Increasing motivation in robot-aided arm rehabilitation with competitive and cooperative gameplay

Novak, Domen; Nagle, Aniket; Keller, Urs; Riener, Robert

doi:10.1186/1743-0003-11-64

Cited by 173 publications

(155 citation statements)

References 39 publications

Supporting

Mentioning

136

Contrasting

Unclassified

Order By: Relevance

“…After the second baseline free test, and at the end of both experimental days, subjects responded to 11 questions ( Table 1) selected from the Intrinsic Motivation Inventory (IMI, Ryan, 1982), which is a well-established and valid questionnaire already used in previous motor learning and rehabilitation studies (Novak et al, 2014;Duarte and Reinkensmeyer, 2015). The full questionnaire consists of 45 questions and can be further divided into 7 subscales.…”

Section: Experimental Protocolmentioning

confidence: 99%

Experimental Evaluation of a Mixed Controller That Amplifies Spatial Errors and Reduces Timing Errors

et al. 2017

Self Cite

View full text Add to dashboard Cite

Research on motor learning suggests that training with haptic guidance enhances learning of the timing components of motor tasks, whereas error amplification is better for learning the spatial components. We present a novel mixed guidance controller that combines haptic guidance and error amplification to simultaneously promote learning of the timing and spatial components of complex motor tasks. The controller is realized using a force field around the desired position. This force field has a stable manifold tangential to the trajectory that guides subjects in velocity-related aspects. The force field has an unstable manifold perpendicular to the trajectory, which amplifies the perpendicular (spatial) error. We also designed a controller that applies randomly varying, unpredictable disturbing forces to enhance the subjects' active participation by pushing them away from their "comfort zone." We conducted an experiment with thirty-two healthy subjects to evaluate the impact of four different training strategies on motor skill learning and selfreported motivation: (i) No haptics, (ii) mixed guidance, (iii) perpendicular error amplification and tangential haptic guidance provided in sequential order, and (iv) randomly varying disturbing forces. Subjects trained two motor tasks using ARMin IV, a robotic exoskeleton for upper limb rehabilitation: follow circles with an ellipsoidal speed profile, and move along a 3D line following a complex speed profile. Mixed guidance showed no detectable learning advantages over the other groups. Results suggest that the effectiveness of the training strategies depends on the subjects' initial skill level. Mixed guidance seemed to benefit subjects who performed the circle task with smaller errors during baseline (i.e., initially more skilled subjects), while training with no haptics was more beneficial for subjects who created larger errors (i.e., less skilled subjects). Therefore, perhaps the high functional difficulty of the tasks limited the potential benefit of mixed guidance. Adding random disturbing forces during training reduced the learning effect size compared to no haptics. The unanticipated forces also decreased the subjects' feelings of competence while did not increase their effort and interest. Further studies with mildly affected neurologically patients employing easier tasks need to be performed in order to evaluate the applicability of our approaches in rehabilitation.

show abstract

Section: Experimental Protocolmentioning

confidence: 99%

Experimental Evaluation of a Mixed Controller That Amplifies Spatial Errors and Reduces Timing Errors

et al. 2017

Self Cite

View full text Add to dashboard Cite

show abstract

“…From the patients' answers and the literature analysis [7,[23][24][25][26], REAPP specifications were defined: it has to be a system capable of providing the patients with a well-studied set of information about their performance, weighed on their psychological and physical state, a means to improve the patient awareness and (partially) integrate the human therapist during the rehabilitation with a robotic device. On the patient side, in fact, the act of fully understanding what they are doing can be a good starting point for correcting or addressing their approach, their intentions and their movements while doing the exercise [27].…”

Section: System Designmentioning

confidence: 99%

“…Better results were obtained both in terms of performance and motivation of the patients. Regarding upper limb rehabilitation, only a few examples of coupled systems were found in the literature [7,9,17]. In all these cases, the patients benefited from the therapy, but as for virtual environments alone, no feedback on their movements were provided.…”

Section: Introductionmentioning

confidence: 98%

See 1 more Smart Citation

A virtual reality system for strengthening awareness and participation in rehabilitation for post-stroke patients

Mottura

Fontana

Arlati

et al. 2015

J Multimodal User Interfaces

View full text Add to dashboard Cite

This paper presents a system called REAPP, a virtual environment aiming at supporting upper-limb robotic neurorehabilitation for post-stroke patients. In the last few years different systems using either or both virtual environments and robots have been developed. However, such advanced systems often lack attention on the physical and psychological conditions perceived by the patient, who should be the key focus in therapies. In this context, REAPP aims not to be just an entertaining interface but also a means to investigate patients' feelings toward the therapy and to enhance their self-perception while performing the rehabilitation exercises. Before and after the rehabilitation session the patients are inquired about their emotional state, their physical condition and a self-evaluation of the performance is done. While performing the exercises patients look at a 2D/3D interface which has the aim of enhancing their self-awareness by showing them, through an avatar, the movements they are doing. Widgets and a virtual assistant provide additional feedback about the quality of the movements which is computed through a specifically developed B Stefano Mottura arm model that can be customized on the residual capabilities of each patient.

show abstract

“…A new, interesting challenge for performancebased exercise adaptation has recently arisen in the form of multipatient exercise games where patients compete or cooperate with each other in order to achieve a goal (Novak et al 2014). The exercise parameters must then be adapted to suit each exercising patient even though different patients may have different needs.…”

Section: Performance-based Adaptationmentioning

confidence: 99%

Control Strategies and Artificial Intelligence in Rehabilitation Robotics

Novak

Riener

2015

AI Magazine

Self Cite

View full text Add to dashboard Cite

Rehabilitation robots physically support and guide a patient's limb during motor therapy, but require sophisticated control algorithms and artificial intelligence to do so. This article provides an overview of the state of the art in this area. It begins with the dominant paradigm of assistive control, from impedance-based cooperative controller through electromyography and intention estimation. It then covers challenge-based algorithms, which provide more difficult and complex tasks for the patient to perform through resistive control and error augmentation. Furthermore, it describes exercise adaptation algorithms that change the overall exercise intensity based on the patient's performance or physiological responses, as well as socially assistive robots that provide only verbal and visual guidance. The article concludes with a discussion of the current challenges in rehabilitation robot software: evaluating existing control strategies in a clinical setting as well as increasing the robot's autonomy using entirely new artificial intelligence techniques.

show abstract

Increasing motivation in robot-aided arm rehabilitation with competitive and cooperative gameplay

Cited by 173 publications

References 39 publications

Experimental Evaluation of a Mixed Controller That Amplifies Spatial Errors and Reduces Timing Errors

Experimental Evaluation of a Mixed Controller That Amplifies Spatial Errors and Reduces Timing Errors

A virtual reality system for strengthening awareness and participation in rehabilitation for post-stroke patients

Control Strategies and Artificial Intelligence in Rehabilitation Robotics

Contact Info

Product

Resources

About