About this trial
Participants will perform experiments with non-invasive activity recordings. The study will record from multiple non-invasive signal sources that reflect motor intent that may include: electroencephalography (EEG), electromyography (EMG), functional near infrared spectroscopy (fNIRS), inertial measurement units (IMUs), eye movements, pupil size, and speech. Participants will wear all or a subset of these sensors and be asked to perform, imagine, or attempt movements or speech. The recorded sensor signals will be decoded to help guide an end effector, which may be a computer, robotic arm, wheelchair, or other assistive device.
These experiments present minimal risk and participants may withdraw participation at any time for any reason. Participants may return for additional experiments if desired and to perform additional comparisons. If a participant withdraws during a comparison, another participant will be recruited to complete collection of data for that comparison.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
Fluent in the English language
Disqualifiers
Neurological injury or disease that results in functional paralysis
Trial design
Single group
Treatments tested in this trial
Participants will perform experimental tasks while undergoing non-invasive activity recordings, which may include EEG, EMG, IMUs, fNIRS, eye gaze, or pupillometry.
BehavioralParticipants may be prompted to imagine, attempt, or perform actions while a task is being performed on a computer, robotic arm, wheelchair, or exoskeleton. Participants may also autonomously perform actions to control each end effector. Participants may be asked to control a cursor to acquire a target or multiple targets. Participants may be asked to pick and place various objects, interact with articulated objects, or perform other motor tasks using a robotic manipulator. Participants may be asked to navigate a wheelchair.
Treatment groups
Trial outcomes
Primary outcomes
Normalized Performance
The normalized performance of the non-invasive assistive interface on a task. Non-invasive signals, which may include electroencephalography, electromyography, functional near infrared spectroscopy, inertial measurements units, eye movements, pupil size, and speech are input into an algorithm that controls an end effector's movements. The end effector, which may be a computer cursor, robotic manipulator, wheelchair, or other assistive device, is used to perform a motor task. The normalized performance is derived from the the performance of the end effector on the motor task, reflecting the overall performance of the non-invasive assistive interface. The minimum value is zero. There is no maximum value, although the values are usually less than 1. Higher is better.
Sponsors and contacts
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University of California, Los Angeles
Lead sponsor
Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)
Collaborator