This work lies within the multidisciplinary Southampton Musculoskeletal Research Unit (Southampton University Hospitals Trust/University of Southampton) and the Arthritis Research UK Centre for Sport, Exercise and Osteoarthritis. The authors wish to thank their funding sources; Arthritis Research UK for funding of laboratory equipment (Grant No: 18512) and Vicon Motion System, Oxford UK for providing funding for a PhD studentship (M.Warner). The authors also wish to thank the participants, and Kate Scott and Lindsay Pringle for their help with participant recruitment.

NOTE: The use of human participants was approved by the Faculty of Health Sciences Ethics Committee at the University of Southampton. All participants signed consent forms before data collection commenced. For the data presented in this study kinematics were recorded using a passive marker motion capture system consisting of 12 cameras; six 4-megapixel cameras and six 16-megapixel cameras operating at sampling frequency of 120 Hz.
1. Participant Preparation
<ol>
	<li>Ask subjects to remove their upper body clothing or to wear a sports bra, vest, or strapless top. It is important that clothing does not interfere with the movement of the markers or occlude markers from the view of the cameras.</li>
	<li>Construct an acromion marker cluster consisting of an &#8216;L&#8217; shaped piece of plastic 70 mm in length along each aspect. Attach three retroreflective markers to the AMC, one on the end of each end of each aspect and one where each aspect meet (Figure 1).</li>
	<li>Attach the acromion marker cluster (AMC) onto the posterior portion of the acromion where the acromion meets the scapular spine, using double sided adhesive tape. One aspect of the plate should follow the spine of the scapula pointing medially, the other should point anterior to the scapular plane (Figure 1).</li>
	<li>Attach a cluster marker set to the upper arm using straps (Figure 2).</li>
	<li>Attach retroreflective markers to the following anatomical landmarks at recommended by the International Society of Biomechanics33 (Figures 1 &#38; 2): Sternal notch (IJ; Deepest joint of the sternal notch), Xiphoid process (PX; Most caudal point on the sternum), C7 (Spinous process of the C7 vertebra), T8 (Spinous process of the T8 vertebra), Sternoclavicular joint (SC; Most ventral point on the sternoclavicular joint), Radial styloid (Most caudal point on the radial styloid), and Ulnar styloid (Most caudal point on the ulnar styloid).</li>
</ol>
<img alt="Figure 1" src="/files/ftp_upload/51717/51717fig1highres.jpg" /> 
Figure 1: Position of the acromion marker cluster, C7 and T8 anatomical markers. This figure has been modified from Warner, M. B., Chappell, P. H. &#38; Stokes, M. J. Measuring scapular kinematics during arm lowering using the acromion marker cluster. Hum. Mov. Sci. 31, 386-396, doi:http://dx.doi.org/10.1016/j.humov.2011.07.004 (2012).
<img alt="Figure 2" src="/files/ftp_upload/51717/51717fig2highres.jpg" /> 
Figure 2: Marker locations for the sternal notch (IJ), xiphoid process (PX), sternoclavicular (SC), upper arm cluster, ulnar styloid (US), radial styloid (RS).
2. Participant Calibration
NOTE: Locations of the scapula&#8217;s anatomical landmarks need to be determined with respect to the acromion marker cluster. Calibration of the landmarks is required for each participant.
<ol>
	<li>Construct a calibration wand consisting of four reflective markers placed into a &#8216;T&#8217; formation (Figure 3). Measure the distance from the tip of the calibration wand to the first wand marker.</li>
	<li>Palpate and locate the following anatomical landmarks as recommended by the International Society of Biomechanics33. Place the tip of the calibration wand on the landmark (Figure 3). Capture three seconds of data with the motion capture system ensuring the markers on the wand, the AMC and upper arm cluster are all visible to the cameras.
	<ol>
		<li>Acromioclavicular joint (AC) &#8212; Place a hand on the clavicle, then move laterally until the point where the clavicle reaches the acromion. Place the tip of the wand at the joint between the clavicle and acromion.</li>
		<li>Acromion angle (AA) &#8212; Palpate along the spine of the scapula to the most lateral point. Place the tip of the wand on the dorsal aspect of the acromion at the most lateral point (Figure 3).</li>
		<li>Medial spine of the scapula (TS) &#8212; Palpate along the spine of the scapula to the most medial point. Place the tip of the wand at the point where the spine meets the medial border of the scapula.</li>
		<li>Inferior angle of the scapula (AI) &#8212; Palpate inferiorly along the medial border of the scapula. Place the tip of the wand on the most caudal point of the scapula.</li>
		<li>Medial epicondyle (EM) &#8212; With the participant&#8217;s elbow in 90&#176; of flexion pointing forward, with their thumb pointing upwards, place a hand on the medial side of the elbow to locate the medial epicondyle. Place the tip of the wand on the most caudal point of the medial epicondyle.</li>
		<li>Lateral epicondyles (EL) &#8212; With the participant&#8217;s elbow in 90&#176; of flexion pointing forward, with their thumb pointing upwards, place a hand on the lateral side of the elbow to locate the lateral epicondyle. Place the tip of the wand on the most caudal point of the lateral epicondyle.</li>
	</ol>
	</li>
	<li>To determine the glenohumeral joint center, ask the participant to perform a circumduction movement with their upper arm with the elbow fully extended, from zero degrees arm elevation to approximately 40&#176; arm elevation. They must perform this movement whilst aiming to minimize protraction/retraction and elevation/depression of the shoulder complex; the investigator can provide assistance if necessary. Record this movement for approximately 30 sec.</li>
</ol>
<img alt="Figure 3" src="/files/ftp_upload/51717/51717fig3highres.jpg" /> 
Figure 3: Calibration wand used to locate anatomical bony landmark with respect the acromion marker cluster (AMC).
3. Experiment Protocol
<ol>
	<li>Ask participant to perform arm elevation from zero to 120&#176; arm elevation, and then lower their arm back down to rest by their side in the sagittal, frontal and scapular plane. The scapular plane is approximately 40&#176; anterior to the frontal plane.</li>
</ol>
4. Post-processing of Kinematic Data
NOTE: The following steps detail the procedure needed to calculate scapular kinematics during the dynamic movement trials. These steps have been described and explored extensively within the literature21,33,34 and the purpose of the following section is to provide a synthesis and step-by-step guide to implementing the modeling steps required to obtain scapular kinematics. The application of these steps is conducted in relevant kinematic modeling software. The software contains commands to enable the creation of local coordinate systems, the conversion of coordinates from a global to local coordinate system, the conversion of coordinates from local to global coordinate systems and the calculation of Euler angle rotations. These steps will allow the scapula, humerus and thorax to be defined as rigid bodies. Subsequently rotation of the scapula with respect the thorax, and the humerus with respect thorax can then be determined.
<ol>
	<li>Using the coordinates of markers on the AMC, define an arbitrary local coordinate system for the AMC (Figure 4a). For each scapular anatomical landmark calibration trial, determine the location of the tip of the wand, which represents the location of the anatomical landmark, with respect the local coordinate system on the AMC using the following steps. 
	NOTE: Kinematic modeling software contain commands to enable the creation of local coordinate systems and conversion of coordinates from a global to a local coordinates, see Figure 4 for example commands.
	<ol>
		<li>Use the markers on the wand to create a local coordinate system for the wand (Figure 4a) using the following command in the kinematic modeling software: AMC= [AMCO,AMCA-AMCO,AMCO-AMCM,xyz] where AMCO, AMCA and AMCM are the labels given to the markers on the AMC.</li>
		<li>Using the kinematic modeling software, calculate the location of the tip of the wand in the global coordinate system. In the example provided this is 83 mm from the marker 1 (M1) along the X axis of the wand (Figure 4b); use the command: Wand = [M1,M1-M2,M3-M4,xyz] and Wandtip = M1+{83,0,0}*ATTITUDE(Wand) where M1, M2, M3 and M4 are the labels given to the markers on the wand.</li>
		<li>Determine the location of the tip of the wand with respect to the local coordinate system of the AMC ($%AA) (Figure 4c) using the modeling commands: $%AA = WandTip/AMC and PARAM($%AA).</li>
		<li>Repeat steps 4.1.1 to 4.1.3 for each scapular anatomical landmark.</li>
		<li>Determine the location of the medial and lateral epicondyles with respect to the humerus marker cluster, instead of the AMC, using the using the above steps.</li>
	</ol>
	</li>
	<li>Use the dynamic calibration trial to calculate the location of the glenohumeral joint center with respect to the scapula. Calculate the position of the glenohumeral joint center, with respect to the scapula, as the pivot point of the helical axis between the humerus and scapula. For more details on this technique refer to Veeger35.</li>
	<li>Calculate the elbow joint center (ELJC) as the mid-distance between the lateral (EL) and medial epicondyles (EM) of the humerus; ELJC = (EM + EL) / 2.</li>
	<li>During the dynamic trials, use the known position of the anatomical landmarks with respect to the AMC to determine the location of the anatomical landmarks within the global coordinate system (Figure 5). 
	NOTE: Modeling software contain commands to enable conversion of coordinates from local coordinate systems to global coordinate systems, see Figure 5 for example commands.
	<ol>
		<li>Refer to Figure 5a that shows the location of the acromion angle landmark with respect to the AMC ($%AA) as described in point 4.1.</li>
		<li>Convert the location of $%AA virtual marker to the global coordinate system for each time point during the dynamic trial to create the acromion angle (AA) landmark (Figure 5b) using the following kinematic modeling command: AA = $%AA*AMC and OUTPUT(AA).</li>
		<li>Repeat steps 4.4.2 for each anatomical landmark.</li>
	</ol>
	</li>
	<li>Define a local coordinate system for the thorax and scapula by calculating the unit vectors between the relevant markers to represent each axis for a given rigid body using the following kinematic modeling command: Scapula = [AA,TS-AA,AA-AI,zxy]. Thorax = [IJ,MUTHX-MLTHX,IJ-C7,yzx], where MUTHX is the mid-point between the IJ and C7 landmark and MLTHX is the mid-point between the PX and T8 landmarks. 
	NOTE: The axes definition are based on International Society of Biomechanics&#8217; (ISB) recommendations33 (Table 1 and Figure 6).
	<ol>
		<li>Using a similar method, define a local coordinate system for the humerus using &#8216;Option 2&#8217; as recommended by the ISB33. 
		NOTE: Option 2 requires a sufficient plane formed by the gleohumeral joint center, elbow joint center and the ulna styloid, i.e. a degree of elbow flexion is required. If the participant approaches full elbow extension, the humeral axes may become unstable and therefore &#8216;Option 1&#8217; should be used (Table 1). See Wu et al. (2005) for further details.</li>
	</ol>
	</li>
	<li>Determine the orientation of the scapula relative to the thorax for each time point during the dynamic trial using the Euler angle decomposition method with a rotation sequence of internal rotation (Y), upward rotation (X&#8217;) and posterior tilt (Z&#8217;&#8217;)33 using the following kinematic modeling command: ScapularKin = -&#60;Thorax,Scapula,yxz&#62; (Figure 7).</li>
	<li>Determine the orientation of the humerus with respect to the thorax during the dynamic trial using a non-cardan rotation sequence of Y (plane of elevation), X&#8217; (elevation) and Y&#8217;&#8217; (axial rotation)36 using relevant kinematic modeling software. 
	NOTE: A macro is available to download from the manufacturer in order to determine non-cardan rotation sequences within the kinematic modeling software used in this manuscript.</li>
</ol>
<img alt="Table 1" fo:content-width="6in" src="/files/ftp_upload/51717/51717table1.jpg" width="600" /> 
MUTHX = mid-point between IJ and C7. MLTHX = mid-point between PX and T8. GH = glenohumeral joint center. ELJC = elbow joint center.
Mathematical operators:
^ = cross product of two vectors
|| = absolute value of a vector
Table 1: Local coordinate system for each rigid segment.
5. Data Reduction and Analysis
NOTE: The following data reduction and analysis steps are performed in numerical modeling software (such as MATLAB) that allows manipulation of data matrices. The kinematic data is divided into the elevation and lowering phases of humeral movement, time normalized for each phase of movement, then scapular kinematics are expressed relative to humeral elevation angle.
<ol>
	<li>Determine the elevation and lowering phase of the humeral elevation as described below (Figure 8). These phases are determined from the angular velocity of the humeral elevation angle (Figure 8). See ElevationLoweringPhases.m function file.
	<ol>
		<li>Determine the start of humeral elevation when the angular velocity of the humerus exceeds a threshold 2% of the maximal humeral angular velocity.</li>
		<li>Determine the end of the elevation phase as the point at which the humeral angular velocity falls below 2% of the maximal humeral angular velocity, or when humeral elevation exceeds 120&#176;.</li>
		<li>Determine the start of the humeral lowering phase when the angular velocity falls below 2% of the minimum angular velocity, or the point at which humeral elevation falls below 120&#176;.</li>
		<li>Determine the end of the lowering phase when the angular velocity exceeds 2% of the minimum angular velocity.</li>
	</ol>
	</li>
	<li>Normalize the data by interpolating the kinematic data in each phase of movement to 101 data points (Figure 9). See Time_normalisation.m function file.</li>
	<li>Express scapular kinematics in relation to humeral elevation by plotting the arm angle (degrees) vs. upward rotation (degrees) (Figure 10). See PlotScapHumRhythm.m function file.</li>
</ol>

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J. <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+attachment+position+and+shoulder+orientation+during+calibration+on+the+accuracy+of+the+acromial+tracker.">Effects of attachment position and shoulder orientation during calibration on the accuracy of the acromial tracker.</a> J. Biomech. 44, 1410-1413 (2011).</li><li>Prinold, J. A. I., Shaheen, A. F., Bull, A. M. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Skin-fixed+scapula+trackers:+A+comparison+of+two+dynamic+methods+across+a+range+of+calibration+positions.">Skin-fixed scapula trackers: A comparison of two dynamic methods across a range of calibration positions.</a> J. Biomech. 44, 2004-2007 (2011).</li><li>Wu, 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=ISB+recommendation+on+definitions+of+joint+coordinate+systems+of+the+various+joints+for+the+reporting+of+human+joint+motion+-+Part+II:+shoulder,+elbow,+wrist+and+hand.">ISB recommendation on definitions of joint coordinate systems of the various joints for the reporting of human joint motion - Part II: shoulder, elbow, wrist and hand.</a> J. Biomech. 38, 981-992 (2005).</li><li>Karduna, A. R., McClure, P. W., Michener, L. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Scapular+kinematics:+effects+of+altering+the+Euler+angle+sequence+of+rotations.">Scapular kinematics: effects of altering the Euler angle sequence of rotations.</a> J. Biomech. 33, 1063-1068 (2000).</li><li>Veeger, H. 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=The+position+of+the+rotation+center+of+the+glenohumeral+joint.">The position of the rotation center of the glenohumeral joint.</a> J. Biomech. 33, 1711-1715 (2000).</li><li>Doorenbosch, C. A. M., Harlaar, J., Veeger, H. 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=The+globe+system:+an+unambiguous+description+of+shoulder+positions+in+daily+life+movements.">The globe system: an unambiguous description of shoulder positions in daily life movements.</a> J. Rehabil. Res. Dev. 40, 147-156 (2003).</li><li>Kadaba, M. 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=Repeatability+of+kinematic,+kinetic,+and+electromyographic+data+in+normal+adult+gait.">Repeatability of kinematic, kinetic, and electromyographic data in normal adult gait.</a> Journal of Orthopaedic Research. 7, 849-860 (1989).</li><li>Schwartz, M. H., Trost, J. P., Wervey, R. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measurement+and+management+of+errors+in+quantitative+gait+data.">Measurement and management of errors in quantitative gait data.</a> Gait and Posture. 20, 196-203 (2004).</li><li>Jaspers, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+reliability+of+upper+limb+kinematics+in+children+with+hemiplegic+cerebral+palsy.">The reliability of upper limb kinematics in children with hemiplegic cerebral palsy.</a> Gait and Posture. 33, 568-575 (2011).</li><li>Thigpen, C. A., Gross, M. T., Karas, S. G., Garrett, W. E., Yu, 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+repeatability+of+scapular+rotations+across+three+planes+of+humeral+elevation.">The repeatability of scapular rotations across three planes of humeral elevation.</a> Research in Sports Medicine. 13, 181-198 (2005).</li><li>Groot, J. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+variability+of+shoulder+motions+recorded+by+means+of+palpation.">The variability of shoulder motions recorded by means of palpation.</a> Clinical Biomechanics. 12, 461-472 (1997).</li></ol>

None of the authors had any affiliation with any organization that could influence the outcome of this work.

The choice of methodology for determining scapular kinematics is crucial, and consideration of the validity, reliability and its appropriateness for the research study should be given. Various methods have been adopted throughout the literature but each method has its limitations. The acromion marker cluster overcomes a number of these limitations, such as projection errors from 2D imaging or requiring repeated interpretation of the location of the scapula by providing non-invasive dynamic kinematic measurement of the sc...

Objective, quantitative measurement of scapular kinematics can provide an assessment of abnormal movement patterns associated with shoulder dysfunction1, such as reduced upward rotation and posterior tilt during arm elevation observed in shoulder impingement2-8. Measurement of scapular kinematics, however, is difficult due to the bone&#8217;s deep position and gliding nature beneath the skin surface1. Typical kinematic measurement techniques of attaching reflective markers over anatomical landmarks do not adequately track the scapula as it glides beneath the skin surface9. Various methods have been adopted throughout the literature to overcome these difficulties, including; imaging (X-ray or magnetic resonance)10-14, goniometers15,16, bone pins17-22, manual palpation23,24, and the acromion method3,5,19,25. Each method, however, has its limitations which include: exposure to radiation, projection errors in the case of two-dimensional image based analysis, require repeated subjective interpretation of the location of the scapula, are static in nature or are highly invasive (e.g. bone pins).
A solution to overcome some of these difficulties is to employ the acromion method where an electromagnetic sensor is attached to the flat portion of the acromion25, a flat portion of bone which extends anteriorly at the most lateral part of the scapula leading from the spine of the scapula. The principle idea behind using the acromion method is to reduce skin movement artifact, as the acromion has been shown to have the least amount of skin movement artifact compared to other sites on the scapula26. The acromion method is non-invasive and provides dynamic three-dimensional measurement of scapular kinematics. Validation studies have shown the acromion method to be valid up to 120&#176; during the arm elevation phase when using electromagnetic sensors17,27. When using marker based motion capture devices a series of markers arranged in a cluster, the acromion marker cluster (AMC), is required and has been shown to be valid when using an active-marker motion capture system28 and whilst using a passive-marker motion capture system during arm elevation and arm lowering29.
The use of the AMC with a passive marker motion capture device for measuring scapular kinematics has been used to assess changes in scapular kinematics following an intervention to address shoulder impingement30. The valid use of this method, however, depends on the ability to accurately apply the cluster of markers, the position of which has been shown to affect results31, calibrate anatomical landmarks32 and ensuring arm movements are within a valid range of motion (i.e. below 120&#176; arm elevation)29. It has also been suggested the reapplication of the marker cluster, when using an active marker based motion capture system, was found to be the source of increased error for scapular posterior tilt28. It is, therefore, important to establish the between-day reliability of the acromion method to ensure it provides a stable measure of scapular kinematics. Ensuring that measurements are reliable will enable changes in scapular kinematics, due to an intervention, for example, to be measured and examined. The methods used to measure scapular kinematics have been described elsewhere29,33; the aim of the present study was to provide a step-by-step guide and reference tool for applying these methods using a passive-marker motion capture system, with consideration to the potential sources of error, and to examine the reliability of the measurement method.

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			<td style="width:167px;">Comments/Description</td>
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			<td height="63" style="height:63px;width:216px;">Passive marker capture system</td>
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			<td style="width:119px;">N/A</td>
			<td></td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:216px;">Nexus</td>
			<td style="width:81px;">Vicon Motion Systems</td>
			<td style="width:119px;">N/A</td>
			<td>Data capture software</td>
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		<tr height="63">
			<td height="63" style="height:63px;width:216px;">Bodybuilder</td>
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			<td height="63" style="height:63px;width:216px;">14 mm retro reflective markers</td>
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			<td height="63" style="height:63px;width:216px;">6.5mm retro reflective markers</td>
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			<td style="width:119px;">VACC-V166</td>
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			<td height="63" style="height:63px;width:216px;">Calibration wand</td>
			<td style="width:81px;">Vicon Motion Systems</td>
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			<td height="21" style="height:21px;width:216px;">Plastic base</td>
			<td style="width:81px;">N/A</td>
			<td style="width:119px;">N/A</td>
			<td>Constructed &#39;in-house&#39;</td>
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			<td height="21" style="height:21px;width:216px;">Matlab</td>
			<td style="width:81px;">Mathworks</td>
			<td style="width:119px;">N/A</td>
			<td>Numerical modelling software</td>
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measurement of dynamic scapular kinematics using an acromion marker cluster to minimize skin movement artifact

The measurement of dynamic scapular kinematics is complex due to the sliding nature of the scapula beneath the skin surface. The aim of the study was to clearly describe the acromion marker cluster (AMC) method of determining scapular kinematics when using a passive marker motion capture system, with consideration for the sources of error which could affect the validity and reliability of measurements. The AMC method involves placing a cluster of markers over the posterior acromion, and through calibration of anatomical landmarks with respect to the marker cluster it is possible to obtain valid measurements of scapular kinematics. The reliability of the method was examined between two days in a group of 15 healthy individuals (aged 19-38 years, eight males) as they performed arm elevation, to 120&#176;, and lowering in the frontal, scapular and sagittal planes. Results showed that between-day reliability was good for upward scapular rotation (Coefficient of Multiple Correlation; CMC = 0.92) and posterior tilt (CMC = 0.70) but fair for internal rotation (CMC = 0.53) during the arm elevation phase. The waveform error was lower for upward rotation (2.7&#176; to 4.4&#176;) and posterior tilt (1.3&#176; to 2.8&#176;), compared to internal rotation (5.4&#176; to 7.3&#176;). The reliability during the lowering phase was comparable to results observed during the elevation phase. If the protocol outlined in this study is adhered to, the AMC provides a reliable measurement of upward rotation and posterior tilt during the elevation and lowering phases of arm movement.

Fifteen participants who had no known history of shoulder, neck or arm injuries were recruited onto the study (Table 2). To assess intra-rater (between-day) reliability, participants attended two data collection sessions separated by at least 24 hours and a maximum of 7 days. During each data collection session, the same investigator performed the protocol for attaching reflective markers, the acromion marker cluster and anatomical landmark calibrations, as detailed above. The reliability of the kinemati...

Watch this Scientific Journal Video about Measurement of Dynamic Scapular Kinematics Using an Acromion Marker Cluster to Minimize Skin Movement Artifact at JoVE.com

Measurement of Dynamic Scapular Kinematics Using an Acromion Marker Cluster to Minimize Skin Movement Artifact

This report presents details of how to adopt the acromion marker cluster method of obtaining scapular kinematics when using a passive marker motion capture device. As has been described in the literature, this method provides a robust, non-invasive, three-dimensional, dynamic and valid measurement of scapular kinematics, minimizing skin movement artifact.

The measurement of dynamic scapular kinematics is complex due to the sliding nature of the scapula beneath the skin surface. The aim of the study was to ...

measurement-dynamic-scapular-kinematics-using-an-acromion-marker

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19.0K Views.  University of Southampton. This report presents details of how to adopt the acromion marker cluster method of obtaining scapular kinematics when using a passive marker motion capture device. As has been described in the literature, this method provides a robust, non-invasive, three-dimensional, dynamic and valid measurement of scapular kinematics, minimizing skin movement artifact.

Video: Measurement of Dynamic Scapular Kinematics Using an Acromion Marker Cluster to Minimize Skin Movement Artifact

Accurate and Simple Measurement of the Pro-inflammatory Cytokine IL-1&beta; using a Whole Blood Stimulation Assay

Inflammatory processes resulting from the secretion of soluble mediators by immune cells, lead to various manifestations in skin, joints and other tissues as well as altered cytokine homeostasis. The innate immune system plays a crucial role in recognizing pathogens and other endogenous danger stimuli. One of the major cytokines released by innate immune cells is Interleukin (IL)-1. Therefore, we utilize a whole blood stimulation assay in order to measure the secretion of inflammatory cytokines and specifically of the pro-inflammatory cytokine IL-1&beta; 1, 2, 3.
Patients with genetic dysfunctions of the innate immune system causing autoinflammatory syndromes show an exaggerated release of mature IL-1&beta; upon stimulation with LPS alone. In order to evaluate the innate immune component of patients who present with inflammatory-associated pathologies, we use a specific immunoassay to detect cellular immune responses to pathogen-associated molecular patterns (PAMPs), such as the gram-negative bacterial endotoxin, lipopolysaccharide (LPS). These PAMPs are recognized by pathogen recognition receptors (PRRs), which are found on the cells of the innate immune system 4, 5, 6, 7. A primary signal, LPS, in conjunction with a secondary signal, ATP, is necessary for the activation of the inflammasome, a multiprotein complex that processes pro-IL-1&beta; to its mature, bioactive form 4, 5, 6, 8, 9, 10.
The whole blood assay requires minimal sample manipulation to assess cytokine production when compared to other methods that require labor intensive isolation and culturing of specific cell populations. This method differs from other whole blood stimulation assays; rather than diluting samples with a ratio of RPMI media, we perform a white blood cell count directly from diluted whole blood and therefore, stimulate a known number of white blood cells in culture 2. The results of this particular whole blood assay demonstrate a novel technique useful in elucidating patient cohorts presenting with autoinflammatory pathophysiologies.

Accurate and Simple Measurement of the Pro-inflammatory Cytokine IL-1&amp;#946; using a Whole Blood Stimulation Assay

We describe a simple immunoassay to measure the production of pro-inflammatory cytokines, such as IL-1 beta production, in patients presenting with autoinflammatory phenotypes. By activating cells in whole blood cultures with pathogen-associated molecular patterns, specifically with lipopolysaccharide, cytokine secretion can be conveniently evaluated in whole blood supernatants.

Inflammatory processes resulting from the secretion of soluble mediators by immune cells, lead to various manifestations in skin, joints and other tissues ...

Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging

In 2010 approximately 68,720 melanomas will be diagnosed in the US alone, with around 8,650 resulting in death 1. To date, the only effective treatment for melanoma remains surgical excision, therefore, the key to extended survival is early detection 2,3. Considering the large numbers of patients diagnosed every year and the limitations in accessing specialized care quickly, the development of objective in vivo diagnostic instruments to aid the diagnosis is essential. New techniques to detect skin cancer, especially non-invasive diagnostic tools, are being explored in numerous laboratories. Along with the surgical methods, techniques such as digital photography, dermoscopy, multispectral imaging systems (MelaFind), laser-based systems (confocal scanning laser microscopy, laser doppler perfusion imaging, optical coherence tomography), ultrasound, magnetic resonance imaging, are being tested. Each technique offers unique advantages and disadvantages, many of which pose a compromise between effectiveness and accuracy versus ease of use and cost considerations. Details about these techniques and comparisons are available in the literature 4.
Infrared (IR) imaging was shown to be a useful method to diagnose the signs of certain diseases by measuring the local skin temperature. There is a large body of evidence showing that disease or deviation from normal functioning are accompanied by changes of the temperature of the body, which again affect the temperature of the skin 5,6. Accurate data about the temperature of the human body and skin can provide a wealth of information on the processes responsible for heat generation and thermoregulation, in particular the deviation from normal conditions, often caused by disease. However, IR imaging has not been widely recognized in medicine due to the premature use of the technology 7,8 several decades ago, when temperature measurement accuracy and the spatial resolution were inadequate and sophisticated image processing tools were unavailable. This situation changed dramatically in the late 1990s-2000s. Advances in IR instrumentation, implementation of digital image processing algorithms and dynamic IR imaging, which enables scientists to analyze not only the spatial, but also the temporal thermal behavior of the skin 9, allowed breakthroughs in the field.
In our research, we explore the feasibility of IR imaging, combined with theoretical and experimental studies, as a cost effective, non-invasive, in vivo optical measurement technique for tumor detection, with emphasis on the screening and early detection of melanoma 10-13. In this study, we show data obtained in a patient study in which patients that possess a pigmented lesion with a clinical indication for biopsy are selected for imaging. We compared the difference in thermal responses between healthy and malignant tissue and compared our data with biopsy results. We concluded that the increased metabolic activity of the melanoma lesion can be detected by dynamic infrared imaging.

We demonstrated that malignant pigmented lesions with increased metabolic activity generate quantifiable amounts of heat and the measurement of the transient thermal response of the skin to a cooling excitation allows quantitative identification of melanoma and other skin cancers (vs. non-proliferative nevi) at an early stage of the disease.

In 2010 approximately 68,720 melanomas will be diagnosed in the US alone, with around 8,650 resulting in death 1. To date, the only effective treatment ...

The Measurement and Treatment of Suppression in Amblyopia

Amblyopia, a developmental disorder of the visual cortex, is one of the leading causes of visual dysfunction in the working age population. Current estimates put the prevalence of amblyopia at approximately 1-3%1-3, the majority of cases being monocular2. Amblyopia is most frequently caused by ocular misalignment (strabismus), blur induced by unequal refractive error (anisometropia), and in some cases by form deprivation.
Although amblyopia is initially caused by abnormal visual input in infancy, once established, the visual deficit often remains when normal visual input has been restored using surgery and/or refractive correction. This is because amblyopia is the result of abnormal visual cortex development rather than a problem with the amblyopic eye itself4,5 . Amblyopia is characterized by both monocular and binocular deficits6,7 which include impaired visual acuity and poor or absent stereopsis respectively. The visual dysfunction in amblyopia is often associated with a strong suppression of the inputs from the amblyopic eye under binocular viewing conditions8. Recent work has indicated that suppression may play a central role in both the monocular and binocular deficits associated with amblyopia9,10 .
Current clinical tests for suppression tend to verify the presence or absence of suppression rather than giving a quantitative measurement of the degree of suppression. Here we describe a technique for measuring amblyopic suppression with a compact, portable device11,12 . The device consists of a laptop computer connected to a pair of virtual reality goggles. The novelty of the technique lies in the way we present visual stimuli to measure suppression. Stimuli are shown to the amblyopic eye at high contrast while the contrast of the stimuli shown to the non-amblyopic eye are varied. Patients perform a simple signal/noise task that allows for a precise measurement of the strength of excitatory binocular interactions. The contrast offset at which neither eye has a performance advantage is a measure of the "balance point" and is a direct measure of suppression. This technique has been validated psychophysically both in control13,14 and patient6,9,11 populations.
In addition to measuring suppression this technique also forms the basis of a novel form of treatment to decrease suppression over time and improve binocular and often monocular function in adult patients with amblyopia12,15,16 . This new treatment approach can be deployed either on the goggle system described above or on a specially modified iPod touch device15.

Amblyopia is a developmental disorder of the visual cortex that is often accompanied by strong suppression of one eye. We present a new technique for measuring and treating interocular suppression in patients with amblyopia that can be deployed using virtual reality goggles or a portable iPod Touch device.

Amblyopia, a developmental disorder of the visual cortex, is one of the leading causes of visual dysfunction in the working age population. Current ...

Movement Retraining using Real-time Feedback of Performance

Any modification of movement - especially movement patterns that have been honed over a number of years - requires re-organization of the neuromuscular patterns responsible for governing the movement performance. This motor learning can be enhanced through a number of methods that are utilized in research and clinical settings alike. In general, verbal feedback of performance in real-time or knowledge of results following movement is commonly used clinically as a preliminary means of instilling motor learning. Depending on patient preference and learning style, visual feedback (e.g. through use of a mirror or different types of video) or proprioceptive guidance utilizing therapist touch, are used to supplement verbal instructions from the therapist. Indeed, a combination of these forms of feedback is commonplace in the clinical setting to facilitate motor learning and optimize outcomes.
Laboratory-based, quantitative motion analysis has been a mainstay in research settings to provide accurate and objective analysis of a variety of movements in healthy and injured populations. While the actual mechanisms of capturing the movements may differ, all current motion analysis systems rely on the ability to track the movement of body segments and joints and to use established equations of motion to quantify key movement patterns. Due to limitations in acquisition and processing speed, analysis and description of the movements has traditionally occurred offline after completion of a given testing session.
This paper will highlight a new supplement to standard motion analysis techniques that relies on the near instantaneous assessment and quantification of movement patterns and the display of specific movement characteristics to the patient during a movement analysis session. As a result, this novel technique can provide a new method of feedback delivery that has advantages over currently used feedback methods.

Retraining abnormal movement patterns following injury or disease is a key component of physical rehabilitation. Recent advances in technology have permitted accurate assessment of movement during a variety of tasks, with near instantaneous quantification of results. This provides new opportunities for modification of faulty movement patterns in real time.

Any modification of movement - especially movement patterns that have been honed over a number of years - requires re-organization of the neuromuscular ...

Using Quantitative Real-time PCR to Determine Donor Cell Engraftment in a Competitive Murine Bone Marrow Transplantation Model

Murine bone marrow transplantation models provide an important tool in measuring hematopoietic stem cell (HSC) functions and determining genes/molecules that regulate HSCs. In these transplant model systems, the function of HSCs is determined by the ability of these cells to engraft and reconstitute lethally irradiated recipient mice. Commonly, the donor cell contribution/engraftment is measured by antibodies to donor- specific cell surface proteins using flow cytometry. However, this method heavily depends on the specificity and the ability of the cell surface marker to differentiate donor-derived cells from recipient-originated cells, which may not be available for all mouse strains. Considering the various backgrounds of genetically modified mouse strains in the market, this cell surface/ flow cytometry-based method has significant limitations especially in mouse strains that lack well-defined surface markers to separate donor cells from congenic recipient cells. Here, we reported a PCR-based technique to determine donor cell engraftment/contribution in transplant recipient mice. We transplanted male donor bone marrow HSCs to lethally irradiated congenic female mice. Peripheral blood samples were collected at different time points post transplantation. Bone marrow samples were obtained at the end of the experiments. Genomic DNA was isolated and the Y chromosome specific gene, Zfy1, was amplified using quantitative Real time PCR. The engraftment of male donor-derived cells in the female recipient mice was calculated against standard curve with known percentage of male vs. female DNAs. Bcl2 was used as a reference gene to normalize the total DNA amount. Our data suggested that this approach reliably determines donor cell engraftment and provides a useful, yet simple method in measuring hematopoietic cell reconstitution in murine bone marrow transplantation models. Our method can be routinely performed in most laboratories because no costly equipment such as flow cytometry is required.

Determining donor cell engraftment presents a challenge in mouse bone marrow transplant models that lack well-defined phenotypical markers. We described a methodology to quantify male donor cell engraftment in female transplant recipient mice. This method can be used in all mouse strains for the study of HSC functions.

Murine bone marrow transplantation models provide an important tool in measuring hematopoietic stem cell (HSC) functions and determining genes/molecules ...

Dynamic Contrast Enhanced Magnetic Resonance Imaging of an Orthotopic Pancreatic Cancer Mouse Model

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) has been limitedly used for orthotopic pancreatic tumor xenografts due to severe respiratory motion artifact in the abdominal area. Orthotopic tumor models offer advantages over subcutaneous ones, because those can reflect the primary tumor microenvironment affecting blood supply, neovascularization, and tumor cell invasion. We have recently established a protocol of DCE-MRI of orthotopic pancreatic tumor xenografts in mouse models by securing tumors with an orthogonally bent plastic board to prevent motion transfer from the chest region during imaging. The pressure by this board was localized on the abdominal area, and has not resulted in respiratory difficulty of the animals. This article demonstrates the detailed procedure of orthotopic pancreatic tumor modeling using small animals and DCE-MRI of the tumor xenografts. Quantification method of pharmacokinetic parameters in DCE-MRI is also introduced. The procedure described in this article will assist investigators to apply DCE-MRI for orthotopic gastrointestinal cancer mouse models.

The goal of this protocol is to apply dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) for orthotopic pancreatic tumor xenografts in mice. DCE-MRI is a non-invasive method to analyze microvasculature in a target tissue, and useful to assess vascular response in a tumor following a novel therapy.

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) has been limitedly used for orthotopic pancreatic tumor xenografts due to severe ...

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 Ultrasound Imaging: Fast and Cost-effective Morphometry of Musculoskeletal Tissue

The developmental goal of 3D ultrasound imaging (3DUS) is to engineer a modality to perform 3D morphological ultrasound analysis of human muscles. 3DUS images are constructed from calibrated freehand 2D B-mode ultrasound images, which are positioned into a voxel array. Ultrasound (US) imaging allows quantification of muscle size, fascicle length, and angle of pennation. These morphological variables are important determinants of muscle force and length range of force exertion. The presented protocol describes an approach to determine volume and fascicle length of m.&#160;vastus lateralis and m.&#160;gastrocnemius medialis. 3DUS facilitates standardization using 3D anatomical references. This approach provides a fast and cost-effective approach for quantifying 3D morphology in skeletal muscles. In healthcare and sports, information on the morphometry of muscles is very valuable in diagnostics and/or follow-up evaluations after treatment or training.

3D ultrasound imaging (3DUS) allows fast and cost-effective morphometry of musculoskeletal tissues. We present a protocol to measure muscle volume and fascicle length using 3DUS.

The developmental goal of 3D ultrasound imaging (3DUS) is to engineer a modality to perform 3D morphological ultrasound analysis of human muscles. 3DUS ...

A Novel Approach to Overcome Movement Artifact When Using a Laser Speckle Contrast Imaging System for Alternating Speeds of Blood Microcirculation

The laser speckle contrast imager (LSCI) provides a powerful yet simple technique for measuring microcirculatory blood flow. Ideal for blood dynamic responses, the LSCI is used in the same way as a conventional Laser Doppler Imager (LDI). However, with a maximum skin depth of approximately 1 mm, the LSCI is designed to focus on mainly superficial blood flow. It is used to measure skin surface areas of up to 15 cm x 20 cm. The new technique introduced in this paper accounts for alternating speeds of microcirculations; i.e. both slow and fast flow flux measurement using the LSCI. The novel technique also overcomes LSCI&#39;s biggest shortcoming, which is high sensitivity to artifact movement. An adhesive opaque patch (AOP) is introduced for satisfactory recording of microcirculatory blood flow, by subtracting the LSCI signal from the AOP from the laser speckle skin signal. The optimal setting is also defined because the LSCI is most powerful when flux changes are measured relative to a reference baseline, with blood microcirculatory flux expressed as a percentage change from the baseline. These changes may be used for analyzing the status of the blood flow system.

This study introduces a novel technique for the measurement and analysis of alternating speeds of blood microcirculation in a single experiment using a laser speckle contrast imager.

The laser speckle contrast imager (LSCI) provides a powerful yet simple technique for measuring microcirculatory blood flow. Ideal for blood dynamic ...

Dynamic Measurement and Imaging of Capillaries, Arterioles, and Pericytes in Mouse Heart

Coronary arterial tone along with the opening or closing of the capillaries largely determine the blood flow to cardiomyocytes at constant perfusion pressure. However, it is difficult to monitor the dynamic changes of the coronary arterioles and the capillaries in the whole heart, primarily due to its motion and non-stop beating. Here we describe a method that enables monitoring of arterial perfusion rate, pressure and the diameter changes of the arterioles and capillaries in mouse right ventricular papillary muscles. The mouse septal artery is cannulated and perfused at a constant flow or pressure with the other dynamically measured. After perfusion with a fluorescently labeled lectin (e.g., Alexa Fluor-488 or -633 labeled Wheat-Germ Agglutinin, WGA), the arterioles and capillaries (and other vessels) in right ventricle papillary muscle and septum could be readily imaged. The vessel-diameter changes could then be measured in the presence or absence of heart contractions. When genetically encoded fluorescent proteins were expressed, specific features could be monitored. For examples, pericytes were visualized in mouse hearts that expressed NG2-DsRed. This method has provided a useful platform to study the physiological functions of capillary pericytes in heart. It is also suitable for studying the effect of reagents on the blood flow in heart by measuring the vascular/capillary diameter and the arterial luminal pressure simultaneously. This preparation, combined with a state-of-the-art optic imaging system, allows one to study the blood flow and its control at cellular and molecular level in the heart under near-physiological conditions.

Presented here is a protocol to study the coronary microcirculation in living murine heart tissue by ex vivo monitoring of the arterial perfusion pressure and flow that maintains the pressure, as well as vascular tree components including the capillary beds and pericytes, as the septal artery is cannulated and pressurized.

Coronary arterial tone along with the opening or closing of the capillaries largely determine the blood flow to cardiomyocytes at constant perfusion ...