Literature DB >> 34321035

A robot goes to rehab: a novel gamified system for long-term stroke rehabilitation using a socially assistive robot-methodology and usability testing.

Ronit Feingold-Polak1, Oren Barzel2,3,4,5, Shelly Levy-Tzedek6,7,8.   

Abstract

BACKGROUND: Socially assistive robots (SARs) have been proposed as a tool to help individuals who have had a stroke to perform their exercise during their rehabilitation process. Yet, to date, there are no data on the motivating benefit of SARs in a long-term interaction with post-stroke patients.
METHODS: Here, we describe a robot-based gamified exercise platform, which we developed for long-term post-stroke rehabilitation. The platform uses the humanoid robot Pepper, and also has a computer-based configuration (with no robot). It includes seven gamified sets of exercises, which are based on functional tasks from the everyday life of the patients. The platform gives the patients instructions, as well as feedback on their performance, and can track their performance over time. We performed a long-term patient-usability study, where 24 post-stroke patients were randomly allocated to exercise with this platform-either with the robot or the computer configuration-over a 5-7 week period, 3 times per week, for a total of 306 sessions.
RESULTS: The participants in both groups reported that this rehabilitation platform addressed their arm rehabilitation needs, and they expressed their desire to continue training with it even after the study ended. We found a trend for higher acceptance of the system by the participants in the robot group on all parameters; however, this difference was not significant. We found that system failures did not affect the long-term trust that users felt towards the system.
CONCLUSIONS: We demonstrated the usability of using this platform for a long-term rehabilitation with post-stroke patients in a clinical setting. We found high levels of acceptance of both platform configurations by patients following this interaction, with higher ratings given to the SAR configuration. We show that it is not the mere use of technology that increases the motivation of the person to practice, but rather it is the appreciation of the technology's effectiveness and its perceived contribution to the rehabilitation process. In addition, we provide a list of guidelines that can be used when designing and implementing other technological tools for rehabilitation. TRIAL REGISTRATION: This trial is registered in the NIH ClinicalTrials.gov database. Registration number NCT03651063, registration date 21.08.2018. https://clinicaltrials.gov/ct2/show/NCT03651063 .
© 2021. The Author(s).

Entities:  

Keywords:  Co-design; Exergames; In-the-wild-study; Participatory design; Rehabilitation; Socially assistive robots; Stroke; Trust

Year:  2021        PMID: 34321035     DOI: 10.1186/s12984-021-00915-2

Source DB:  PubMed          Journal:  J Neuroeng Rehabil        ISSN: 1743-0003            Impact factor:   4.262


  21 in total

1.  Maximal grip force in chronic stroke subjects and its relationship to global upper extremity function.

Authors:  P Boissy; D Bourbonnais; M M Carlotti; D Gravel; B A Arsenault
Journal:  Clin Rehabil       Date:  1999-08       Impact factor: 3.477

2.  End-state comfort meets pre-crastination.

Authors:  David A Rosenbaum; Kyle S Sauerberger
Journal:  Psychol Res       Date:  2019-01-08

Review 3.  Cognition, action, and object manipulation.

Authors:  David A Rosenbaum; Kate M Chapman; Matthias Weigelt; Daniel J Weiss; Robrecht van der Wel
Journal:  Psychol Bull       Date:  2012-03-26       Impact factor: 17.737

Review 4.  The prevalence of fatigue after stroke: A systematic review and meta-analysis.

Authors:  Toby B Cumming; Marcie Packer; Sharon F Kramer; Coralie English
Journal:  Int J Stroke       Date:  2016-10-04       Impact factor: 5.266

5.  Planning for manual positioning: the end-state comfort effect for manual abduction-adduction.

Authors:  Wei Zhang; David A Rosenbaum
Journal:  Exp Brain Res       Date:  2007-08-29       Impact factor: 1.972

Review 6.  The impact of stroke on the performance of grasping: usefulness of kinetic and kinematic motion analysis.

Authors:  Dennis A Nowak
Journal:  Neurosci Biobehav Rev       Date:  2008-05-23       Impact factor: 8.989

Review 7.  Grip force behavior during object manipulation in neurological disorders: toward an objective evaluation of manual performance deficits.

Authors:  Dennis A Nowak; Joachim Hermsdörfer
Journal:  Mov Disord       Date:  2005-01       Impact factor: 10.338

8.  Effectiveness of Virtual Reality- and Gaming-Based Interventions for Upper Extremity Rehabilitation Poststroke: A Meta-analysis.

Authors:  Reneh Karamians; Rachel Proffitt; David Kline; Lynne V Gauthier
Journal:  Arch Phys Med Rehabil       Date:  2019-12-07       Impact factor: 3.966

9.  Robotic gaming prototype for upper limb exercise: Effects of age and embodiment on user preferences and movement.

Authors:  Danny Eizicovits; Yael Edan; Iris Tabak; Shelly Levy-Tzedek
Journal:  Restor Neurol Neurosci       Date:  2018       Impact factor: 2.406

Review 10.  Rehabilitation of Motor Function after Stroke: A Multiple Systematic Review Focused on Techniques to Stimulate Upper Extremity Recovery.

Authors:  Samar M Hatem; Geoffroy Saussez; Margaux Della Faille; Vincent Prist; Xue Zhang; Delphine Dispa; Yannick Bleyenheuft
Journal:  Front Hum Neurosci       Date:  2016-09-13       Impact factor: 3.169

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  4 in total

1.  Interaction Matters: The Effect of Touching the Social Robot PARO on Pain and Stress is Stronger When Turned ON vs. OFF.

Authors:  Nirit Geva; Netta Hermoni; Shelly Levy-Tzedek
Journal:  Front Robot AI       Date:  2022-07-08

2.  A Socially Assistive Robot for Stroke Patients: Acceptance, Needs, and Concerns of Patients and Informal Caregivers.

Authors:  Ayelet Dembovski; Yael Amitai; Shelly Levy-Tzedek
Journal:  Front Rehabil Sci       Date:  2022-01-25

3.  Extended Interviews with Stroke Patients Over a Long-Term Rehabilitation Using Human-Robot or Human-Computer Interactions.

Authors:  Yaacov Koren; Ronit Feingold Polak; Shelly Levy-Tzedek
Journal:  Int J Soc Robot       Date:  2022-09-16       Impact factor: 3.802

4.  Automating provision of feedback to stroke patients with and without information on compensatory movements: A pilot study.

Authors:  Daphne Fruchter; Ronit Feingold Polak; Sigal Berman; Shelly Levy-Tzedek
Journal:  Front Hum Neurosci       Date:  2022-08-08       Impact factor: 3.473

  4 in total

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