960
Views
14
CrossRef citations to date
0
Altmetric
Articles

Assessing Multiple Sclerosis With Kinect: Designing Computer Vision Systems for Real-World Use

Pages 191-226 | Received 14 Nov 2014, Accepted 31 Aug 2015, Published online: 16 Feb 2016

REFERENCES

  • Bailenson, J., Patel, K., Nielsen, A., Bajscy, R., Jung, S.-H., & Kurillo, G. (2008). The effect of interactivity on learning physical actions in virtual reality. Media Psychology, 11, 354–376. doi:10.1080/15213260802285214
  • Baram, Y., & Miller, A. (2006). Virtual reality cues for improvement of gait in patients with multiple sclerosis. Neurology, 66, 178–181. doi:10.1212/01.wnl.0000194255.82542.6b
  • Behrens, J., Otte, K., Mansow-Model, S., Brandt, A., & Paul, F. (2014). Kinect-based gait analysis in patients with multiple sclerosis (P3.135). Neurology, 82(10 Suppl.), P3.135.
  • Bellotti, V., Back, M., Edwards, W. K., Grinter, R. E., Henderson, A., & Lopes, C. (2002). Making sense of sensing systems. Proceedings of the CHI 2002 Conference on Human Factors in Computer Systems. New York, NY: ACM.
  • Bonnechère, B., Jansen, B., Omelina, L., Degelaen, M., Wermenbol, V., Rooze, M., & Van Sint Jan, S. (2014). Can serious games be incorporated with conventional treatment of children with cerebral palsy? A review. Research in Developmental Disabilities, 35, 1899–1913. doi:10.1016/j.ridd.2014.04.016
  • Bonnechère, B., Jansen, B., Salvia, P., Bouzahouene, H., Omelina, L., Moiseev, F., & Van Sint Jan, S. (2014). Validity and reliability of the Kinect within functional assessment activities: Comparison with standard stereophotogrammetry. Gait & Posture, 39, 593–598. doi:10.1016/j.gaitpost.2013.09.018
  • Chan, J. C. P., Leung, H., Tang, J. K. T., & Komura, T. (2011). A virtual reality dance training system using motion capture technology. IEEE Transactions on Learning Technologies, 4, 187–195. doi:10.1109/TLT.2010.27
  • Charbonneau, E., Miller, A., Wingrave, C., & LaViola, J. J. (2009). Understanding visual interfaces for the next generation of dance-based rhythm video games. Proceedings of the SIGGRAPH 2009 Symposium on Video Games–Sandbox ’09. New York, NY: ACM.
  • Chua, P., Crivella, R., Daly, B., Hu, N., Schaaf, R., Ventura, D., & Pausch, R. (2003). Training for physical tasks in virtual environments: Tai Chi. IEEE Virtual Reality, 2003, 87–94.
  • Clark, R. A., Pua, Y.-H., Fortin, K., Ritchie, C., Webster, K. E., Denehy, L., & Bryant, A. L. (2012). Validity of the Microsoft Kinect for assessment of postural control. Gait & Posture, 36, 372–377. doi:10.1016/j.gaitpost.2012.03.033
  • Cohen, J. A., Reingold, S. C., Polman, C. H., & Wolinsky, J. S. (2012). Disability outcome measures in multiple sclerosis clinical trials: Current status and future prospects. The Lancet Neurology, 11, 467–476. doi:10.1016/S1474-4422(12)70059-5
  • Eguíluz, G., & García Zapirain, B. (2013). Use of a time-of-flight camera with an Omek BeckonTM framework to analyze, evaluate and correct in real time the verticality of multiple sclerosis patients during exercise. International Journal of Environmental Research and Public Health, 10, 5807–5829. doi:10.3390/ijerph10115807
  • Gijbels, D., Lamers, I., Kerkhofs, L., Alders, G., Knippenberg, E., & Feys, P. (2011). The Armeo Spring as training tool to improve upper limb functionality in multiple sclerosis: A pilot study. Journal of Neuroengineering and Rehabilitation, 8, 5. doi:10.1186/1743-0003-8-5
  • Gladstone, D. J., Danells, C. J., & Black, S. E. (2002). The fugl-meyer assessment of motor recovery after stroke: A critical review of its measurement properties. Neurorehabilitation and Neural Repair, 16, 232–240. doi:10.1177/154596802401105171
  • Goodwin, C. (1994). Professional vision. American Anthropologist, 96, 606–633. doi:10.1525/aa.1994.96.issue-3
  • Hartswood, M., Procter, R., & Rouncefield, M. (2003). “Repairing”the machine: A case study of the evaluation of computer-aided detection tools in breast screening. Proceedings of the ECSCW 2003 Conference on European Computer Supported Cooperative Work.
  • Hayashi, E., Maas, M., & Hong, J. I. (2014). Wave to me. Proceedings of the CHI 2014 Conference on Human Factors in Computer Systems. New York, NY: ACM.
  • Hobart, J. C., Cano, S. J., Zajicek, J. P., & Thompson, A. J. (2007). Rating scales as outcome measures for clinical trials in neurology: Problems, solutions, and recommendations. The Lancet Neurology, 6, 1094–1105. doi:10.1016/S1474-4422(07)70290-9
  • Kamm, C. P., Uitdehaag, B. M., & Polman, C. H. (2014). Multiple sclerosis: Current knowledge and future outlook. European Neurology, 72, 132–141. doi:10.1159/000360528
  • Kayama, H., Okamoto, K., Nishiguchi, S., Yamada, M., Kuroda, T., & Aoyama, T. (2014). Effect of a Kinect-based exercise game on improving executive cognitive performance in community-dwelling elderly: Case control study. Journal of Medical Internet Research, 16, e61. doi:10.2196/jmir.3108
  • Kontschieder, P., Dorn, J., Morrison, C., Corish, R., Zikic, D., Sellen, A. K., & Criminisi, A. (2014). Quantifying progression of multiple sclerosis via classification of depth videos. Proceedings of the MICCAI 2014 Conference on Medical Image Computing and Computer Assisted Intervention Society.
  • Kurtzke, J. F. (1983). Rating neurologic impairment in multiple sclerosis: An expanded disability status scale (EDSS). Neurology, 33, 1444–1452. doi:10.1212/WNL.33.11.1444
  • Leddy, A. L., Crowner, B. E., & Earhart, G. M. (2011). Utility of the Mini-BESTest, BESTest, and BESTest sections for balance assessments in individuals with Parkinson disease. Journal of Neurologic Physical Therapy: JNPT, 35, 90–97. doi:10.1097/NPT.0b013e31821a620c
  • Levine, D., Richards, J., & Whittle, M. (2012). Whittle’s gait analysis (5th ed.)
  • Lowes, L. P., Alfano, L. N., Yetter, B. A., Worthen-Chaudhari, L., Hinchman, W., Savage, J., & Mendell, J. R. (2013). Proof of concept of the ability of the kinect to quantify upper extremity function in dystrophinopathy. PLoS Currents, 5.
  • Lozano-Quilis, J.-A., Gil-Gómez, H., Gil-Gómez, J.-A., Albiol-Pérez, S., Palacios-Navarro, G., Fardoun, H. M., & Mashat, A. S. (2014). Virtual rehabilitation for multiple sclerosis using a kinect-based system: Randomized controlled trial. JMIR Serious Games, 2, e12. doi:10.2196/games.2933
  • Lynch, M. (1985). Discipline and the material form of images: An analysis of scientific visibility. Social Studies of Science, 15, 37–66. doi:10.1177/030631285015001002
  • Lynch, M., & Woolgar, S. (1990). Representation in scientific practice. Cambridge, MA: MIT Press.
  • Mathiowetz, V., Weber, K., Kashman, N., & Volland, G. (1985). Adult norms for the nine hole peg test of finger dexterity. OTJR: Occupation, Participation and Health, 5(1), 24–38.
  • Mentiplay, B. F., Clark, R. A., Mullins, A., Bryant, A. L., Bartold, S., & Paterson, K. (2013). Reliability and validity of the Microsoft Kinect for evaluating static foot posture. Journal of Foot and Ankle Research, 6(1), 14. doi:10.1186/1757-1146-6-14
  • Mentis, H. M., & Taylor, A. S. (2013). Imaging the body: Embodied vision in minimally invasive surgery. Proceedings of the CHI 2013 Conference on Human Factors in Computer Systems. New York, NY: ACM Press.
  • Morrison, C., Corish, R., & Sellen, A. J. (2014). Place-onas: Shared resource for designing body tracking applications. Proceedings of the CHI 2014 Conference on Human Factors in Computer Systems. New York, NY: ACM Press.
  • Morrison, C., Culmer, P., Mentis, H., & Pincus, T. (2014). Vision-based body tracking: Turning kinect into a clinical tool. Disability and Rehabilitation: Assistive Technology. Advance online publication. doi:10.3109/17483107.2014.989419
  • Morrison, C., D’Souza, M., Huckvale, K., Dorn, J. F., Burggraaff, J., Kamm, C. P., & Sellen, A. (2015). Usability and acceptability of ASSESS MS: A system to support the assessment of motor dysfunction in Multiple Sclerosis using depth sensing computer vision. JMIR Human Factors, 2, e11. doi:10.2196/humanfactors.4129
  • Morrison, C., Fitzpatrick, G., & Blackwell, A. (2011). Multi-disciplinary collaboration during ward rounds: Embodied aspects of electronic medical record usage. International Journal of Medical Informatics, 80, e96–111. doi:10.1016/j.ijmedinf.2011.01.007
  • Morrison, C., Smyth, N., Corish, R., O’Hara, K., & Sellen, A. (2014). Collaborating with computer vision systems: An exploration of audio feedback. Proceedings of the DIS 2014 Conference on Designing Interactive Systems. New York, NY: ACM Press.
  • O’Hara, K., Dastur, N., Carrell, T., Gonzalez, G., Sellen, A., Penney, G., & Rouncefield, M. (2014). Touchless interaction in surgery. Communications of the ACM, 57, 70–77. doi:10.1145/2541883.2541899
  • O’Hara, K., Gonzalez, G., Carrell, T., Sellen, A., Penney, G., Mentis, H., & Varnavas, A. (2014). Interactional order and constructed ways of seeing with touchless imaging systems in surgery. Computer Supported Cooperative Work, 23, 299–337. doi:10.1007/s10606-014-9203-4
  • O’Hara, K., Morrison, C., Sellen, A., Craig, C., & Berthouze, N. (in press). Body tracking in healthcare. Morgan and Claypool.
  • Ortiz-Gutiérrez, R., Cano-de-la-Cuerda, R., Galán-Del-Río, F., Alguacil-Diego, I. M., Palacios-Ceña, D., & Miangolarra-Page, J. C. (2013). A telerehabilitation program improves postural control in multiple sclerosis patients: A Spanish preliminary study. International Journal of Environmental Research and Public Health, 10, 5697–5710. doi:10.3390/ijerph10115697
  • Pomplun, M., & Matarić, M. (2000). Evaluation metrics and results of human arm movement imitation. First IEEE-RAS International Conference on Humanoid Robotics (Humanoids).
  • Rudick, R. A., Miller, D., Bethoux, F., Rao, S. M., Lee, J.-C., Stough, D., & Alberts, J. (2014). The Multiple Sclerosis Performance Test (MSPT): An iPad-based disability assessment tool. Journal of Visualized Experiments: JoVE, 88, e51318.
  • Schmidt, R. A., & Wulf, G. (1997). Continuous concurrent feedback degrades skill learning: Implications for training and simulation. Human Factors, 39, 509–525. doi:10.1518/001872097778667979
  • Simon, S. R. (2004). Quantification of human motion: Gait analysis-benefits and limitations to its application to clinical problems. Journal of Biomechanics, 37, 1869–1880. doi:10.1016/j.jbiomech.2004.02.047
  • Spain, R. I., St George, R. J., Salarian, A., Mancini, M., Wagner, J. M., Horak, F. B., & Bourdette, D. (2012). Body-worn motion sensors detect balance and gait deficits in people with multiple sclerosis who have normal walking speed. Gait & Posture, 35, 573–578. doi:10.1016/j.gaitpost.2011.11.026
  • Stone, E. E., & Skubic, M. (2013). Unobtrusive, continuous, in-home gait measurement using the Microsoft Kinect. IEEE Transactions on Bio-Medical Engineering, 60, 2925–2932. doi:10.1109/TBME.2013.2266341
  • Usui, J., Hatayama, H., & Sato, T. (2006). Paravie: Dance entertainment system for everyone to express oneself with movement. Proceedings of the ACE 2006 Conference on Advances in Computer Entertainment.
  • Weikert, M., Motl, R. W., Suh, Y., McAuley, E., & Wynn, D. (2010). Accelerometry in persons with multiple sclerosis: Measurement of physical activity or walking mobility? Journal of the Neurological Sciences, 290, 6–11. doi:10.1016/j.jns.2009.12.021
  • Weyer, T. D., Robert, K., Hariandja, J., Alders, G., & Conin, K. (2012). The Social Maze: A collaborative game to motivate MS patients for upper limb training. Proceedings of the ICEC 2012 International Conference on Entertainment Computing.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.