Psychophysiological responses to robot training in different recovery phases after stroke.

Psychophysiological responses have become a valuable tool in human-robot interaction since they provide an objective estimate of the user's psychological state. Unfortunately, their usefulness in rehabilitation robotics is uncertain since they are influenced by both physical activity and pathological conditions such as stroke. We performed psychophysiological measurements in subacute and chronic stroke patients as well as healthy controls during a reaching and grasping exercise task performed in a multimodal virtual environment.

Challenges in biocooperative rehabilitation robotics.

Psychological states such as mood, motivation and engagement are known to be critical for the success of rehabilitation, and encouraging unmotivated stroke patients improves the likelihood of their eventual recovery. Psychological factors can be incorporated into the closed-loop control of biocooperative rehabilitation systems, augmenting the device with critical information about the patient state. However, in rehabilitation robotics, interpretation of psychophysiological measurements is made complex by the multi-task environment, the presence of strenuous physical activity and patient's damage to the central and autonomic nervous systems.

River multimodal scenario for rehabilitation robotics.

This paper presents the novel "River" multimodal rehabilitation robotics scenario that includes video, audio and haptic modalities. Elements contributing to intrinsic motivation are carefully joined in the three modalities to increase motivation of the user. The user first needs to perform a motor action, then receives a cognitive challenge that is solved with adequate motor activity.

Task difficulty adjustment in biocooperative rehabilitation using psychophysiological responses.

This study presents a biocooperative feedback loop where the difficulty of an upper extremity rehabilitation task is adjusted based on four psychophysiological measurements: heart rate, skin conductance, respiration and skin temperature. They are used both by themselves and in combination with task performance and biomechanics. Different variants of linear discriminant analysis are used for data fusion, including a variant that can adjust the fusion rules online and thus gradually adapt to the subject.

Psychophysiological measurements in a biocooperative feedback loop for upper extremity rehabilitation.

This paper examines the usefulness of psychophysiological measurements in a biocooperative feedback loop that adjusts the difficulty of an upper extremity rehabilitation task. Psychophysiological measurements (heart rate, skin conductance, respiration, and skin temperature) were used both by themselves and in combination with task performance and biomechanics. Data fusion was performed with discriminant analysis, and a special adaptive version was implemented that can gradually adapt to a subject.

Evaluation of upper extremity robot-assistances in subacute and chronic stroke subjects.

Background: Robotic systems are becoming increasingly common in upper extremity stroke rehabilitation. Recent studies have already shown that the use of rehabilitation robots can improve recovery. This paper evaluates the effect of different modes of robot-assistances in a complex virtual environment on the subjects' ability to complete the task as well as on various haptic parameters arising from the human-robot interaction.

Psychophysiological responses to robotic rehabilitation tasks in stroke.

This paper presents the analysis of four psychophysiological responses in post-stroke upper extremity rehabilitation. The goal was to determine which psychophysiological responses would provide the most reliable information about subjects' psychological states during rehabilitation. Heart rate, skin conductance, respiration, and skin temperature were recorded in a stroke group and a control group during two difficulty levels of a pick-and-place task performed in a virtual environment using a haptic robot and during a cognitive task.

Pick to place trajectories in human arm training environment.

This paper presents a new method of trajectory planning in rehabilitation robotics. First were measured in healthy subject the pick to place trajectories while haptic robot is in zero impedance space. B-spline approximation is used to mathematically define the measured paths.