Robot-Assisted Stroke Rehabilitation Based on Patient-Therapist Interactions (Baxter)

Our study goal is to assess natural patient-therapist interactions in order to map such human-human activities to robot-human interactions. Critical to accomplishing this mapping will be determining the feasibility of a humanoid robot interacting with a patient in a more intuitive and flexible way, while concomitantly investigating the issue of safe contact and release.

Stroke survivors with varying levels of motor deficit impairment in their upper extremity (UE) will be assessed using standardized clinical scales for cognition and motor impairment. Following assessment, the patient and therapist will complete a therapy session consisting of activities of daily living (ADL). During the therapy session, visual 3D motion tracking will be used via Kinect, audio will be recorded, and basic measurements (i.e. the distance between a participants wrist and elbow) will be taken. After the patient-therapist interaction has been mapped, members of the research team will build computer based models of the therapist and patient using the insights gained from the human-human interaction. The models developed in this proposed study will be used as a template for programming safe and intuitive humanoid-patient interactions for future study. The model of the therapist will be implemented on the Robot (w/o a patient involved) and in a simulation environment where it will be tested with a computer-based model of the patient.

Stroke survivors greater than 18 years of age with hemiplegia and varying levels of impairment as well as healthy subjects greater than 18 years old with no motor disabilities will be asked to interact with a therapist. The Patient-Therapist interactions will be recorded using the Rehab Intercap System and 3D Kinect Device.

The therapist will conduct a therapy session which will consist of various activities of daily living. During the session, the motion of the therapist and patients will be collected with a custom motion capture system (Rehab InterCap) and 3D visual mapping may take place using the Kinect device, audio will be recorded, and basic measurements of length (i.e. the distance from a participant's shoulder to elbow) will be taken. Patients and therapists will wear the sensors to capture their arm movements. 3D video motion capture may be completed with some subjects. This will involve subjects wearing reflective markers on their upper arms in addition to the intercap sensors.

Using the data collected during the subject's visit to the Rehabilitation Robotics Lab, computer-based models of the therapist and the patient will be devised. These models may be used in future studies with a robot Video collection of patient-therapists in real settings.

Inclusion Criteria: Stroke survivors 18 years of age with hemiplegia and varying levels of impairment Healthy subjects greater than 18 years of age with no motor disabilities Exclusion Criteria: Under 18 years of age