Social Human-Robot Interaction for Gait Rehabilitation
Robot-assisted therapy for gait rehabilitation of patients with neurological disorders usually combines a body weight support system with a treadmill system. Lokomatis oneof the most useddevicesforgait rehabilitation. This device allows therapists to focus on the patient and the therapy. However, th...
- Autores:
-
Céspedes, Nathalia
Múnera, Marcela
Gómez, Catalina
Cifuentes, Carlos A.
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2020
- Institución:
- Escuela Colombiana de Ingeniería Julio Garavito
- Repositorio:
- Repositorio Institucional ECI
- Idioma:
- eng
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- oai:repositorio.escuelaing.edu.co:001/3309
- Acceso en línea:
- https://repositorio.escuelaing.edu.co/handle/001/3309
https://repositorio.escuelaing.edu.co/
- Palabra clave:
- Rehabilitación médica
Medical rehabilitation
Robótica médica
Robotics in medicine
Tecnología médica
Medical technology
Neurología - Rehabilitación
Neurology - Rehabilitation
Gaitrehabilitación
Interacción humano-robot
Biorretroalimentación
Robótica de asistencia social
Gaitrehabilitation
Lokomat
Human-robot interaction
Biofeedback
Socially assistive robotics
- Rights
- closedAccess
- License
- http://purl.org/coar/access_right/c_14cb
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dc.title.eng.fl_str_mv |
Social Human-Robot Interaction for Gait Rehabilitation |
title |
Social Human-Robot Interaction for Gait Rehabilitation |
spellingShingle |
Social Human-Robot Interaction for Gait Rehabilitation Rehabilitación médica Medical rehabilitation Robótica médica Robotics in medicine Tecnología médica Medical technology Neurología - Rehabilitación Neurology - Rehabilitation Gaitrehabilitación Interacción humano-robot Biorretroalimentación Robótica de asistencia social Gaitrehabilitation Lokomat Human-robot interaction Biofeedback Socially assistive robotics |
title_short |
Social Human-Robot Interaction for Gait Rehabilitation |
title_full |
Social Human-Robot Interaction for Gait Rehabilitation |
title_fullStr |
Social Human-Robot Interaction for Gait Rehabilitation |
title_full_unstemmed |
Social Human-Robot Interaction for Gait Rehabilitation |
title_sort |
Social Human-Robot Interaction for Gait Rehabilitation |
dc.creator.fl_str_mv |
Céspedes, Nathalia Múnera, Marcela Gómez, Catalina Cifuentes, Carlos A. |
dc.contributor.author.none.fl_str_mv |
Céspedes, Nathalia Múnera, Marcela Gómez, Catalina Cifuentes, Carlos A. |
dc.contributor.researchgroup.spa.fl_str_mv |
GiBiome |
dc.subject.armarc.none.fl_str_mv |
Rehabilitación médica Medical rehabilitation Robótica médica Robotics in medicine Tecnología médica Medical technology Neurología - Rehabilitación Neurology - Rehabilitation |
topic |
Rehabilitación médica Medical rehabilitation Robótica médica Robotics in medicine Tecnología médica Medical technology Neurología - Rehabilitación Neurology - Rehabilitation Gaitrehabilitación Interacción humano-robot Biorretroalimentación Robótica de asistencia social Gaitrehabilitation Lokomat Human-robot interaction Biofeedback Socially assistive robotics |
dc.subject.proposal.spa.fl_str_mv |
Gaitrehabilitación Interacción humano-robot Biorretroalimentación Robótica de asistencia social |
dc.subject.proposal.eng.fl_str_mv |
Gaitrehabilitation Lokomat Human-robot interaction Biofeedback Socially assistive robotics |
description |
Robot-assisted therapy for gait rehabilitation of patients with neurological disorders usually combines a body weight support system with a treadmill system. Lokomatis oneof the most useddevicesforgait rehabilitation. This device allows therapists to focus on the patient and the therapy. However, this therapy session is based on multi-tasking processes, which are often difficult for a therapist to manage. In this work, a Socially Assistive Robot (SAR) was integrated into a neurorehabilitation programasacollaboratoragenttopromotepatientengagement and performance during the therapy. This short-term study presents the effects comparing the social robot condition and control condition with a group of four neurological patients using repeated measurementdesign. As a remarkable result, patients improved thoracic 18.44% and cervical 32.23%postureonaveragewithSARassistance.Thisstudy demonstrated the feasibility of the integration of a social robot as a complement of gait rehabilitation programs. |
publishDate |
2020 |
dc.date.issued.none.fl_str_mv |
2020-06 |
dc.date.accessioned.none.fl_str_mv |
2024-10-11T15:34:51Z |
dc.date.available.none.fl_str_mv |
2024-10-11T15:34:51Z |
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Artículo de revista |
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http://purl.org/coar/resource_type/c_6501 |
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1534-4320 |
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1534-4320 |
dc.identifier.instname.spa.fl_str_mv |
Universidad Escuela Colombiana de Ingeniería Julio Garavito |
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Repositorio Digital |
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identifier_str_mv |
1534-4320 Universidad Escuela Colombiana de Ingeniería Julio Garavito Repositorio Digital |
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https://repositorio.escuelaing.edu.co/handle/001/3309 https://repositorio.escuelaing.edu.co/ |
dc.language.iso.spa.fl_str_mv |
eng |
language |
eng |
dc.relation.citationedition.spa.fl_str_mv |
Vol. 28 No. 6 June 2020 |
dc.relation.citationendpage.spa.fl_str_mv |
1307 |
dc.relation.citationissue.spa.fl_str_mv |
6 |
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dc.relation.citationvolume.spa.fl_str_mv |
28 |
dc.relation.ispartofjournal.eng.fl_str_mv |
IEEE TRANSACTIONS ON NEURALSYSTEMS AND REHABILITATION ENGINEERING |
dc.relation.references.spa.fl_str_mv |
T. Dua, A. Janca, and A. Muscetta, “Public health principles and neurological disorders,” Neurological Disorders: Public Health Challenges, no. 2, pp. 7–25, 2006. WHO What are Neurological Disorders? WHO, Geneva, Switzerland, 2016. S. B. O’Sullivan, T. J. Schmitz, and G. D. Fulk, Physical Rehabilitation. Philadelphia, PA, USA: F. A. Davis Company, 2014. M. Visintin, H. Barbeau, N. Korner-Bitensky, and N. E. Mayo, “A new approach to retrain gait in stroke patients through body weight support and treadmill stimulation,” Stroke, vol. 29, no. 6, pp. 1122–1128, 1998. World Health Organization. Adherence to Long-Term Therapies— Evidence for Action: Section I—Setting the Scene: Chapter I—Defining Adherence: 1. What is Adherence? Accessed: Sep. 17, 2018. [Online]. Available: http://apps.who.int/medicinedocs/es/d/Js4883e/6.html S. Fisher, L. Lucas, and T. A. Thrasher, “Robot-assisted gait training for patients with hemiparesis due to stroke,” Topics Stroke Rehabil., vol. 18, no. 3, pp. 269–276, May 2011. S. Hussain, S. Q. Xie, and G. Liu, “Robot assisted treadmill training: Mechanisms and training strategies,” Med. Eng. Phys., vol. 33, no. 5, pp. 527–533, Jun. 2011. C. Werner, S. von Frankenberg, T. Treig, M. Konrad, and S. Hesse, “Treadmill training with partial body weight support and an electromechanical gait trainer for restoration of gait in subacute stroke patients: A randomized crossover study,” Stroke, vol. 33, no. 12, pp. 2895–2901, Dec. 2002. D. A. Winter, “Biomechanics of normal and pathological gait: Implications for understanding human locomotor control,” J. Motor Behav., vol. 21, no. 4, pp. 337–355, Dec. 1989. Lokomat-Hocoma. Accessed: Jan. 20, 2019. [Online]. Available: https://www.hocoma.com/solutions/lokomat/ B. Husemann, F. Müller, C. Krewer, S. Heller, and E. Koenig, “Effects of locomotion training with assistance of a robot-driven gait orthosis in hemiparetic patients after stroke: A randomized controlled pilot study,” Stroke, vol. 38, no. 2, pp. 349–354, Feb. 2007. C. Krewer, F. Müller, B. Husemann, S. Heller, J. Quintern, and E. Koenig, “The influence of different lokomat walking conditions on the energy expenditure of hemiparetic patients and healthy subjects,” Gait Posture, vol. 26, no. 3, pp. 372–377, Sep. 2007. A. Mayr, M. Kofler, E. Quirbach, H. Matzak, K. Fröhlich, and L. Saltuari, “Prospective, blinded, randomized crossover study of gait rehabilitation in stroke patients using the lokomat gait orthosis,” Neurorehabilitation Neural Repair, vol. 21, no. 4, pp. 307–314, Jul. 2007. D.-H. Bang and W.-S. Shin, “Effects of robot-assisted gait training on spatiotemporal gait parameters and balance in patients with chronic stroke: A randomized controlled pilot trial,” NeuroRehabilitation, vol. 38, no. 4, pp. 343–349, Jun. 2016. R. Banz, M. Bolliger, G. Colombo, V. Dietz, and L. Lünenburger, “Computerized visual feedback: An adjunct to robotic-assisted gait training,” Phys. Therapy, vol. 88, no. 10, pp. 1135–1145, Oct. 2008. S. Hwang et al., “Improved gait speed after robot-assisted gait training in patients with motor incomplete spinal cord injury: A preliminary study,” Ann. Rehabil. Med., vol. 41, no. 1, p. 34, 2017. M. Munera et al., “Lokomat therapy in colombia: Current state and cognitive aspects,” in Proc. Int. Conf. Rehabil. Robot. (ICORR), Jul. 2017, pp. 394–399. K. Jack, S. M. McLean, J. K. Moffett, and E. Gardiner, “Barriers to treatment adherence in physiotherapy outpatient clinics: A systematic review,” Manual Therapy, vol. 15, no. 3, pp. 220–228, Jun. 2010. H. E. Douglas, M. Z. Raban, S. R. Walter, and J. I. Westbrook, “Improving our understanding of multi-tasking in healthcare: Drawing together the cognitive psychology and healthcare literature,” Appl. Ergonom., vol. 59, pp. 45–55, Mar. 2017. S. H. Appelbaum, A. Marchionni, and A. Fernandez, “The multi-tasking paradox: Perceptions, problems and strategies,” Manage. Decis., vol. 46, no. 9, pp. 1313–1325, Oct. 2008. H. Pashler, P. Jolicæur, R. Dell’Acqua, J. Crebolder, T. Goschke, R. De Jong, N. Meiran, R. B. Ivry, and E. Hazeltine, “Task switching and multitask performance,” in Control of Cognitive Processes: Attention and Performance XVIII, S. Monsell and J. Driver, Eds. Cambridge, MA, USA: MIT Press, 2000, pp. 275–423. B. J. Kalisch and M. Aebersold, “Interruptions and multitasking in nursing care,” Joint Commission J. Qual. Patient Saf., vol. 36, no. 3, pp. 126–132, Mar. 2010. M. Alkahtani, T. Aziz, A. Ahmad, and S. Darmoul, “Multitasking in healthcare systems,” in Proc. IIE Annu. Conf. Expo, May 2015, pp. 2146–2155. W. Moyle et al., “Exploring the effect of companion robots on emotional expression in older adults with dementia: A pilot randomized controlled trial,” J. Gerontological Nursing, vol. 39, no. 5, pp. 46–53, May 2013. B. Robins, K. Dautenhahn, R. T. Boekhorst, and A. Billard, “Robotic assistants in therapy and education of children with autism: Can a small humanoid robot help encourage social interaction skills?” Universal Access Inf. Soc., vol. 4, no. 2, pp. 105–120, Dec. 2005. K. Il Kang, S. Freedman, M. J. Mataric, M. J. Cunningham, and B. Lopez, “A hands-off physical therapy assistance robot for cardiac patients,” in Proc. 9th Int. Conf. Rehabil. Robot. (ICORR), 2005, pp. 337–340. E. Short et al., “How to train your DragonBot: Socially assistive robots for teaching children about nutrition through play,” in Proc. 23rd IEEE Int. Symp. Robot Hum. Interact. Commun., Aug. 2014, pp. 924–929. S. Jeong, “Developing a social robotic companion for stress and anxiety mitigation in pediatric hospitals,” Massachusetts Inst. Technol., Cambridge, MA, USA, Tech. Rep., 2014. P. Marti, M. Bacigalupo, L. Giusti, C. Mennecozzi, and T. Shibata, “Socially assistive robotics in the treatment of behavioural and psychological symptoms of dementia,” in Proc. 1st IEEE/RAS-EMBS Int. Conf. Biomed. Robot. Biomechatron. (BioRob), 2006, pp. 483–488. M. J. Matari´ c, J. Eriksson, D. J. Feil-Seifer, and C. J. Winstein, “Socially assistive robotics for post-stroke rehabilitation,” J. NeuroEng. Rehabil., vol. 4, no. 1, p. 5, 2007. R. Mead, E. Wade, P. Johnson, A. St. Clair, S. Chen, and M. J. Mataric, “An architecture for rehabilitation task practice in socially assistive human-robot interaction,” in Proc. 19th Int. Symp. Robot Hum. Interact. Commun., Sep. 2010, pp. 404–409. H.-T. Jung, J. Baird, Y.-K. Choe, and R. A. Grupen, “Upper-limb exercises for stroke patients through the direct engagement of an embodied agent,” in Proc. 6th Int. Conf. Hum.-Robot Interact. (HRI), 2011, p. 157. D. L. Recio, L. M. Segura, E. M. Segura, and A. Waern, “The NAO models for the elderly,” in Proc. 8th ACM/IEEE Int. Conf. Human-Robot Interact. (HRI), Mar. 2013, pp. 187–188. J. C. Pulido, J. C. González, and F. Fernández, “NAOTherapist: Autonomous assistance of physical rehabilitation therapies with a social humanoid robot,” in Proc. Int. Workshop Assistive Rehabil. Technol. (IWART), 2016, pp. 15–16. C. D. Kidd and C. Breazeal, “Robots at home: Understanding long-term human-robot interaction,” in Proc. IEEE/RSJ Int. Conf. Intell. Robots Syst., Sep. 2008, pp. 3230–3235. T. W. Bickmore and R. W. Picard, “Establishing and maintaining long-term human-computer relationships,” ACM Trans. Comput.-Hum. Interact., vol. 12, no. 2, pp. 293–327, Jun. 2005. B. Görer, A. A. Salah, and H. L. Akin, A Robotic Fitness Coach for the Elderly (Lecture Notes in Computer Science: Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8309. Cham, Switzerland: Springer, 2013, pp. 124–139. P. Gadde, H. Kharrazi, H. Patel, and K. F. MacDorman, “Toward monitoring and increasing exercise adherence in older adults by robotic intervention: A proof of concept study,” J. Robot., vol. 2011, pp. 1–11, May 2011. M. Bremer. (2005). What is Gait and Balance Training? What Can Gait and Balance Training Do For Me. Accessed: Apr. 19, 2019. [Online]. Available: https://wellness.unl.edu/pdf/physicalactivity/Gait and Balance Training.pdf L. J. Weaver and A. L. Ferg, Therapeutic Measurement and Testing: The Basics of ROM, MMT, Posture, and Gait Analysis. Delmar Cengage Learning, 2010. W. G. W. G. Bradley, Neurology in Clinical Practice. London, U.K.: Butterworth, 2004. J. Achten and A. E. Jeukendrup, “Heart rate monitoring: Applications and limitations,” Sports medicine (Auckland, N.Z.), vol. 33, no. 7, pp. 517–538, 2003. H. Kim, S.-H. Shin, J.-K. Kim, Y.-J. Park, H.-S. Oh, and Y.-B. Park, “Cervical coupling motion characteristics in healthy people using a wireless inertial measurement unit,” Evidence-Based Complementary Alternative Med., vol. 2013, pp. 1–8, 2013. J. Fasola and M. J. Matari´ c, “Using socially assistive human-robot interaction to motivate physical exercise for older adults,” Proc. IEEE, vol. 100, no. 8, pp. 2512–2526, Jul. 2012. P. Masvaure and A. Maharaj, “Work engagement, intrinsic motivation and job satisfaction among employees of a diamond mining company in zimbabwe,” J. Econ. Behav. Stud., vol. 6, no. 6, pp. 488–499, 2014. W. D. McArdle, F. I. Katch, and V. L. Katch, Exercise Physiology: Nutrition, Energy, and Human Performance. Philadelphia, PA, USA: Lippincott Williams & Wilkins, 2010. Lumbar (L1-L5) Spinal Cord Injuries | SpinalCord.com. Accessed: Jan. 15, 2019. [Online]. Available: https://www.spinalcord.com/lumbarl1-l5-vertebrae-spinal-cord-injury Spinal Cord Injury Levels & Classification | Travis Roy Foundation. Accessed: Jan. 15, 2019. [Online]. Available: https://www. travisroyfoundation.org/sci/resources/spinal-cord-injury-levelsclassification/ WHO. (2015). WHO | Stroke, Cerebrovascular Accident. [Online]. Available: https://www.who.int/topics/cerebrovascular_accident/en/ Guillain-Barré. Syndrome Fact Sheet | National Institute of Neurological Disorders and Stroke. Accessed: Jan. 15, 2019. [Online]. Available: https://www.ninds.nih.gov/Disorders/Patient-Caregiver-Education/FactSheets/Guillain-Barré-Syndrome-Fact-Sheet |
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Céspedes, Nathalia60511aded7d8a09c17c810c00f67c2d8Múnera, Marcela8047a30ff2499f8ae5a4e903871b8f95Gómez, Catalina6f8cbcb91361a2bd3b5ee47d9b913c54Cifuentes, Carlos A.0b885a45437175ae12e5d0a6f598afc4GiBiome2024-10-11T15:34:51Z2024-10-11T15:34:51Z2020-061534-4320https://repositorio.escuelaing.edu.co/handle/001/33091534-4320Universidad Escuela Colombiana de Ingeniería Julio GaravitoRepositorio Digitalhttps://repositorio.escuelaing.edu.co/Robot-assisted therapy for gait rehabilitation of patients with neurological disorders usually combines a body weight support system with a treadmill system. Lokomatis oneof the most useddevicesforgait rehabilitation. This device allows therapists to focus on the patient and the therapy. However, this therapy session is based on multi-tasking processes, which are often difficult for a therapist to manage. In this work, a Socially Assistive Robot (SAR) was integrated into a neurorehabilitation programasacollaboratoragenttopromotepatientengagement and performance during the therapy. This short-term study presents the effects comparing the social robot condition and control condition with a group of four neurological patients using repeated measurementdesign. As a remarkable result, patients improved thoracic 18.44% and cervical 32.23%postureonaveragewithSARassistance.Thisstudy demonstrated the feasibility of the integration of a social robot as a complement of gait rehabilitation programs.La terapia asistida por robot para la rehabilitación de la marcha de pacientes con trastornos neurológicos suele combinar un sistema de soporte del peso corporal con un sistema de cinta rodante. Lokomat es uno de los dispositivos más utilizados para la rehabilitación de la marcha. Este dispositivo permite a los terapeutas centrarse en el paciente y la terapia. Sin embargo, esta sesión de terapia se basa en procesos multitarea, que a menudo resultan difíciles de gestionar para un terapeuta. En este trabajo, se integró un robot de asistencia social (SAR) en un programa de neurorrehabilitación como agente colaborador para promover el compromiso y el desempeño del paciente durante la terapia. Este estudio a corto plazo presenta los efectos comparando la condición de robot social y la condición de control con un grupo de cuatro pacientes neurológicos utilizando un diseño de medición repetida. Como resultado notable, los pacientes mejoraron la postura torácica en un 18,44 % y la cervical en un 32,23 % en promedio con asistencia SAR. Este estudio demostró la viabilidad de la integración de un robot social como complemento de los programas de rehabilitación de la marcha.9 páginasapplication/pdfengIEEE Engineering Medicine & Biology SocietyEstados Unidoshttps://www.ieee.org/publications/rights/index.htmlSocial Human-Robot Interaction for Gait RehabilitationArtículo de revistainfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/coar/version/c_970fb48d4fbd8a85Vol. 28 No. 6 June 202013076129928IEEE TRANSACTIONS ON NEURALSYSTEMS AND REHABILITATION ENGINEERINGT. Dua, A. Janca, and A. Muscetta, “Public health principles and neurological disorders,” Neurological Disorders: Public Health Challenges, no. 2, pp. 7–25, 2006.WHO What are Neurological Disorders? WHO, Geneva, Switzerland, 2016.S. B. O’Sullivan, T. J. Schmitz, and G. D. Fulk, Physical Rehabilitation. Philadelphia, PA, USA: F. A. Davis Company, 2014.M. Visintin, H. Barbeau, N. Korner-Bitensky, and N. E. Mayo, “A new approach to retrain gait in stroke patients through body weight support and treadmill stimulation,” Stroke, vol. 29, no. 6, pp. 1122–1128, 1998.World Health Organization. Adherence to Long-Term Therapies— Evidence for Action: Section I—Setting the Scene: Chapter I—Defining Adherence: 1. What is Adherence? Accessed: Sep. 17, 2018. [Online]. Available: http://apps.who.int/medicinedocs/es/d/Js4883e/6.htmlS. Fisher, L. Lucas, and T. A. Thrasher, “Robot-assisted gait training for patients with hemiparesis due to stroke,” Topics Stroke Rehabil., vol. 18, no. 3, pp. 269–276, May 2011.S. Hussain, S. Q. Xie, and G. Liu, “Robot assisted treadmill training: Mechanisms and training strategies,” Med. Eng. Phys., vol. 33, no. 5, pp. 527–533, Jun. 2011.C. Werner, S. von Frankenberg, T. Treig, M. Konrad, and S. Hesse, “Treadmill training with partial body weight support and an electromechanical gait trainer for restoration of gait in subacute stroke patients: A randomized crossover study,” Stroke, vol. 33, no. 12, pp. 2895–2901, Dec. 2002.D. A. Winter, “Biomechanics of normal and pathological gait: Implications for understanding human locomotor control,” J. Motor Behav., vol. 21, no. 4, pp. 337–355, Dec. 1989.Lokomat-Hocoma. Accessed: Jan. 20, 2019. [Online]. Available: https://www.hocoma.com/solutions/lokomat/B. Husemann, F. Müller, C. Krewer, S. Heller, and E. Koenig, “Effects of locomotion training with assistance of a robot-driven gait orthosis in hemiparetic patients after stroke: A randomized controlled pilot study,” Stroke, vol. 38, no. 2, pp. 349–354, Feb. 2007.C. Krewer, F. Müller, B. Husemann, S. Heller, J. Quintern, and E. Koenig, “The influence of different lokomat walking conditions on the energy expenditure of hemiparetic patients and healthy subjects,” Gait Posture, vol. 26, no. 3, pp. 372–377, Sep. 2007.A. Mayr, M. Kofler, E. Quirbach, H. Matzak, K. Fröhlich, and L. Saltuari, “Prospective, blinded, randomized crossover study of gait rehabilitation in stroke patients using the lokomat gait orthosis,” Neurorehabilitation Neural Repair, vol. 21, no. 4, pp. 307–314, Jul. 2007.D.-H. Bang and W.-S. Shin, “Effects of robot-assisted gait training on spatiotemporal gait parameters and balance in patients with chronic stroke: A randomized controlled pilot trial,” NeuroRehabilitation, vol. 38, no. 4, pp. 343–349, Jun. 2016.R. Banz, M. Bolliger, G. Colombo, V. Dietz, and L. Lünenburger, “Computerized visual feedback: An adjunct to robotic-assisted gait training,” Phys. Therapy, vol. 88, no. 10, pp. 1135–1145, Oct. 2008.S. 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Available: https://www.ninds.nih.gov/Disorders/Patient-Caregiver-Education/FactSheets/Guillain-Barré-Syndrome-Fact-Sheetinfo:eu-repo/semantics/closedAccesshttp://purl.org/coar/access_right/c_14cbRehabilitación médicaMedical rehabilitationRobótica médicaRobotics in medicineTecnología médicaMedical technologyNeurología - RehabilitaciónNeurology - RehabilitationGaitrehabilitaciónInteracción humano-robotBiorretroalimentaciónRobótica de asistencia socialGaitrehabilitationLokomatHuman-robot interactionBiofeedbackSocially assistive roboticsTEXTSocial_Human-Robot_Interaction_for_Gait_Rehabilitation.pdf.txtSocial_Human-Robot_Interaction_for_Gait_Rehabilitation.pdf.txtExtracted texttext/plain49929https://repositorio.escuelaing.edu.co/bitstream/001/3309/4/Social_Human-Robot_Interaction_for_Gait_Rehabilitation.pdf.txtaf932395f624e0a00e1869a9454389d4MD54metadata only accessTHUMBNAILPortada Social_Human-Robot_Interaction_for_Gait_Rehabilitation.PNGPortada Social_Human-Robot_Interaction_for_Gait_Rehabilitation.PNGimage/png262753https://repositorio.escuelaing.edu.co/bitstream/001/3309/3/Portada%20Social_Human-Robot_Interaction_for_Gait_Rehabilitation.PNG930585932b2f602f9d1b252dd2778cf8MD53open accessSocial_Human-Robot_Interaction_for_Gait_Rehabilitation.pdf.jpgSocial_Human-Robot_Interaction_for_Gait_Rehabilitation.pdf.jpgGenerated Thumbnailimage/jpeg20889https://repositorio.escuelaing.edu.co/bitstream/001/3309/5/Social_Human-Robot_Interaction_for_Gait_Rehabilitation.pdf.jpgee9ac3143bbc45190891c3814f0cb51aMD55metadata only accessLICENSElicense.txtlicense.txttext/plain; charset=utf-81881https://repositorio.escuelaing.edu.co/bitstream/001/3309/2/license.txt5a7ca94c2e5326ee169f979d71d0f06eMD52open accessORIGINALSocial_Human-Robot_Interaction_for_Gait_Rehabilitation.pdfSocial_Human-Robot_Interaction_for_Gait_Rehabilitation.pdfapplication/pdf2249255https://repositorio.escuelaing.edu.co/bitstream/001/3309/1/Social_Human-Robot_Interaction_for_Gait_Rehabilitation.pdf3fb8b3b01c4abce5b4223515390ec3faMD51metadata only access001/3309oai:repositorio.escuelaing.edu.co:001/33092024-10-12 03:00:22.525metadata only accessRepositorio Escuela Colombiana de Ingeniería Julio Garavitorepositorio.eci@escuelaing.edu.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 |