Research Papers

Inexpensive Vision-Based System for the Direct Measurement of Ankle Stiffness During Quiet Standing

[+] Author and Article Information
Raul Chavez-Romero

Unidad Académica de Ingeniería I,
Programa de Ingeniería Mecánica,
Universidad Autónoma de Zacatecas,
Jardín Juárez #147,
Zacatecas 98000, México
e-mail: rchavez@uaz.edu.mx

Antonio Cardenas

Facultad de Ingeniería,
Centro de Investigación y Estudios de Posgrado,
Universidad Autónoma de San Luis Potosí,
Avenue Dr. Manuel Nava #9,
San Luis Potosí 78290, México
e-mail: antonio.cardenas@uaslp.mx

Juan Manuel Rendon-Mancha

Departamento de Computación,
Universidad Autónoma del Estado de Morelos,
Avenue Universidad #1001,
Cuernavaca, Morelos 62209, México
e-mail: rendon@uaem.mx

Karinna M. Vernaza

Department of Mechanical Engineering,
Gannon University,
109 University Square,
Erie, PA 16541-0001
e-mail: vernaza001@gannon.edu

Davide Piovesan

Biomedical Engineering Program,
Department of Mechanical Engineering,
Gannon University,
109 University Square, PMB 3251,
Erie, PA 16541-0001
e-mail: piovesan001@gannon.edu

1Corresponding author.

Manuscript received October 10, 2014; final manuscript received July 9, 2015; published online August 12, 2015. Assoc. Editor: Venketesh Dubey.

J. Med. Devices 9(4), 041011 (Aug 12, 2015) (8 pages) Paper No: MED-14-1250; doi: 10.1115/1.4031060 History: Received October 10, 2014

We created a sensor-fusion suite for the acquisition of biometric information that can be used for the estimation of human control strategy in a variety of everyday tasks. This work focuses on the experimental validation of the integrated motion capture subsystem based on raster images. Understanding human control strategies utilized in everyday activity requires measurement of several variables that can be grouped as kinematic, dynamic, and biological-feedback variables. Hence, there is a strong need for the acquisition, analysis, and synchronization of the information measured by a variety of transducers. Our system was able to capture the complex dynamics of a flexible robot by means of two inexpensive web cameras without compromising accuracy. After validating the vision system by means of the robotic device, a direct measure of the center of gravity (COG) position during the recovery from a fall was performed on two groups of human subjects separated by age. The instrumental setup was used to estimate how ankle operational stiffness changes as function of age. The results indicate a statistical increase of stiffness for the older group.

Copyright © 2015 by ASME
Your Session has timed out. Please sign back in to continue.


Janssen, H. C. , Samson, M. M. , and Verhaar, H. J. , 2002, “Vitamin D Deficiency, Muscle Function, and Falls in Elderly People,” Am. J. Clin. Nutr., 75(4), pp. 611–615. [PubMed]
Winter, D. A. , 1995, A.B.C. (Anatomy, Biomechanics and Control) of Balance During Standing and Walking, Waterloo Biomechanics, Waterloo, ON, Canada.
Langlois, J. , Visser, M. , Davidovic, L. S. , Maggi, S. , Li, G. , and Harris, T. B. , 1998, “Hip Fracture Risk in Older White Men is Associated With Change in Body Weight From Age 50 Years to Old Age,” Arch. Intern. Med., 158(9), pp. 990–996. [CrossRef] [PubMed]
Menz, H. B. , Morris, M. E. , and Lord, S. R. , 2005, “Foot and Ankle Characteristics Associated With Impaired Balance and Functional Ability in Older People,” J. Gerontol., Ser. A, 60(12), pp. 1546–1552. [CrossRef]
Piovesan, D. , Morasso, P. , Giannoni, P. , and Casadio, M. , 2013, “Arm Stiffness During Assisted Movement After Stroke: The Influence of Visual Feedback and Training,” IEEE Trans. Neural Syst. Rehabil. Eng., 21(3), pp. 454–465. [CrossRef] [PubMed]
Piovesan, D. , Pierobon, A. , Dizio, P. , and Lackner, J. R. , 2012, “Measuring Multi-Joint Stiffness During Single Movements: Numerical Validation of a Novel Time-Frequency Approach,” PLoS One, 7(3), p. e33086. [CrossRef] [PubMed]
Piovesan, D. , Pierobon, A. , Dizio, P. , and Lackner, J. R. , 2013, “Experimental Measure of Arm Stiffness During Single Reaching Movements With a Time-Frequency Analysis,” J. Neurophysiol., 110(10), pp. 2484–2496. [CrossRef] [PubMed]
Casadio, M. , Morasso, P. G. , and Sanguineti, V. , 2005, “Direct Measurement of Ankle Stiffness During Quiet Standing: Implications for Control Modelling and Clinical Application,” Gait Posture, 21(4), pp. 410–424. [CrossRef] [PubMed]
Piovesan, D. , Pierobon, A. , Dizio, P. , and Lackner, J. R. , 2011, “Comparative Analysis of Methods for Estimating Arm Segment Parameters and Joint Torques From Inverse Dynamics,” ASME J. Biomech. Eng., 133(3), p. 031003. [CrossRef]
Piovesan, D. , Bortolami, S. B. , Debei, S. , Dizio, P. , and Lackner, J. R. , 2005, Is Surface Electromyography a Measure for Neurocommands? Society for Neuroscience, Washington, DC.
Tognetti, A. , Lorussi, F. , Mura, G. , Carbonaro, N. , Pacelli, M. , Paradiso, R. , and Rossi, D. , 2014, “New Generation of Wearable Goniometers for Motion Capture Systems,” J. Neuroeng. Rehabil., 11(1), p. 56. [CrossRef] [PubMed]
Pierobon, A. , Piovesan, D. , Dizio, P. , and Lackner, J. R. , 2008, Moving Object in Microgravity, Society for Neuroscience, Washington, DC.
Bohannon, R. W. , Harrison, S. , and Kinsella-Shaw, J. , 2009, “Reliability and Validity of Pendulum Test Measures of Spasticity Obtained With the Polhemus Tracking System From Patients With Chronic Stroke,” J. Neuroeng. Rehabil., 6(30).
Klopčar, N. , and Lenarčič, J. , 2005, “Kinematic Model for Determination of Human Arm Reachable Workspace,” Meccanica, 40(2), pp. 203–219. [CrossRef]
Schmidt, R. , Disselhorst-Klug, C. , Silny, J. , and Rau, G. , 1999, “A Marker-Based Measurement Procedure for Unconstrained Wrist and Elbow Motions,” J. Biomech., 32(6), pp. 615–621. [CrossRef] [PubMed]
Roy, J.-S. , Moffet, H. , Mcfadyen, B. J. , and Macdermid, J. C. , 2010, “The Kinematics of Upper Extremity Reaching: A Reliability Study on People With and Without Shoulder Impingement Syndrome,” Sports Med. Arthroscopy Rehabil. Ther. Technol., 2(1), p. 8. [CrossRef]
Barca, J. C. , Rumantir, G. , and Koon Li, R. , 2006, “A New Illuminated Contour-Based Marker System for Optical Motion Capture,” International Conference on Innovations in Information Technology, Dubai, UAE, Nov. 19–21.
Weber, M. , Ben Amor, H. , and Alexander, T. , 2008, “Identifying Motion Capture Tracking Markers With Self-Organizing Maps,” Virtual Reality Conference (VR '08), Reno, NE, Mar. 8–12, pp. 297–298.
Orr, J. , and Shelton, J. C. , 1997, Optical Measurement Methods in Biomechanics, Springer, London.
Corazza, S. , Mündermann, L. , Gambaretto, E. , Ferrigno, G. , and Andriacchi, T. P. , 2010, “Markerless Motion Capture Through Visual Hull, Articulated ICP and Subject Specific Model Generation,” Int. J. Comput. Vision, 87(1–2), pp. 156–169. [CrossRef]
Steele, K. , Johnson, A. , Kelley, A. , Johnson, T. , and Andriacchi, T. , 2009, “Markerless vs. Marker-Based Motion Capture: A Comparison of Measured Joint Centers,” North American Congress on Biomechanics Annual Meeting, Ann Arbor, MI, Aug. 5–9.
Clark, R. A. , Pua, Y. H. , Bryant, A. L. , and Hunt, M. A. , 2013, “Validity of the Microsoft Kinect for Providing Lateral Trunk Lean Feedback During Gait Retraining,” Gait Posture, 38(4), pp. 1064–1066. [CrossRef] [PubMed]
Clark, R. A. , Pua, Y.-H. , Fortin, K. , Ritchie, C. , Webster, K. E. , Denehy, L. , and Bryant, A. L. , 2012, “Validity of the Microsoft Kinect for Assessment of Postural Control,” Gait Posture, 36(3), pp. 372–377. [CrossRef] [PubMed]
Corazza, S. , Mündermann, L. , Chaudhari, A. , Demattio, T. , Cobelli, C. , and Andriacchi, T. , 2006, “A Markerless Motion Capture System to Study Musculoskeletal Biomechanics: Visual Hull and Simulated Annealing Approach,” Ann. Biomed. Eng., 34(6), pp. 1019–1029. [CrossRef] [PubMed]
Mündermann, L. , Anguelov, D. , Corazza, S. , Chaudhari, A. M. , and Andriacchi, T. P. , 2005, “Validation of a Markerless Motion Capture System for the Calculation of Lower Extremity Kinematics,” 29th Annual Meeting of the American Society of Biomechanics, Cleveland, OH, July 31–Aug. 5.
Mundermann, L. , Corazza, S. , and Andriacchi, T. P. , 2007, “Accurately Measuring Human Movement Using Articulated ICP With Soft-Joint Constraints and a Repository of Articulated Models,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR '07), Minneapolis, MN, June 17–22.
Schmitz, A. , Ye, M. , Boggess, G. , Shapiro, R. , Yang, R. , and Noehren, B. , 2015, “The Measurement of In Vivo Joint Angles During a Squat Using a Single Camera Markerless Motion Capture System as Compared to a Marker Based System,” Gait Posture, 41(2), pp. 694–698. [CrossRef] [PubMed]
Corazza, S. , Mündermann, L. , and Andriacchi, T. , 2006, “Markerless Motion Capture Methods for the Estimation of Human Body Kinematics,” 9th International Symposium on the 3D Analysis of Human Movement, Valenciennes, France, June 28–30.
Mentiplay, B. F. , Clark, R. A. , Mullins, A. , Bryant, A. L. , Bartold, S. , and Paterson, K. , 2013, “Reliability and Validity of the Microsoft Kinect for Evaluating Static Foot Posture,” J. Foot Ankle Res., 6(1), p. 14. [CrossRef] [PubMed]
Stone, E. , and Skubic, M. , 2011, “Evaluation of an Inexpensive Depth Camera for In-Home Gait Assessment,” J. Ambient Intell. Smart Environ., 3(4), pp. 349–361.
Meta-Motion, 2013, “Motion Capture Prices,” Meta Motion, San Francisco, CA, http://www.metamotion.com/FAQ/prices.html
Rendon-Mancha, J. M. , Cardenas, A. , Garcia, M. A. , Gonzalez-Galvan, E. , and Lara, B. , 2010, “Robot Positioning Using Camera-Space Manipulation With a Linear Camera Model,” IEEE Trans. Rob., 26(4), pp. 726–733. [CrossRef]
García, M. A. , Cárdenas, A. , Rendón, J. M. , and Maya Méndez, M. , 2009, “Una Plataforma De Control Basado En Visión Para La Rehabilitación De Robots Manipuladores De Tipo Industrial,” Computación y Sistemas, 12(4), pp. 409–420.
Cárdenas, A. , Goodwine, B. , Skaar, S. , and Seelinger, M. , 2003, “Vision-Based Control of a Mobile Base and On-Board Arm,” Int. J. Rob. Res., 22(9), pp. 677–698. [CrossRef]
Zhengyou, Z. , 2000, “A Flexible New Technique for Camera Calibration,” IEEE Trans. Pattern Anal. Mach. Intell., 22(11), pp. 1330–1334. [CrossRef]
Hartley, R. , and Zisserman, A. , 2003, Multiple View Geometry in Computer Vision, Cambridge University Press, Cambridge, UK.
Chanchareon, R. , Sangveraphunsiri, V. , and Chantranuwathana, S. , 2006, “Tracking Control of an Inverted Pendulum Using Computed Feedback Linearization Technique,” IEEE Conference on Robotics, Automation and Mechatronics, Bangkok, Thailand, June 1–3.
Franklin, E. N. , 2012, Dynamic Alignment Through Imagery, Human Kinetics, Champaign, IL.
Bortolami, S. B. , Dizio, P. , Rabin, E. , and Lackner, J. R. , 2003, “Analysis of Human Postural Responses to Recoverable Falls,” Exp. Brain Res., 151(3), pp. 387–404. [CrossRef] [PubMed]
Piovesan, D. , Pierobon, A. , and Mussa Ivaldi, F. A. , 2013, “Critical Damping Conditions for Third Order Muscle Models: Implications for Force Control,” ASME J. Biomech. Eng., 135(10), p. 101010. [CrossRef]
McGinnis, P. M. , 1999, Biomechanics of Sport and Exercise, Human Kinetics, Champaign, IL.
Gonzalez-Galvan, E. J. , Pazos-Flores, F. , Skaar, S. B. , and Cardenas-Galindo, A. , 2002, “Camera Pan/Tilt to Eliminate the Workspace-Size/Pixel-Resolution Tradeoff With Camera-Space Manipulation,” Rob. Comput. Integr. Manuf., 18(2), pp. 95–104. [CrossRef]
Piovesan, D. , Casadio, M. , Mussa-Ivaldi, F. , and Morasso, P. , 2011, “Multijoint Arm Stiffness During Movements Following Stroke: Implications for Robot Therapy,” IEEE International Conference on Rehabilitation Robotics (ICORR), Zurich, Switzerland, June 29–July 1.
Piovesan, D. , Casadio, M. , Mussa-Ivaldi, F. A. , and Morasso, P. , 2012, “Comparing Two Computational Mechanisms for Explaining Functional Recovery in Robot-Therapy of Stroke Survivors,” 4th IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), Rome, Italy, June 24–27, pp. 1488–1493.
Melendez-Calderon, A. , Piovesan, D. , and Mussa-Ivaldi, F. , 2013, “Therapist Recognition of Impaired Muscle Groups in Simulated Multi-Joint Hypertonia,” 2013 IEEE International Conference on Rehabilitation Robotics (ICORR), Seattle, WA, pp. 1–6.
Piovesan, D. , Melendez-Calderon, A. , and Mussa-Ivaldi, F. , 2013, “Haptic Recognition of Dystonia and Spasticity in Simulated Multi-Joint Hypertonia,” IEEE International Conference on Rehabilitation Robotics (ICORR), Seattle, WA, June 24–26.
Melendez-Calderon, A. , Piovesan, D. , Patton, J. L. , and Mussa-Ivaldi, F. A. , 2014, “Enhanced Assessment of Limb Neuro-Mechanics Via a Haptic Display,” Rob. Biomimetics, 1(1), p. 12. [CrossRef]
Funaya, H. , Shibata, T. , Wada, Y. , and Yamanaka, T. , 2013, “Accuracy Assessment of Kinect Body Tracker in Instant Posturography for Balance Disorders,” 7th International Symposium on Medical Information and Communication Technology (ISMICT), Tokyo, Japan, Mar. 6–8, pp. 213–217.
Obdrzalek, S. , Kurillo, G. , Ofli, F. , Bajcsy, R. , Seto, E. , Jimison, H. , and Pavel, M. , 2012, “Accuracy and Robustness of Kinect Pose Estimation in the Context of Coaching of Elderly Population,” Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), San Diego, CA, Aug. 28–Sept. 1, pp. 1188–1193.
Khoshelham, K. , and Elberink, S. O. , 2012, “Accuracy and Resolution of Kinect Depth Data for Indoor Mapping Applications,” Sensors (Basel), 12(2), pp. 1437–1454. [CrossRef] [PubMed]
Han, J. J. , Kurillo, G. , Abresch, R. T. , De Bie, E. , Nicorici Lewis, A. , and Bajcsy, R. , 2015, “Upper Extremity 3D Reachable Workspace Analysis in Dystrophinopathy Using Kinect,” Muscle Nerve, epub.
Li, Y. , Berkowitz, L. , Noskin, G. , and Mehrotra, S. , 2014, “Detection of Patient's Bed Statuses in 3D Using a Microsoft Kinect,” 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Chicago, Aug. 26–30, pp. 5900–5903.
Pfister, A. , West, A. M. , Bronner, S. , and Noah, J. A. , 2014, “Comparative Abilities of Microsoft Kinect and Vicon 3D Motion Capture for Gait Analysis,” J. Med. Eng. Technol., 38(5), pp. 274–280. [CrossRef] [PubMed]
Leach, J. M. , Mancini, M. , Peterka, R. J. , Hayes, T. L. , and Horak, F. B. , 2014, “Validating and Calibrating the Nintendo Wii Balance Board to Derive Reliable Center of Pressure Measures,” Sensors (Basel), 14(10), pp. 18244–18267. [CrossRef] [PubMed]
Bartlett, H. L. , Ting, L. H. , and Bingham, J. T. , 2014, “Accuracy of Force and Center of Pressure Measures of the Wii Balance Board,” Gait Posture, 39(1), pp. 224–228. [CrossRef] [PubMed]


Grahic Jump Location
Fig. 1

Settings for calibrations pattern for estimation of vision parameters

Grahic Jump Location
Fig. 2

(a) Segmental model of human standing, (b) analytical schematic of robot, and (c) human and robotic device proportions

Grahic Jump Location
Fig. 3

Phase A—quiet standing, phase B—hold, phase C—release with consequence acceleration of the center of mass forward, and phase D—recoil where fall is prevented and quiet posture is regained as in condition A

Grahic Jump Location
Fig. 4

Block diagram of positional step response from phase D back to phase A

Grahic Jump Location
Fig. 5

Tracking angle from vision system (gray) and tracked angle of a pendulum using the robot's encoder (dashed)

Grahic Jump Location
Fig. 6

Torque trajectory at the ankle and angular displacement of the COG for the experiment on one unimpaired individual. (Top panel) measurement from force plate of the total torque at the ground. (Bottom panel) position of the COG as tracked by the vision system. Shaded area indicates phases B and C from Fig 3. Nonshaded area represents the transient in the recovery from fall between phase D and phase A in Fig. 3. Td is the period of oscillation of the COG before system stabilization; θmax is the maximum angular deviation during phase D; θf is the desired angle at equilibrium in phase A; and θ0 is the position at the beginning of phase D.

Grahic Jump Location
Fig. 7

Comparison of ankle stiffness in two age groups




Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In