parameters, specifically ankle, knee and hip angles, in the frontal plane,25 and inter-rater reliability of the device.26 There are no studies to date that have validated the use of smartphone video analysis applications to record kinematics of gait in the sagittal plane, which is most commonly performed in clinical gait analysis.
The purpose of this study was to test the concurrent validity of kinematic measures recorded by the smartphone application and compare them to measures recorded by a 3D motion capture system in the sagittal plane. We predict that there will be no significant differences between the measures recorded by the smartphone application when compared to the measures recorded by the 3D motion capture system. The secondary purpose is to test if two distinct placements of the smartphone camera from the subject (near distance of 2-m; far distance of 4 -nt difference in measures between the two distinct placements of the smartphone camera. The final purpose of the study is to draft a protocol for clinical video gait analysis using a smartphone application.

<table border="0" cellpadding="0" cellspacing="0" width="655">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:247px;">Hudl Technique App</td>
			<td style="width:81px;">Hudl&#160;</td>
			<td style="width:136px;">Online app</td>
			<td style="width:191px;">Freely downladable app from adroid /apple store</td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:247px;">Optotrak Certus 3D motion capture system</td>
			<td style="width:81px;">Northern Digital inc</td>
			<td style="width:136px;">Optotrak certus System</td>
			<td>http://www.ndigital.com/msci/products/optotrak-certus/</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:247px;">Smartphone</td>
			<td style="width:81px;">Apple</td>
			<td style="width:136px;">Iphone 5</td>
			<td>www.apple.com</td>
		</tr>
	</tbody>
</table>

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.

All 32 subjects completed the 6 walking trials; however, data from 6 of the participants were not included in the data analysis due to technical problems resulting in poor marker visibility. The absolute measurement errors of knee angles were least during toe off events (3.12 &#177; 5.44 degrees) compared to heel strike (5.81 &#177; 5.26 degrees) (Table 1b). There were no statistically significant agreements (P &#62; 0.05) between the smartphone application and 3D motion ...

Watch this Scientific Journal Video about Video Movement Analysis Using Smartphones ViMAS: A Pilot Study at JoVE.com

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.

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 ...

The overall goal of this study is to test the concurrent validity of kinematic measures recorded by the smart phone application, and compare them to measures recorded by a 3D motion capture system, in order to develop a valid clinical protocol. This clinical protocol has been developed, so that the smartphone can be used to capture human movement, and provide valid kinematic measurements, using a simple and user-friendly set-up. The main advantage of this technique is that the smartphone can be set up in a clinic or a patient's home, for video analysis of human movement.Visual demonstration of this method is critical, because clinicians can follow the step-by-step clinical protocol, in order to obtain valid measures of lower extremity kinematics. Demonstrating the procedure will be graduate students, who are coauthors in the study. Begin by measuring and marking off a six-meter walkway, using measuring tape and sticky tape.Then place four 3D motion capture cameras at the four corners of the six-meter walkway, to record walking in this area. Orient each of the cameras at the diagonal ends of the walkway to face each other. Next, escort the participant into the testing area, and collect weight and leg length, from the greater trochanter to the medial malleoli of both legs with a measuring tape.Then measure the height by having the participant stand barefoot next to a measuring tape, attached to the wall. Place a ruler on top of the participant's head to read the measurement from the measuring tape adhered to the wall. Mount the smart phone on a tripod, using an adapter clip to hold the smart phone.Place the tripod perpendicular to the center of the walkway, at 2.0 meters away from the first setted trial. Note the tripod should be placed at 4.0 meters away for the second set of trials. Then calculate the height from the floor to the camera lens in meters for each configuration, using the patient's leg length.The near camera position, two meters, is for recording and analyzing only the lower extremity movement whereas the far distance covers both lower extremity and trunk. Next, place clusters of three smart markers with velcro straps on the bilateral anterior superior iliac crest or ASIS, upper one-third of the lateral aspect of the thighs, upper one-third of the lateral aspect of the calves, and the dorsum of both feet. Place a single smart marker on the midline between the right and left posterior superior iliac spines.Place stickers indicating bony landmarks of the bilateral medial and lateral femoral condyles, medial and lateral malleoli, and the webbed space between first and second toes for calibration of the 3D motion capture system. Finally, calibrate the equipment using an instrumented wand with smart markers on it, to register the 3D location of the stickers. To begin, have one investigator operate the smartphone, and the other operating the computer that controls the 3D motion capture system.Ask the participant to complete a practice trial. Then, open the smartphone application and press the red record button on the bottom center of the screen to begin recording. Use numbered paper to indicate trial number on the smartphone recording.Then, instruct the participant to walk at their normal pace, and to focus on a marker placed on the opposite wall to assist in walking in a straight line. Give the participant a countdown to start by saying three, two, one, go. Then, have the participant cross the first two 3D motion capture cameras placed at the beginning of the walkway on either side, and walk towards another two cameras placed at the other end of the walkway on either side.After the subject finishes walking the six meter distance, countdown to the end of the trial by saying three, two, one, stop. Then press the red record button once more to stop recording the walking trial. Check all markers for position after each trial.Next, move the tripod with the smartphone to the second distance four meters away to capture the upper and lower body. Ask the participant to stand on the midpoint of the walkway, then start walking in the same manner as before. Finally, save and verify the 3D motion capture recordings and smartphone recordings.Then remove the smart markers. Begin by manually recording the knee angle that is displayed on the screen at the heel strike and toe off phases of the gait cycle. Then, complete the analysis of smart phone recordings for heel strike and toe off events.Use the stylus for increased accuracy of landmark placement for knee angle measurements. Next, view that was just recorded by selecting the video square in the bottom left corner of the screen. Use the scrollbar at the base of the screen to select the frame in which the subject is closest to heel strike or toe off in the center of the screen.Then, to drop in the angle, tap on the white outline pencil icon on the upper right side of the screen. Select the angle option in the drop down menu. Choose a preferred color and the angle marker.Slide or tap the stylus anywhere on the screen to drop in the angle. Finally, place the center of the angle on the knee joint, with the vectors reaching upwards along the femur and downwards towards the lateral malleoli. If needed, zoom in by placing two fingers close together in the center of the screen and slowly drawing them apart from one another.Based on the results, there was a significant difference between the angle measurements by the 3D motion capture system and smartphone application. The plots for the 4.0 meter and the 2.0 meter distances displayed data that are more scattered around the mean difference line in the center. This indicates that the camera position did not contribute to the errors in measurements.While attempting the clinical protocol for smartphone video movement analysis, it's important to remember that the camera must be placed at the set distance and the height of the camera is determined by the individual's leg length.

Research

JoVE Journal

Medicine

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