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

 What would be vastly more important is to create robots that cause your doctors to solve the 5 causes of the neuronal cascade of death in the first week saving billions of neurons. Because rehab only gets you almost fully recovered 10% of the time. So rehab is essentially a total failure and you are promoting more of that failure.  You're focusing on completely the wrong part of stroke.

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-Polak,
• Oren Barzel &
• Shelly Levy-Tzedek 

Journal of NeuroEngineering and Rehabilitation volume 18, Article number: 122 (2021) Cite this article

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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.

Background

Retraining coordination of reach-to-grasp movements is one of the major functional goals of rehabilitation after stroke [1], as it is the basis of a substantial number of daily activities, such as reaching to pick up a cup for drinking [2]. Intensive, repetitive task-specific training [3,4,5], over multiple sessions, can improve arm function post stroke [1, 6]. However, intensive practice, which requires a large number of repetitions, is challenging both for the patient and for the therapist [4, 6], for a variety of reasons, including the limited time in the individual therapy sessions dedicated to both acquiring and practicing new abilities, the fatigue of the patient [7, 8] and the lack of motivation of the individual with stroke to keep on training alone [9]. Therefore, it is imperative to devise feasible, alternative methods for long-term rehabilitation [4], which do not depend solely on the availability of the therapist, to be used both in the rehabilitation center and in patients’ homes [10]. These methods need to promote and motivate patients to practice their exercise, in order to improve the function of the impaired arm [4]. In order for the patient to repeat a certain task many times, they have to be highly motivated and engaged [5]. One of the ways to enhance motivation and engagement is to gamify the task; in the context of rehabilitation, this would translate to gamifying the repetitive exercise. Gamification has been demonstrated to increase patient motivation, learning, confidence, and positivity through achievement and social interaction [11]. Competitive and cooperative gamified tasks have been shown to increase motivation and exercise intensity of stroke patients when playing with another patient [12] or when playing with a healthy individual as a partner [9]. These suggest that the presence of a partner and of competition increases motivation and engagement. This can be achieved, for example, using competitive elements (such as a score) on a computer screen, or by using interactive robots, which may take on the role of a competition partner, or a coach. Socially Assistive Robots (SARs) have been designed for this purpose [13,14,15,16,17,18,19,20,21].

Previous works [13,14,15,16], on short-term interactions with a SAR, suggest that incorporating SARs into a practice regime that calls for repetitive tasks can increase stroke patients’ motivation. In previous works, patients were asked to do tasks such as magazine stacking [13], button pressing [16] or to imitate movements made by the robot [13] while receiving feedback from a SAR in a one-session interaction. These foundational studies demonstrated the feasibility of such an interaction with stroke patients. However, it is not yet known whether stroke patients' motivation will be maintained during a long-term interaction with the SAR, and whether it can lead to an improvement in their functional ability—that is, their ability to perform everyday tasks with their impaired arm, such as reaching to pick up a cup and drink from it.

Our goals in the current work were therefore threefold: first, to build a platform for functional post-stroke rehabilitation, which can track the performance of patients over time. More specifically, we aimed to build two implementations of this platform, in which the instructions and the feedback to the patient are given either by a socially assistive robot or by a computer screen. Second, to conduct a usability study with stroke patients, who will undergo a long-term intervention in the clinic with these two implementations of the platform. Third, to measure the patients’ willingness to exercise with the platform following a long-term intervention with it (15 exercise sessions conducted over 5–7 weeks), and to test the differences in the willingness of participants to use the system when using the SAR configuration, compared to the computer one.

We hypothesized that participants in the SAR group would show greater motivation and willingness to keep on exercising with the system compared to the computer group as will be measured (i) by the usability questionnaire, and (ii) by the dropout rates.

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