JMIR Publications

ABSTRACT

Background:

Robot-mediated telerehabilitation has the potential to provide patient-tailored cost-effective rehabilitation. However, compliance with therapy can be a problem that undermines the prospective advantages of telerehabilitation technologies. Lack of motivation has been identified as a major factor that hampers compliance. Exploring various motivational interventions, the integration of citizen science activities in robotics-based rehabilitation has been shown to increase patients’ motivation to engage in otherwise tedious exercises, by tapping into a vast array of intrinsic motivational drivers. Patient engagement can be further enhanced by the incorporation of social interactions.

Objective:

Herein, we explored the possibility of bolstering engagement in physical therapy by leveraging cooperation among users in an environmental citizen science project. Further, we investigated how the degree of interdependence among users affects participation in citizen science-based telerehabilitation.

Methods:

We developed an online citizen science platform in which users work in pairs to classify images collected by an aquatic robot in a polluted water canal. The classification was carried out by labeling objects that appear in the images and trashing irrelevant labels. The software was interfaced by a haptic device for fine motor rehabilitation. We recruited 120 healthy volunteers to operate the platform. Of these volunteers, 98 were cooperating in pairs, with one user tagging images and the other trashing labels. The other 22 volunteers performed both tasks alone. To vary the degree of interdependence within cooperation, we implemented independent and joint terminations.

Results:

We found that users’ engagement and motor performance are modulated by their task choice and the degree of interdependence. Specifically, enjoyment and peak speed of the end-effector differed among conditions (P = .005 and P = .02, respectively). A significant interaction between condition and task was found to influence productivity (P < .001), as well as mean speed, peak speed, and pathlength of the end-effector (P = .01, P = .006, and P < .001, respectively).

Conclusions:

Enhancing user engagement, satisfaction, and motor performance through cooperative citizen science tasks relies on the degree of interdependence among users and the perceived nature of task. Therefore, cooperative citizen science may enhance motivation in robotics-based telerehabilitation, if designed attentively.