Annals of Biomedical Engineering

, Volume 46, Issue 12, pp 2069–2078 | Cite as

A Wearable Magnet-Based System to Assess Activity and Joint Flexion in Humans and Large Animals

  • Feini Qu
  • Brendan D. Stoeckl
  • Peter M. Gebhard
  • Todd J. Hullfish
  • Josh R. Baxter
  • Robert L. Mauck


Functional outcomes, such as joint flexion and gait, are important indicators of efficacy in musculoskeletal research. Current technologies that objectively assess these parameters, including visual tracking systems and force plates, are challenging to deploy in long-term translational and clinical studies. To that end, we developed a wearable device that measures both physical activity and joint flexion using a single integrated sensor and magnet system, and hypothesized that it could evaluate post-operative functional recovery in an unsupervised setting. To demonstrate the feasibility of measuring joint flexion, we first compared knee motion from the wearable device to that acquired from a motion capture system to confirm that knee flexion measurements during normal human gait, predicted via changes in magnetic field strength, closely correlated with data acquired by motion capture. Using this system, we then monitored a porcine cohort after bilateral stifle arthrotomy to investigate longitudinal changes in physical activity and joint flexion. We found that unsupervised activity declined immediately after surgery, with a return to pre-operative activity occurring over a period of 2 weeks. By providing objective, individualized data on locomotion and joint function, this magnet-based system will facilitate the in vivo assessment of novel therapeutics in translational orthopaedic research.


Joint function Motion sensor Large animal model Translational research 



This work was supported by the NIH (T32 AR007132), the Penn Center for Musculoskeletal Disorders (P30 AR069619), and the Montague Research Award. The authors thank Drs. Emily L. Meidel, Christian G. Pfeifer, and James M. Friedman for their assistance with the large animal model.


Feini Qu and Peter Gebhard are inventors on patent application US20170231533 and co-founders of Animotion, LLC. Feini Qu, Peter Gebhard, and Brendan Stoeckl have equity interest in Animotion, LLC, which is developing products related to the research described in this paper. All remaining co-authors have no competing financial interests.


  1. 1.
    Akbarshahi, M., A. G. Schache, J. W. Fernandez, R. Baker, S. Banks, and M. G. Pandy. Non-invasive assessment of soft-tissue artifact and its effect on knee joint kinematics during functional activity. J. Biomech. 43:1292–1301, 2010.CrossRefGoogle Scholar
  2. 2.
    Anderst, W. J., C. Les, and S. Tashman. In vivo serial joint space measurements during dynamic loading in a canine model of osteoarthritis. Osteoarthr. Cartil. 13:808–816, 2005.CrossRefGoogle Scholar
  3. 3.
    Bansal, S., N. M. Keah, A. L. Neuwirth, O. O’Reilly, F. Qu, B. N. Seiber, S. Mandalapu, R. L. Mauck, and M. H. Zgonis. Large animal models of meniscus repair and regeneration: a systematic review of the state of the field. Tissue Eng. Part C Methods 11:661–672, 2017.CrossRefGoogle Scholar
  4. 4.
    Barthélémy, I., E. Barrey, J.-L. Thibaud, A. Uriarte, T. Voit, S. Blot, and J.-Y. Hogrel. Gait analysis using accelerometry in dystrophin-deficient dogs. Neuromuscul. Disord. 19:788–796, 2009.CrossRefGoogle Scholar
  5. 5.
    Baxter, J. R., D. R. Sturnick, C. A. Demetracopoulos, S. J. Ellis, and J. T. Deland. Cadaveric gait simulation reproduces foot and ankle kinematics from population-specific inputs. J. Orthop. Res. 34:1663–1668, 2016.CrossRefGoogle Scholar
  6. 6.
    Benoit, D. L., D. K. Ramsey, M. Lamontagne, L. Xu, P. Wretenberg, and P. Renstrom. Effect of skin movement artifact on knee kinematics during gait and cutting motions measured in vivo. Gait Posture 24:152–164, 2006.CrossRefGoogle Scholar
  7. 7.
    Bonnet, S., and R. Héliot. A magnetometer-based approach for studying human movements. IEEE Trans. Biomed. Eng. 54:1353–1355, 2007.CrossRefGoogle Scholar
  8. 8.
    Brown, D. C., R. C. Boston, and J. T. Farrar. Use of an activity monitor to detect response to treatment in dogs with osteoarthritis. J. Am. Vet. Med. Assoc. 237:66–70, 2010.CrossRefGoogle Scholar
  9. 9.
    Cook, J. L., P. A. Smith, C. C. Bozynski, K. Kuroki, C. R. Cook, A. M. Stoker, and F. M. Pfeiffer. Multiple injections of leukoreduced platelet rich plasma reduce pain and functional impairment in a canine model of ACL and meniscal deficiency. J. Orthop. Res. 34:607–615, 2016.CrossRefGoogle Scholar
  10. 10.
    Defrate, L. E., R. Papannagari, T. J. Gill, J. M. Moses, N. P. Pathare, and G. Li. The 6 degrees of freedom kinematics of the knee after anterior cruciate ligament deficiency: an in vivo imaging analysis. Am. J. Sports Med. 34:1240–1246, 2006.CrossRefGoogle Scholar
  11. 11.
    Evans, R., C. Horstman, and M. Conzemius. Accuracy and optimization of force platform gait analysis in Labradors with cranial cruciate disease evaluated at a walking gait. Vet. Surg. 34:445–449, 2005.CrossRefGoogle Scholar
  12. 12.
    Favre, J., B. M. Jolles, R. Aissaoui, and K. Aminian. Ambulatory measurement of 3d knee joint angle. J. Biomech. 41:1029–1035, 2008.CrossRefGoogle Scholar
  13. 13.
    Fisher, M. B., N. S. Belkin, A. H. Milby, E. A. Henning, M. Bostrom, M. Kim, C. Pfeifer, G. Meloni, G. R. Dodge, J. A. Burdick, T. P. Schaer, D. R. Steinberg, and R. L. Mauck. Cartilage repair and subchondral bone remodeling in response to focal lesions in a mini-pig model: implications for tissue engineering. Tissue Eng. Part A 21:850–860, 2014.CrossRefGoogle Scholar
  14. 14.
    Keegan, K. G. Evidence-based lameness detection and quantification. Vet. Clin. North Am. Equine Pract. 23:403–423, 2007.CrossRefGoogle Scholar
  15. 15.
    Keegan, K. G., E. V. Dent, D. A. Wilson, J. Janicek, J. Kramer, A. Lacarrubba, D. M. Walsh, M. W. Cassells, T. M. Esther, P. Schiltz, K. E. Frees, C. L. Wilhite, J. M. Clark, C. C. Pollitt, R. Shaw, and T. Norris. Repeatability of subjective evaluation of lameness in horses. Equine Vet. J. 42:92–97, 2010.CrossRefGoogle Scholar
  16. 16.
    Keegan, K. G., Y. Yonezawa, P. F. Pai, D. A. Wilson, and J. Kramer. Evaluation of a sensor-based system of motion analysis for detection and quantification of forelimb and hind limb lameness in horses. Am. J. Vet. Res. 65:665–670, 2004.CrossRefGoogle Scholar
  17. 17.
    Ladha, C., J. O’Sullivan, Z. Belshaw, and L. Asher. Gaitkeeper: a system for measuring canine gait. Sensors (Basel) 17:309, 2017.CrossRefGoogle Scholar
  18. 18.
    Lafortune, M. A., P. R. Cavanagh, H. J. Sommer, 3rd, and A. Kalenak. Three-dimensional kinematics of the human knee during walking. J. Biomech. 25:347–357, 1992.CrossRefGoogle Scholar
  19. 19.
    Lascelles, B. D., S. C. Roe, E. Smith, L. Reynolds, J. Markham, D. Marcellin-Little, M. S. Bergh, and S. C. Budsberg. Evaluation of a pressure walkway system for measurement of vertical limb forces in clinically normal dogs. Am. J. Vet. Res. 67:277–282, 2006.CrossRefGoogle Scholar
  20. 20.
    Leardini, A., Z. Sawacha, G. Paolini, S. Ingrosso, R. Nativo, and M. G. Benedetti. A new anatomically based protocol for gait analysis in children. Gait Posture 26:560–571, 2007.CrossRefGoogle Scholar
  21. 21.
    Lebel, K., P. Boissy, H. Nguyen, and C. Duval. Autonomous quality control of joint orientation measured with inertial sensors. Sensors (Basel) 16:1037, 2016.CrossRefGoogle Scholar
  22. 22.
    Maher, S. A., S. A. Rodeo, H. G. Potter, L. J. Bonassar, T. M. Wright, and R. F. Warren. A pre-clinical test platform for the functional evaluation of scaffolds for musculoskeletal defects: the meniscus. HSS J. 7:157–163, 2011.CrossRefGoogle Scholar
  23. 23.
    Ng, J. L., M. E. Kersh, S. Kilbreath, and M. Knothe Tate. Establishing the basis for mechanobiology-based physical therapy protocols to potentiate cellular healing and tissue regeneration. Front. Physiol. 8:303, 2017.CrossRefGoogle Scholar
  24. 24.
    O’Donovan, K. J., R. Kamnik, D. T. O’Keeffe, and G. M. Lyons. An inertial and magnetic sensor based technique for joint angle measurement. J. Biomech. 40:2604–2611, 2007.CrossRefGoogle Scholar
  25. 25.
    Olsen, E., P. H. Andersen, and T. Pfau. Accuracy and precision of equine gait event detection during walking with limb and trunk mounted inertial sensors. Sensors (Basel) 12:8145–8156, 2012.CrossRefGoogle Scholar
  26. 26.
    Pfeifer, C. G., M. B. Fisher, J. L. Carey, and R. L. Mauck. Impact of guidance documents on translational large animal studies of cartilage repair. Sci. Transl. Med. 7:310, 2015.CrossRefGoogle Scholar
  27. 27.
    Pfeifer, C. G., S. D. Kinsella, A. H. Milby, M. B. Fisher, N. S. Belkin, R. L. Mauck, and J. L. Carey. Development of a large animal model of osteochondritis dissecans of the knee: a pilot study. Orthop. J. Sports Med. 3:2325967115570019, 2015.CrossRefGoogle Scholar
  28. 28.
    Qu, F., M. P. Pintauro, J. E. Haughan, E. A. Henning, J. L. Esterhai, T. P. Schaer, R. L. Mauck, and M. B. Fisher. Repair of dense connective tissues via biomaterial-mediated matrix reprogramming of the wound interface. Biomaterials 39:85–94, 2015.CrossRefGoogle Scholar
  29. 29.
    Rajagopal, A., C. L. Dembia, M. S. DeMers, D. D. Delp, J. L. Hicks, and S. L. Delp. Full-body musculoskeletal model for muscle-driven simulation of human gait. IEEE Trans. Biomed. Eng. 63:2068–2079, 2016.CrossRefGoogle Scholar
  30. 30.
    Roepstorff, L., T. Wiestner, M. A. Weishaupt, and E. Egenvall. Comparison of microgyro-based measurements of equine metatarsal/metacarpal bone to a high speed video locomotion analysis system during treadmill locomotion. Vet. J. 198(Suppl 1):e157–e160, 2013.CrossRefGoogle Scholar
  31. 31.
    Schatti, O., S. Grad, J. Goldhahn, G. Salzmann, Z. Li, M. Alini, and M. J. Stoddart. A combination of shear and dynamic compression leads to mechanically induced chondrogenesis of human mesenchymal stem cells. Eur. Cell Mater. 22:214–225, 2011.CrossRefGoogle Scholar
  32. 32.
    Shin, J. H., B. Greer, C. H. Hakim, Z. Zhou, Y. C. Chung, Y. Duan, Z. He, and D. Duan. Quantitative phenotyping of duchenne muscular dystrophy dogs by comprehensive gait analysis and overnight activity monitoring. PLoS ONE 8:e59875, 2013.CrossRefGoogle Scholar
  33. 33.
    Stavrakakis, S., J. H. Guy, O. M. Warlow, G. R. Johnson, and S. A. Edwards. Longitudinal gait development and variability of growing pigs reared on three different floor types. Animal 8:338–346, 2014.CrossRefGoogle Scholar
  34. 34.
    Zumwalt, A. C., M. Hamrick, and D. Schmitt. Force plate for measuring the ground reaction forces in small animal locomotion. J. Biomech. 39:2877–2881, 2006.CrossRefGoogle Scholar

Copyright information

© Biomedical Engineering Society 2018

Authors and Affiliations

  • Feini Qu
    • 1
    • 2
  • Brendan D. Stoeckl
    • 1
    • 2
  • Peter M. Gebhard
    • 1
  • Todd J. Hullfish
    • 3
  • Josh R. Baxter
    • 3
  • Robert L. Mauck
    • 1
    • 2
  1. 1.McKay Orthopaedic Research Laboratory, Department of Orthopaedic SurgeryUniversity of PennsylvaniaPhiladelphiaUSA
  2. 2.Translational Musculoskeletal Research CenterCorporal Michael J. Crescenz VA Medical CenterPhiladelphiaUSA
  3. 3.Human Motion Laboratory, Department of Orthopaedic SurgeryUniversity of PennsylvaniaPhiladelphiaUSA

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