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      Lower Extremity Joint Angle Tracking with Wireless Ultrasonic Sensors during a Squat Exercise

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          Abstract

          This paper presents an unrestrained measurement system based on a wearable wireless ultrasonic sensor network to track the lower extremity joint and trunk kinematics during a squat exercise with only one ultrasonic sensor attached to the trunk. The system consists of an ultrasound transmitter (mobile) and multiple receivers (anchors) whose positions are known. The proposed system measures the horizontal and vertical displacement, together with known joint constraints, to estimate joint flexion/extension angles using an inverse kinematic model based on the damped least-squares technique. The performance of the proposed ultrasonic measurement system was validated against a camera-based tracking system on eight healthy subjects performing a planar squat exercise. Joint angles estimated from the ultrasonic system showed a root mean square error (RMSE) of 2.85° ± 0.57° with the reference system. Statistical analysis indicated great agreements between these two systems with a Pearson's correlation coefficient (PCC) value larger than 0.99 for all joint angles' estimation. These results show that the proposed ultrasonic measurement system is useful for applications, such as rehabilitation and sports.

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          Statistical methods for assessing agreement between two methods of clinical measurement.

          In clinical measurement comparison of a new measurement technique with an established one is often needed to see whether they agree sufficiently for the new to replace the old. Such investigations are often analysed inappropriately, notably by using correlation coefficients. The use of correlation is misleading. An alternative approach, based on graphical techniques and simple calculations, is described, together with the relation between this analysis and the assessment of repeatability.
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            Validity of the Microsoft Kinect for assessment of postural control.

            Clinically feasible methods of assessing postural control such as timed standing balance and functional reach tests provide important information, however, they cannot accurately quantify specific postural control mechanisms. The Microsoft Kinect™ system provides real-time anatomical landmark position data in three dimensions (3D), and given that it is inexpensive, portable and simple to setup it may bridge this gap. This study assessed the concurrent validity of the Microsoft Kinect™ against a benchmark reference, a multiple-camera 3D motion analysis system, in 20 healthy subjects during three postural control tests: (i) forward reach, (ii) lateral reach, and (iii) single-leg eyes-closed standing balance. For the reach tests, the outcome measures consisted of distance reached and trunk flexion angle in the sagittal (forward reach) and coronal (lateral reach) planes. For the standing balance test the range and deviation of movement in the anatomical landmark positions for the sternum, pelvis, knee and ankle and the lateral and anterior trunk flexion angle were assessed. The Microsoft Kinect™ and 3D motion analysis systems had comparable inter-trial reliability (ICC difference=0.06±0.05; range, 0.00-0.16) and excellent concurrent validity, with Pearson's r-values >0.90 for the majority of measurements (r=0.96±0.04; range, 0.84-0.99). However, ordinary least products analyses demonstrated proportional biases for some outcome measures associated with the pelvis and sternum. These findings suggest that the Microsoft Kinect™ can validly assess kinematic strategies of postural control. Given the potential benefits it could therefore become a useful tool for assessing postural control in the clinical setting. Copyright © 2012 Elsevier B.V. All rights reserved.
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              Human movement analysis using stereophotogrammetry. Part 1: theoretical background.

              This paper sets the stage for a series of reviews dealing with the problems associated with the reconstruction and analysis of in vivo skeletal system kinematics using optoelectronic stereophotogrammetric data. Instantaneous bone position and orientation and joint kinematic variable estimations are addressed in the framework of rigid body mechanics. The conceptual background to these exercises is discussed. Focus is placed on the experimental and analytical problem of merging the information relative to movement and that relative to the morphology of the anatomical body parts of interest. The various global and local frames that may be used in this context are defined. Common anatomical and mathematical conventions that can be used to describe joint kinematics are illustrated in a comparative fashion. The authors believe that an effort to systematize the different theoretical and experimental approaches to the problems involved and related nomenclatures, as currently reported in the literature, is needed to facilitate data and knowledge sharing, and to provide renewed momentum for the advancement of human movement analysis.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Sensors (Basel)
                Sensors (Basel)
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                May 2015
                23 April 2015
                : 15
                : 5
                : 9610-9627
                Affiliations
                School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798 Singapore; E-Mails: qiyo0001@ 123456e.ntu.edu.sg (Y.Q.); egunawan@ 123456ntu.edu.sg (E.G.); ekslow@ 123456ntu.edu.sg (K.-S.L.); rijil001@ 123456e.ntu.edu.sg (R.T.)
                Author notes
                [* ]Author to whom correspondence should be addressed; E-Mail: ecbsoh@ 123456ntu.edu.sg ; Tel.: +65-6790-5373.
                Article
                sensors-15-09610
                10.3390/s150509610
                4481970
                25915589
                83d06926-e4d9-430e-97e4-51a44427fa90
                © 2015 by the authors; licensee MDPI, Basel, Switzerland.

                This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 12 December 2014
                : 16 April 2015
                Categories
                Article

                Biomedical engineering
                ultrasound,wireless sensor network,joint angles,squat,rehabilitation,inverse kinematics

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