Previous work described the lack of involving stakeholders to design such functionalities as one of the major causes. While previous work explored the potential of automatically monitoring exercises for AI and robotic coaches, the deployment of these systems remains a challenge. We outline and discuss future experimental designs and factors toward the development of effective socially assistive post-stroke rehabilitation robots.Īrtificial intelligence (AI) and robotic coaches promise the improved engagement of patients on rehabilitation exercises through social interaction. We also show preliminary results from a follow-up study that focused on the role of robot physical embodiment in a rehabilitation context. The robot navigates autonomously, monitors the patient's arm activity, and helps the patient remember to follow a rehabilitation program. We describe a pilot study involving an autonomous assistive mobile robot that aids stroke patient rehabilitation by providing monitoring, encouragement, and reminders. We demonstrate the approach with an implemented and tested post-stroke recovery robot and discuss its potential for effectiveness.
We describe a new area, called socially assistive robotics, that focuses on non-contact patient/user assistance. However, new rehabilitation studies support the theory that not all therapy need be hands-on. Although there is a great deal of success in rehabilitative robotics applied to patient recovery post stroke, most of the research to date has dealt with providing physical assistance.
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