Abstract
Disabling events such as stroke affect millions of people worldwide, causing a need for efficient and functional rehabilitation therapies in order for patients to regain motor function for reintegration back into their normal lives. Rehabilitation regimes often involve performing exercises that mimic the movements used in activities of daily living and are intended to promote recovery from the physical aspects of an injury. However, alongside physical disability, some patients (e.g., stroke patients) develop cognitive deficiencies that affect their ability to think, plan, and carry out tasks. It is a necessity then to consider rehabilitation techniques that can also accommodate patients with cognitive deficiencies alongside those without. Rehabilitation systems that provide haptic interaction to patients practicing therapy tasks work towards both of these ends; physical interaction can provide strength and coordination training for improving physical condition, and providing additional tactile sensory feedback can make tasks more intuitive for patients with cognitive deficiencies. This chapter introduces novel techniques to incorporate robotics, machine learning, and augmented reality for the purposes of enhancing the haptic interactions provided by therapists to assist patients in their rehabilitation process.
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References
ReJoyce by rehabtronics, https://www.blog.rehabtronics.com/rejoyce
Serious Play Conference, https://seriousplayconf.com/
Abt, C.C.: Serious games. University press of America (1987)
Alankus, G., Proffitt, R., Kelleher, C., Engsberg, J.: Stroke therapy through motion-based games: a case study. ACM Transactions on Accessible Computing (TACCESS) 4(1), 3 (2011)
Albert, S.J., Kesselring, J.: Neurorehabilitation of stroke. Journal of neurology 259(5), 817–832 (2012)
Alexander, N.B., Galecki, A.T., Grenier, M.L., Nyquist, L.V., Hofmeyer, M.R., Grunawalt, J.C., Medell, J.L., Fry-Welch, D.: Task-specific resistance training to improve the ability of activities of daily living–impaired older adults to rise from a bed and from a chair. Journal of the American Geriatrics Society 49(11), 1418–1427 (2001)
Alvarez, J., Alvarez, V., Djaouti, D., Michaud, L.: Serious games: Training & teaching-healthcare-defence & security-information & communication. IDATE, France (2010)
Andaluz, V.H., Salazar, P.J., Escudero V., M., Bustamante D., C., Silva S., M., Quevedo, W., Sánchez, J.S., Espinosa, E.G., Rivas, D.: Virtual reality integration with force feedback in upper limb rehabilitation. In: Advances in Visual Computing. pp. 259–268. Springer International Publishing, Cham (2016)
Argall, B.D., Chernova, S., Veloso, M., Browning, B.: A survey of robot learning from demonstration. Robotics and Autonomous Systems 57(5), 469–483 (2009), http://www.sciencedirect.com/science/article/pii/S0921889008001772
Atashzar, S.F., Shahbazi, M., Tavakoli, M., Patel, R.V.: A computational-model-based study of supervised haptics-enabled therapist-in-the-loop training for upper-limb poststroke robotic rehabilitation. IEEE/ASME Transactions on Mechatronics 23(2), 563–574 (April 2018)
Atashzar, S.F., Jafari, N., Shahbazi, M., Janz, H., Tavakoli, M., Patel, R.V., Adams, K.: Telerobotics-assisted platform for enhancing interaction with physical environments for people living with cerebral palsy. Journal of Medical Robotics Research 2(02), 1740001 (2017)
Atashzar, S.F., Naish, M., Patel, R.V.: 5 active sensorimotor augmentation in robotics-assisted surgical systems. In: Mixed and Augmented Reality in Medicine, pp. 61–81. CRC Press (2018)
Atkeson, C.G., Schaal, S.: Robot learning from demonstration. In: ICML. vol. 97, pp. 12–20. Citeseer (1997)
Badesa, F.J., Morales, R., Garcia-Aracil, N., Sabater, J.M., Casals, A., Zollo, L.: Auto-adaptive robot-aided therapy using machine learning techniques. Computer methods and programs in biomedicine 116(2), 123–130 (2014)
Barzilay, O., Wolf, A.: Adaptive rehabilitation games. Journal of Electromyography and Kinesiology 23(1), 182–189 (2013)
Beckerle, P., Salvietti, G., Unal, R., Prattichizzo, D., Rossi, S., Castellini, C., Hirche, S., Endo, S., Amor, H.B., Ciocarlie, M., Mastrogiovanni, F., Argall, B.D., Bianchi, M.: A human–robot interaction perspective on assistive and rehabilitation robotics. Frontiers in Neurorobotics 11, 24 (2017), https://www.frontiersin.org/article/10.3389/fnbot.2017.00024
Begg, R., Kamruzzaman, J.: A machine learning approach for automated recognition of movement patterns using basic, kinetic and kinematic gait data. Journal of Biomechanics 38(3), 401–408 (2005), http://www.sciencedirect.com/science/article/pii/S0021929004002258
Benjamin, E.J., Blaha, M.J., Chiuve, S.E., Cushman, M., Das, S.R., Deo, R., de Ferranti, S.D., Floyd, J., Fornage, M., Gillespie, C., Isasi, C.R., Jiménez, M.C., Jordan, L.C., Judd, S.E., Lackland, D., Lichtman, J.H., Lisabeth, L., Liu, S., Longenecker, C.T., Mackey, R.H., Matsushita, K., Mozaffarian, D., Mussolino, M.E., Nasir, K., Neumar, R.W., Palaniappan, L., Pandey, D.K., Thiagarajan, R.R., Reeves, M.J., Ritchey, M., Rodriguez, C.J., Roth, G.A., Rosamond, W.D., Sasson, C., Towfighi, A., Tsao, C.W., Turner, M.B., Virani, S.S., Voeks, J.H., Willey, J.Z., Wilkins, J.T., Wu, J.H., Alger, H.M., Wong, S.S., Muntner, P.: Heart disease and stroke statistics—2017 update: A report from the american heart association. Circulation (2017), http://circ.ahajournals.org/content/early/2017/01/25/CIR.0000000000000485
Betker, A.L., Desai, A., Nett, C., Kapadia, N., Szturm, T.: Game-based exercises for dynamic short-sitting balance rehabilitation of people with chronic spinal cord and traumatic brain injuries. Physical therapy 87(10), 1389–1398 (2007)
Blank, A.A., French, J.A., Pehlivan, A.U., O’Malley, M.K.: Current trends in robot-assisted upper-limb stroke rehabilitation: promoting patient engagement in therapy. Current physical medicine and rehabilitation reports 2(3), 184–195 (2014)
Bourbonnais, D., Noven, S.V.: Weakness in patients with hemiparesis. The American journal of occupational therapy 43(5), 313–319 (1989)
Bracewell, R.: Stroke: neuroplasticity and recent approaches to rehabilitation. Journal of Neurology, Neurosurgery & Psychiatry 74(11), 1465–1465 (2003)
Broeren, J., Sunnerhagen, K.S., Rydmark, M.: Haptic virtual rehabilitation in stroke: transferring research into clinical practice. Physical Therapy Reviews 14(5), 322–335 (2009)
Brütsch, K., Koenig, A., Zimmerli, L., Mérillat-Koeneke, S., Riener, R., Jäncke, L., van Hedel, H.J., Meyer-Heim, A.: Virtual reality for enhancement of robot-assisted gait training in children with neurological gait disorders. Journal of rehabilitation medicine 43(6), 493–499 (2011)
Burke, J.W., McNeill, M.D.J., Charles, D.K., Morrow, P.J., Crosbie, J.H., McDonough, S.M.: Augmented reality games for upper-limb stroke rehabilitation. In: 2010 Second International Conference on Games and Virtual Worlds for Serious Applications. pp. 75–78 (March 2010)
Calinon, S., Evrard, P., Gribovskaya, E., Billard, A., Kheddar, A.: Learning collaborative manipulation tasks by demonstration using a haptic interface. In: Advanced Robotics, 2009. ICAR 2009. International Conference on. pp. 1–6. IEEE (2009)
Carignan, C.R., Krebs, H.I.: Telerehabilitation robotics: Bright lights, big future? Journal of Rehabilitation Research and Development 43(5), 695–710 (August 2006), copyright – Copyright Superintendent of Documents Aug/Sep 2006; Document feature – Diagrams; Photographs; Illustrations; Last updated – 2017-11-09; CODEN – JRRDDB
Casas, X., Herrera, G., Coma, I., Fernández, M.: A kinect-based augmented reality system for individuals with autism spectrum disorders. In: Grapp/ivapp. pp. 440–446 (2012)
Colombo, G., Joerg, M., Schreier, R., Dietz, V.: Treadmill training of paraplegic patients using a robotic orthosis. Journal of rehabilitation research and development 37(6), 693–700 (2000)
Colombo, R., Pisano, F., Mazzone, A., Delconte, C., Micera, S., Carrozza, M.C., Dario, P., Minuco, G.: Design strategies to improve patient motivation during robot-aided rehabilitation. Journal of neuroengineering and rehabilitation 4(1), 3 (2007)
Connelly, L., Jia, Y., Toro, M.L., Stoykov, M.E., Kenyon, R.V., Kamper, D.G.: A pneumatic glove and immersive virtual reality environment for hand rehabilitative training after stroke. IEEE Transactions on Neural Systems and Rehabilitation Engineering 18(5), 551–559 (2010)
Correa, A.G.D., de Assis, G.A., d. Nascimento, M., Ficheman, I., d. D. Lopes, R.: Genvirtual: An augmented reality musical game for cognitive and motor rehabilitation. In: 2007 Virtual Rehabilitation. pp. 1–6 (Sept 2007)
Côté, S., Bouchard, S.: Virtual reality exposure for phobias: A critical review. Journal of CyberTherapy & Rehabilitation 1(1), 75–91 (2008)
Cramer, S.C., Sur, M., Dobkin, B.H., O’brien, C., Sanger, T.D., Trojanowski, J.Q., Rumsey, J.M., Hicks, R., Cameron, J., Chen, D., Chen, W.G., Cohen, L.G., Decharms, C., Duffy, C.J., Eden, G.F., Fetz, E.E., Filart, R., Freund, M., Grant, S.J., Haber, S., Kalivas, P.W., Kolb, B., Kramer, A.F., Lynch, M., Mayberg, H.S., McQuillen, P.S., Nitkin, R., Pascual-Leone, A., Reuter-Lorenz, P., Schiff, N., Sharma, A., Shekim, L., Stryker, M., Sullivan, E.V., Vinogradov, S.: Harnessing neuroplasticity for clinical applications. Brain 134(6), 1591–1609 (2011)
Cruz-Neira, C., Sandin, D.J., DeFanti, T.A.: Surround-screen projection-based virtual reality: the design and implementation of the cave. In: Proceedings of the 20th annual conference on Computer graphics and interactive techniques. pp. 135–142. ACM (1993)
Da Gama, A., Chaves, T., Figueiredo, L., Teichrieb, V.: Poster: improving motor rehabilitation process through a natural interaction based system using kinect sensor. In: 3D User Interfaces (3DUI), 2012 IEEE Symposium on. pp. 145–146. IEEE (2012)
Da Gama, A.E.F., Chaves, T.M., Figueiredo, L.S., Baltar, A., Meng, M., Navab, N., Teichrieb, V., Fallavollita, P.: Mirrarbilitation: A clinically-related gesture recognition interactive tool for an ar rehabilitation system. Computer methods and programs in biomedicine 135, 105–114 (2016)
Damush, T.M., Plue, L., Bakas, T., Schmid, A., Williams, L.S.: Barriers and facilitators to exercise among stroke survivors. Rehabilitation nursing 32(6), 253–262 (2007)
Deutsch, J.E., Borbely, M., Filler, J., Huhn, K., Guarrera-Bowlby, P.: Use of a low-cost, commercially available gaming console (wii) for rehabilitation of an adolescent with cerebral palsy. Physical therapy 88(10), 1196–1207 (2008)
Deutsch, J.E., Latonio, J., Burdea, G.C., Boian, R.: Post-stroke rehabilitation with the rutgers ankle system: a case study. Presence: Teleoperators & Virtual Environments 10(4), 416–430 (2001)
Djaouti, D., Alvarez, J., Jessel, J.P.: Classifying serious games: the g/p/s model. In: Handbook of research on improving learning and motivation through educational games: Multidisciplinary approaches, pp. 118–136. IGI Global (2011)
Van der Eerden, W., Otten, E., May, G., Even-Zohar, O.: Caren-computer assisted rehabilitation environment. Medicine Meets Virtual Reality: The Convergence of Physical & Informational Technologies: Options for a New Era in Healthcare 62, 373–378 (1999)
Ekberg, K.: Workplace changes in successful rehabilitation. Journal of Occupational Rehabilitation 5(4), 253–269 (1995)
Feigin, V.L., Norrving, B., Mensah, G.A.: Global burden of stroke. Circulation research 120(3), 439–448 (2017)
FGTeam: Rejoyce speeds up upper extremity recovery post stroke (January 2015), https://www.fitness-gaming.com/news/health-and-rehab/rejoyce-speeds-up-upper-extremity-recovery-post-stroke.html
Flynn, S., Palma, P., Bender, A.: Feasibility of using the sony playstation 2 gaming platform for an individual poststroke: a case report. Journal of neurologic physical therapy 31(4), 180–189 (2007)
Fong, J., Rouhani, H., Tavakoli, M.: A therapist-taught robotic system for assistance during gait therapy targeting foot drop. IEEE Robotics and Automation Letters 4(2), 407–413 (2019)
Fong, J., Tavakoli, M.: Kinesthetic teaching of a therapist’s behavior to a rehabilitation robot. In: 2018 International Symposium on Medical Robotics (ISMR). pp. 1–6 (March 2018)
Garate, V.R., Parri, A., Yan, T., Munih, M., Lova, R.M., Vitiello, N., Ronsse, R.: Experimental validation of motor primitive-based control for leg exoskeletons during continuous multi-locomotion tasks. Frontiers in Neurorobotics 11, 15 (2017)
Garcia, A., Andre, N., Bell Boucher, D., Roberts-South, A., Jog, M., Katchabaw, M.: Immersive Augmented Reality for Parkinson Disease Rehabilitation, pp. 445–469. Springer Berlin Heidelberg, Berlin, Heidelberg (2014), https://doi.org/10.1007/978-3-642-54816-1_22
Giorgino, T., Lorussi, F., De Rossi, D., Quaglini, S.: Posture classification via wearable strain sensors for neurological rehabilitation. In: 2006 International Conference of the IEEE Engineering in Medicine and Biology Society. pp. 6273–6276. IEEE (2006)
Gladstone, D.J., Danells, C.J., Black, S.E.: The fugl-meyer assessment of motor recovery after stroke: a critical review of its measurement properties. Neurorehabilitation and neural repair 16(3), 232–240 (2002)
Göbel, S., Hardy, S., Wendel, V., Mehm, F., Steinmetz, R.: Serious games for health: personalized exergames. In: Proceedings of the 18th ACM international conference on Multimedia. pp. 1663–1666. ACM (2010)
Gowland, C., Stratford, P., Ward, M., Moreland, J., Torresin, W., Van Hullenaar, S., Sanford, J., Barreca, S., Vanspall, B., Plews, N.: Measuring physical impairment and disability with the chedoke-mcmaster stroke assessment. Stroke 24(1), 58–63 (1993)
Grahn, B., Ekdahl, C., Borgquist, L.: Motivation as a predictor of changes in quality of life and working ability in multidisciplinary rehabilitation. Disability and Rehabilitation 22(15), 639–654 (2000)
Gribovskaya, E., Khansari-Zadeh, S.M., Billard, A.: Learning non-linear multivariate dynamics of motion in robotic manipulators. The International Journal of Robotics Research 30(1), 80–117 (2011)
Gui, K., Liu, H., Zhang, D.: Toward multimodal human–robot interaction to enhance active participation of users in gait rehabilitation. IEEE Transactions on Neural Systems and Rehabilitation Engineering 25(11), 2054–2066 (2017)
Guidali, M., Duschau-Wicke, A., Broggi, S., Klamroth-Marganska, V., Nef, T., Riener, R.: A robotic system to train activities of daily living in a virtual environment. Medical & Biological Engineering & Computing 49(10), 1213 (July 2011), https://doi.org/10.1007/s11517-011-0809-0
Hansen, M., Haugland, M., Sinkjær, T., Donaldson, N.: Real time foot drop correction using machine learning and natural sensors. Neuromodulation: Technology at the Neural Interface 5(1), 41–53 (2002), https://onlinelibrary.wiley.com/doi/abs/10.1046/j.1525-1403.2002._2008.x
Heart and Stroke Foundation of Canada: Getting to the heart of the matter: solving cardiovascular disease through research (2015), http://www.heartandstroke.ca/-/media/pdf-files/canada/2017-heart-month/heartandstroke-reportonhealth-2015.ashx?la=en
Hillman, M.: 2 rehabilitation robotics from past to present–a historical perspective. In: Advances in Rehabilitation Robotics, pp. 25–44. Springer (2004)
Hoffman, H.G., Patterson, D.R., Carrougher, G.J.: Use of virtual reality for adjunctive treatment of adult burn pain during physical therapy: a controlled study. The Clinical journal of pain 16(3), 244–250 (2000)
Hogan, N., Krebs, H.I., Charnnarong, J., Srikrishna, P., Sharon, A.: Mit-manus: a workstation for manual therapy and training. i. In: Robot and Human Communication, 1992. Proceedings., IEEE International Workshop on. pp. 161–165. IEEE (1992)
Intercollegiate Stroke Working Party: National clinical guideline for stroke, vol. 20083. Citeseer (2012)
Iosa, M., Morone, G., Cherubini, A., Paolucci, S.: The three laws of neurorobotics: A review on what neurorehabilitation robots should do for patients and clinicians. Journal of Medical and Biological Engineering 36(1), 1–11 (Feb 2016), https://doi.org/10.1007/s40846-016-0115-2
Jadhav, C., Krovi, V.: A low-cost framework for individualized interactive telerehabilitation. In: Engineering in Medicine and Biology Society, 2004. IEMBS’04. 26th Annual International Conference of the IEEE. vol. 2, pp. 3297–3300. IEEE (2004)
Jaffe, D.L., Brown, D.A., Pierson-Carey, C.D., Buckley, E.L., Lew, H.L.: Stepping over obstacles to improve walking in individuals with poststroke hemiplegia. Journal of Rehabilitation Research & Development 41(3A), 283–292 (2004)
Johnson, M.J., Loureiro, R.C., Harwin, W.S.: Collaborative tele-rehabilitation and robot-mediated therapy for stroke rehabilitation at home or clinic. Intelligent Service Robotics 1(2), 109–121 (2008)
Juan, M.C., Calatrava, J.: An augmented reality system for the treatment of phobia to small animals viewed via an optical see-through hmd: comparison with a similar system viewed via a video see-through hmd. International Journal of Human-Computer Interaction 27(5), 436–449 (2011)
Kahn, L.E., Lum, P.S., Rymer, W.Z., Reinkensmeyer, D.J.: Robot-assisted movement training for the stroke-impaired arm: Does it matter what the robot does? Journal of rehabilitation research and development 43(5) (2014)
Kairy, D., Lehoux, P., Vincent, C., Visintin, M.: A systematic review of clinical outcomes, clinical process, healthcare utilization and costs associated with telerehabilitation. Disability and rehabilitation 31(6), 427–447 (2009)
Kaminer, C., LeBras, K., McCall, J., Phan, T., Naud, P., Teodorescu, M., Kurniawan, S.: An immersive physical therapy game for stroke survivors. In: Proceedings of the 16th International ACM SIGACCESS Conference on Computers & Accessibility. pp. 299–300. ASSETS ’14, ACM, New York, NY, USA (2014), http://doi.acm.org.login.ezproxy.library.ualberta.ca/10.1145/2661334.2661340
Khademi, M., Hondori, H.M., Dodakian, L., Cramer, S., Lopes, C.V.: Comparing “pick and place” task in spatial Augmented Reality versus non-immersive Virtual Reality for rehabilitation setting. Conf Proc IEEE Eng Med Biol Soc 2013, 4613–4616 (2013)
Khademi, M., Hondori, H.M., Lopes, C.V., Dodakian, L., Cramer, S.C.: Haptic augmented reality to monitor human arm’s stiffness in rehabilitation. In: 2012 IEEE-EMBS Conference on Biomedical Engineering and Sciences. pp. 892–895 (Dec 2012)
Khalili, D., Zomlefer, M.: An intelligent robotic system for rehabilitation of joints and estimation of body segment parameters. IEEE transactions on biomedical engineering 35(2), 138–146 (1988)
Khansari-Zadeh, S.M., Billard, A.: Learning stable nonlinear dynamical systems with gaussian mixture models. IEEE Transactions on Robotics 27(5), 943–957 (Oct 2011)
Kostov, A., Andrews, B.J., Popovic, D.B., Stein, R.B., Armstrong, W.W.: Machine learning in control of functional electrical stimulation systems for locomotion. IEEE Transactions on Biomedical Engineering 42(6), 541–551 (1995)
Krebs, H.I., Hogan, N., Aisen, M.L., Volpe, B.T.: Robot-aided neurorehabilitation. IEEE transactions on rehabilitation engineering 6(1), 75–87 (1998)
Langhammer, B., Stanghelle, J.K.: Bobath or motor relearning programme? a comparison of two different approaches of physiotherapy in stroke rehabilitation: a randomized controlled study. Clinical rehabilitation 14(4), 361–369 (2000)
Lauretti, C., Cordella, F., Guglielmelli, E., Zollo, L.: Learning by demonstration for planning activities of daily living in rehabilitation and assistive robotics. IEEE Robotics and Automation Letters 2(3), 1375–1382 (July 2017)
Legg, L., Drummond, A., Leonardi-Bee, J., Gladman, J.R., Corr, S., Donkervoort, M., Edmans, J., Gilbertson, L., Jongbloed, L., Logan, P., Sackley, C., Walker, M., Langhorne, P.: Occupational therapy for patients with problems in personal activities of daily living after stroke: systematic review of randomised trials. BMJ (2007), http://www.bmj.com/content/early/2006/12/31/bmj.39343.466863.55
Leightley, D., Darby, J., Li, B., McPhee, J.S., Yap, M.H.: Human activity recognition for physical rehabilitation. In: 2013 IEEE International Conference on Systems, Man, and Cybernetics. pp. 261–266. IEEE (2013)
LeMoyne, R., Mastroianni, T., Hessel, A., Nishikawa, K.: Ankle rehabilitation system with feedback from a smartphone wireless gyroscope platform and machine learning classification. In: 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA). pp. 406–409. IEEE (2015)
Lenze, E.J., Munin, M.C., Quear, T., Dew, M.A., Rogers, J.C., Begley, A.E., Reynolds III, C.F.: Significance of poor patient participation in physical and occupational therapy for functional outcome and length of stay. Archives of physical medicine and rehabilitation 85(10), 1599–1601 (2004)
Li, W.J., Hsieh, C.Y., Lin, L.F., Chu, W.C.: Hand gesture recognition for post-stroke rehabilitation using leap motion. In: 2017 International Conference on Applied System Innovation (ICASI). pp. 386–388. IEEE (2017)
Van der Loos, H.M., Reinkensmeyer, D.J., Guglielmelli, E.: Rehabilitation and Health Care Robotics, pp. 1685–1728. Springer International Publishing, Cham (2016), https://doi.org/10.1007/978-3-319-32552-1_64
Lum, P., Reinkensmeyer, D., Mahoney, R., Rymer, W.Z., Burgar, C.: Robotic devices for movement therapy after stroke: Current status and challenges to clinical acceptance. Topics in Stroke Rehabilitation 8(4), 40–53 (2002), https://doi.org/10.1310/9KFM-KF81-P9A4-5WW0, pMID: 14523729
Lum, P.S., Burgar, C.G., Shor, P.C.: Evidence for improved muscle activation patterns after retraining of reaching movements with the mime robotic system in subjects with post-stroke hemiparesis. IEEE Transactions on Neural Systems and Rehabilitation Engineering 12(2), 186–194 (2004)
Lum, P.S., Burgar, C.G., Shor, P.C., Majmundar, M., Van der Loos, M.: Robot-assisted movement training compared with conventional therapy techniques for the rehabilitation of upper-limb motor function after stroke. Archives of physical medicine and rehabilitation 83(7), 952–959 (2002)
Luo, X., Kline, T., Fischer, H.C., Stubblefield, K.A., Kenyon, R.V., Kamper, D.G.: Integration of augmented reality and assistive devices for post-stroke hand opening rehabilitation. In: 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference. pp. 6855–6858 (2005)
Ma, M., McNeill, M., Charles, D., McDonough, S., Crosbie, J., Oliver, L., McGoldrick, C.: Adaptive virtual reality games for rehabilitation of motor disorders. In: International Conference on Universal Access in Human-Computer Interaction. pp. 681–690. Springer (2007)
Maaref, M., Rezazadeh, A., Shamaei, K., Ocampo, R., Mahdi, T.: A bicycle cranking model for assist-as-needed robotic rehabilitation therapy using learning from demonstration. IEEE Robotics and Automation Letters 1(2), 653–660 (July 2016)
Maclean, N., Pound, P., Wolfe, C., Rudd, A.: A critical review of the concept of patient motivation in the literature on physical rehabilitation. Soc Sci Med 50(4), 495–506 (2000)
Maclean, N., Pound, P., Wolfe, C., Rudd, A.: Qualitative analysis of stroke patients’ motivation for rehabilitation. Bmj 321(7268), 1051–1054 (2000)
Maier, M., Ballester, B.R., Duarte, E., Duff, A., Verschure, P.F.: Social integration of stroke patients through the multiplayer rehabilitation gaming system. In: International Conference on Serious Games. pp. 100–114. Springer (2014)
Mark, V.W., Taub, E.: Constraint-induced movement therapy for chronic stroke hemiparesis and other disabilities. Restorative neurology and neuroscience 22(3-5), 317–336 (2004)
Martínez, C., Tavakoli, M.: Learning and robotic imitation of therapist’s motion and force for post-disability rehabilitation. In: Systems, Man, and Cybernetics (SMC), 2017 IEEE International Conference on. pp. 2225–2230. IEEE (2017)
McComas, A., Sica, R., Upton, A., Aguilera, N.: Functional changes in motoneurones of hemiparetic patients. Journal of Neurology, Neurosurgery & Psychiatry 36(2), 183–193 (1973)
McLeod, A., Bochniewicz, E.M., Lum, P.S., Holley, R.J., Emmer, G., Dromerick, A.W.: Using wearable sensors and machine learning models to separate functional upper extremity use from walking-associated arm movements. Archives of physical medicine and rehabilitation 97(2), 224–231 (2016)
Mehrholz, J., Hädrich, A., Platz, T., Kugler, J., Pohl, M.: Electromechanical and robot-assisted arm training for improving generic activities of daily living, arm function, and arm muscle strength after stroke. Cochrane database of systematic reviews (6) (2012)
Milgram, P., Kishino, F.: A taxonomy of mixed reality visual displays. IEICE TRANSACTIONS on Information and Systems 77(12), 1321–1329 (1994)
Mimouni, M., Cismariu-Potash, K., Ratmansky, M., Shaklai, S., Amir, H., Mimouni-Bloch, A.: Trends in physical medicine and rehabilitation publications over the past 16 years. Archives of Physical Medicine and Rehabilitation 97(6), 1030–1033 (2016), http://www.sciencedirect.com/science/article/pii/S0003999315014100
Mirelman, A., Bonato, P., Deutsch, J.E.: Effects of training with a robot-virtual reality system compared with a robot alone on the gait of individuals after stroke. Stroke 40(1), 169–174 (2009)
Mosey, A.C.: Psychosocial components of occupational therapy. Lippincott Williams & Wilkins (1986)
Mousavi Hondori, H., Khademi, M., Dodakian, L., Cramer, S.C., Lopes, C.V.: A Spatial Augmented Reality rehab system for post-stroke hand rehabilitation. Stud Health Technol Inform 184, 279–285 (2013)
Murphy, M.A., Persson, H.C., Danielsson, A., Broeren, J., Lundgren-Nilsson, Å., Sunnerhagen, K.S.: Salgot-s troke a rm l ongitudinal study at the university of got henburg, prospective cohort study protocol. BMC neurology 11(1), 56 (2011)
Najafi, M., Adams, K., Tavakoli, M.: Robotic learning from demonstration of therapist’s time-varying assistance to a patient in trajectory-following tasks. In: Rehabilitation Robotics (ICORR), 2017 International Conference on. pp. 888–894. IEEE (2017)
Novak, D., Nagle, A., Keller, U., Riener, R.: Increasing motivation in robot-aided arm rehabilitation with competitive and cooperative gameplay. Journal of neuroengineering and rehabilitation 11(1), 64 (2014)
Ocampo, R., Tavakoli, M.: Improving user performance in haptics-based rehabilitation exercises by colocation of user’s visual and motor axes via a three-dimensional augmented-reality display. IEEE Robotics and Automation Letters 4(2), 438–444 (2019)
Ocampo, R., Tavakoli, M.: Visual-haptic colocation in robotic rehabilitation exercises using a 2d augmented-reality display. In: 2019 International Symposium on Medical Robotics (ISMR). pp. 1–7 (April 2019)
Octavia, J.R., Coninx, K.: Adaptive personalized training games for individual and collaborative rehabilitation of people with multiple sclerosis. BioMed research international 2014 (2014)
Pandyan, A., Johnson, G., Price, C., Curless, R., Barnes, M., Rodgers, H.: A review of the properties and limitations of the ashworth and modified ashworth scales as measures of spasticity. Clinical rehabilitation 13(5), 373–383 (1999)
Pardini, H.: VR Vaccine, https://www.adforum.com/award-organization/6650183/showcase/2017/ad/34544861
Parton, A., Malhotra, P., Husain, M.: Hemispatial neglect. Journal of Neurology, Neurosurgery & Psychiatry 75(1), 13–21 (2004)
Pehlivan, A.U., Losey, D.P., O’Malley, M.K.: Minimal assist-as-needed controller for upper limb robotic rehabilitation. IEEE Transactions on Robotics 32(1), 113–124 (2016)
Peternel, L., Petrič, T., Oztop, E., Babič, J.: Teaching robots to cooperate with humans in dynamic manipulation tasks based on multi-modal human-in-the-loop approach. Autonomous Robots 36(1-2), 123–136 (January 2014), https://doi.org/10.1007/s10514-013-9361-0
Public Health Agency of Canada: Tracking heart disease and stroke in canada 2009, https://www.canada.ca/en/public-health/services/reports-publications/2009-tracking-heart-disease-stroke-canada.html
Reinkensmeyer, D.J., Kahn, L.E., Averbuch, M., McKenna-Cole, A., Schmit, B.D., Rymer, W.Z.: Understanding and treating arm movement impairment after chronic brain injury: progress with the arm guide. Journal of Rehabilitation Research and Development 37(6), 653–662 (2014)
Reinkensmeyer, D.J., Pang, C.T., Nessler, J.A., Painter, C.C.: Web-based telerehabilitation for the upper extremity after stroke. IEEE transactions on neural systems and rehabilitation engineering 10(2), 102–108 (2002)
Ricker, J.H., Rosenthal, M., Garay, E., DeLuca, J., Germain, A., Abraham-Fuchs, K., Schmidt, K.U.: Telerehabilitation needs: a survey of persons with acquired brain injury. The Journal of Head Trauma Rehabilitation 17(3), 242–250 (2002)
Robitaille, N., Jackson, P.L., Hébert, L.J., Mercier, C., Bouyer, L.J., Fecteau, S., Richards, C.L., McFadyen, B.J.: A virtual reality avatar interaction (vrai) platform to assess residual executive dysfunction in active military personnel with previous mild traumatic brain injury: proof of concept. Disability and Rehabilitation: Assistive Technology 12(7), 758–764 (2017)
Sandlund, M., McDonough, S., Häger-Ross, C.: Interactive computer play in rehabilitation of children with sensorimotor disorders: a systematic review. Developmental Medicine & Child Neurology 51(3), 173–179 (2009)
Sawyer, B., Rejeski, D.: Serious games: Improving public policy through game-based learning and simulation (2002)
Shahbazi, M., Atashzar, S.F., Tavakoli, M., Patel, R.V.: Position-force domain passivity of the human arm in telerobotic systems. IEEE/ASME Transactions on Mechatronics 23(2), 552–562 (2018)
Sharifi, M., Behzadipour, S., Salarieh, H., Tavakoli, M.: Cooperative modalities in robotic tele-rehabilitation using nonlinear bilateral impedance control. Control Engineering Practice 67, 52–63 (2017)
Shilling, R., Zyda, M., Wardynski, E.C.: Introducing emotion into military simulation and videogame design: America’s army operations and virte. In: Proceedings of the GameOn Conference. vol. 3 (2002)
Shirzad, N., Van der Loos, H.M.: Adaptation of task difficulty in rehabilitation exercises based on the user’s motor performance and physiological responses. In: 2013 IEEE 13th International Conference on Rehabilitation Robotics (ICORR). pp. 1–6. IEEE (2013)
Sietsema, J.M., Nelson, D.L., Mulder, R.M., Mervau-Scheidel, D., White, B.E.: The use of a game to promote arm reach in persons with traumatic brain injury. American Journal of Occupational Therapy 47(1), 19–24 (1993)
Söderback, I.: International handbook of occupational therapy interventions. Springer (2009)
Squeri, V., Basteris, A., Sanguineti, V.: Adaptive regulation of assistance ‘as needed’ in robot-assisted motor skill learning and neuro-rehabilitation. In: 2011 IEEE International conference on rehabilitation robotics. pp. 1–6. IEEE (2011)
Steele, E., Grimmer, K., Thomas, B., Mulley, B., Fulton, I., Hoffman, H.: Virtual reality as a pediatric pain modulation technique: a case study. Cyberpsychology & Behavior 6(6), 633–638 (2003)
Strazzulla, I., Nowak, M., Controzzi, M., Cipriani, C., Castellini, C.: Online bimanual manipulation using surface electromyography and incremental learning. IEEE Transactions on Neural Systems and Rehabilitation Engineering 25(3), 227–234 (2017)
Swapp, D., Pawar, V., Loscos, C.: Interaction with co-located haptic feedback in virtual reality. Virtual Reality 10(1), 24–30 (May 2006), https://doi.org/10.1007/s10055-006-0027-5
Tao, R.: Haptic teleoperation based rehabilitation systems for task-oriented therapy. Master’s thesis, University of Alberta, Edmonton, Canada (2014)
Thompson, D., Baranowski, T., Buday, R., Baranowski, J., Thompson, V., Jago, R., Griffith, M.J.: Serious video games for health: How behavioral science guided the development of a serious video game. Simulation & gaming 41(4), 587–606 (2010)
Trojan, J., Diers, M., Fuchs, X., Bach, F., Bekrater-Bodmann, R., Foell, J., Kamping, S., Rance, M., Maass, H., Flor, H.: An augmented reality home-training system based on the mirror training and imagery approach. Behav Res Methods 46(3), 634–640 (Sep 2014)
Van Krevelen, D., Poelman, R.: A survey of augmented reality technologies, applications and limitations. International journal of virtual reality 9(2), 1 (2010)
Vidrios-Serrano, C., Bonilla, I., Vigueras-Gómez, F., Mendoza, M.: Development of a haptic interface for motor rehabilitation therapy using augmented reality. In: 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). pp. 1156–1159 (Aug 2015)
Vieira, J., Sousa, M., Arsénio, A., Jorge, J.: Augmented reality for rehabilitation using multimodal feedback. In: Proceedings of the 3rd 2015 Workshop on ICTs for improving Patients Rehabilitation Research Techniques. pp. 38–41. ACM (2015)
Voelker, R.: Rehabilitation medicine welcomes a robotic revolution. JAMA 294(10), 1191–1195 (2005), https://doi.org/10.1001/jama.294.10.1191
Volpe, B., Krebs, H., Hogan, N., Edelsteinn, L., Diels, C., Aisen, M.: Robot training enhanced motor outcome in patients with stroke maintained over 3 years. Neurology 53(8), 1874–1874 (1999), http://n.neurology.org/content/53/8/1874
Williams, B., Chang, A., Landefeld, C.S., Ahalt, C., Conant, R., Chen, H.: Current diagnosis and treatment: geriatrics 2E. McGraw Hill Professional (2014)
Williams, D.J., Krebs, H.I., Hogan, N.: A robot for wrist rehabilitation. In: Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE. vol. 2, pp. 1336–1339. IEEE (2001)
Wolbrecht, E.T., Chan, V., Reinkensmeyer, D.J., Bobrow, J.E.: Optimizing compliant, model-based robotic assistance to promote neurorehabilitation. IEEE Transactions on Neural Systems and Rehabilitation Engineering 16(3), 286–297 (2008)
Worsnopp, T., Peshkin, M., Colgate, J., Kamper, D.: An actuated finger exoskeleton for hand rehabilitation following stroke. In: Rehabilitation Robotics, 2007. ICORR 2007. IEEE 10th International Conference on. pp. 896–901. IEEE (2007)
Wright, W., Bogost, I.: Persuasive games: The expressive power of videogames. Mit Press (2007)
Yanco, H.A., Haigh, K.Z.: Automation as caregiver: A survey of issues and technologies. Am. Assoc. Artif. Intell 2, 39–53 (2002)
Yeh, S.C., Hwang, W.Y., Huang, T.C., Liu, W.K., Chen, Y.T., Hung, Y.P.: A study for the application of body sensing in assisted rehabilitation training. In: 2012 International Symposium on Computer, Consumer and Control. pp. 922–925 (June 2012)
Yeh, S.C., Huang, M.C., Wang, P.C., Fang, T.Y., Su, M.C., Tsai, P.Y., Rizzo, A.: Machine learning-based assessment tool for imbalance and vestibular dysfunction with virtual reality rehabilitation system. Computer methods and programs in biomedicine 116(3), 311–318 (2014)
Yelnik, A.P., Lebreton, F.O., Bonan, I.V., Colle, F.M., Meurin, F.A., Guichard, J.P., Vicaut, E.: Perception of verticality after recent cerebral hemispheric stroke. Stroke 33(9), 2247–2253 (2002)
Zhu, M., Zhang, Z., Hirdes, J.P., Stolee, P.: Using machine learning algorithms to guide rehabilitation planning for home care clients. BMC medical informatics and decision making 7(1), 41 (2007)
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Fong, J., Ocampo, R., Tavakoli, M. (2020). Intelligent Robotics and Immersive Displays for Enhancing Haptic Interaction in Physical Rehabilitation Environments. In: McDaniel, T., Panchanathan, S. (eds) Haptic Interfaces for Accessibility, Health, and Enhanced Quality of Life. Springer, Cham. https://doi.org/10.1007/978-3-030-34230-2_10
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