A proposal for patient-tailored supervision of movement performance during end-effector-based robot-assisted rehabilitation of the upper extremities.

Millions of people worldwide suffer from stroke each year. One way to assist patients cost-effectively during their rehabilitation process is using end-effector-based robot-assisted rehabilitation. Such systems allow patients to use their own movement strategies to perform a movement task, which encourages them to do self-motivated training but also allow compensation movements if they have problems executing the movement tasks.

Signal verification of middle latency auditory evoked potentials by automated detection of the brainstem response.

Background: The midlatency components of auditory evoked potentials (AEPs) are gradually suppressed with increasing concentrations of anesthetics. Thus, they have been proposed as a monitor of anesthetic depth. However, undetected malfunction or disconnection of headphones and undetected hearing loss also result in suppressed midlatency AEPs that in turn may be misinterpreted as signs of deep anesthesia.