Uploaded October 2021 | Updated September 2026, 18 minutes ago
Do Good Robotics Symposium: A Quantitative Scientific Theory for Technology-Aided Neuro-Recovery
Neville Hogan
Sun Jae Professor of Mechanical Engineering
Massachusetts Institute of Technology
The emergence of therapeutic and assistive robots promises new ways to aid and measure recovery after neurological injury. A quantitative, scientific theory of recovery is needed to fully realize that promise. That theory should be based on unimpaired motor behavior, at least its main features. Despite slower actuators (muscles), communication (neural transmission) and computation (neural processing) than contemporary robots, humans exhibit remarkably superior dexterity and agility. They also exhibit surprising limitations: for example, moving slowly and smoothly is hard for humans. These observations support a theory that human motor control is based on dynamic ‘building blocks’, including at least three classes: submovements, oscillations and mechanical impedances. Stereotyped submovements are evident in the earliest actions of persons recovering after stroke. Re-organization of these submovements quantifies the progress of recovery. Conversely, learning based on rhythmic performance transfers poorly to discrete actions. This may partly account for the surprising difficulty of technology-assisted locomotor rehabilitation. Abnormal tone, common after neural injury, results in abnormal muscle stiffness; that, in turn, may account for abnormal synergies. We recently showed that humans can identify limb stiffness from purely visual (non-contact) observations. Remarkably, our best subject was a highly-skilled physical therapist. This theory of recovery—re-assembly of dynamic ‘building blocks’ of unimpaired behavior—suggests new therapeutic technologies. Actuators, central to robotics, may be re-imagined as means to provide energy-efficient stiffness modulation and/or programmed into 3D-printed fabrics. These technologies enable ‘smart braces’ to provide permissive assistance, supporting patient actions as needed but without opposing expression of natural actions.
For more information on the Do Good Robotics Symposium see:
https://dgrs.umd.edu/
Do Good Robotics Symposium: A Quantitative Scientific Theory for Technology-Aided Neuro-Recovery
Neville Hogan
Sun Jae Professor of Mechanical Engineering
Massachusetts Institute of Technology
The emergence of therapeutic and assistive robots promises new ways to aid and measure recovery after neurological injury. A quantitative, scientific theory of recovery is needed to fully realize that promise. That theory should be based on unimpaired motor behavior, at least its main features. Despite slower actuators (muscles), communication (neural transmission) and computation (neural processing) than contemporary robots, humans exhibit remarkably superior dexterity and agility. They also exhibit surprising limitations: for example, moving slowly and smoothly is hard for humans. These observations support a theory that human motor control is based on dynamic ‘building blocks’, including at least three classes: submovements, oscillations and mechanical impedances. Stereotyped submovements are evident in the earliest actions of persons recovering after stroke. Re-organization of these submovements quantifies the progress of recovery. Conversely, learning based on rhythmic performance transfers poorly to discrete actions. This may partly account for the surprising difficulty of technology-assisted locomotor rehabilitation. Abnormal tone, common after neural injury, results in abnormal muscle stiffness; that, in turn, may account for abnormal synergies. We recently showed that humans can identify limb stiffness from purely visual (non-contact) observations. Remarkably, our best subject was a highly-skilled physical therapist. This theory of recovery—re-assembly of dynamic ‘building blocks’ of unimpaired behavior—suggests new therapeutic technologies. Actuators, central to robotics, may be re-imagined as means to provide energy-efficient stiffness modulation and/or programmed into 3D-printed fabrics. These technologies enable ‘smart braces’ to provide permissive assistance, supporting patient actions as needed but without opposing expression of natural actions.
For more information on the Do Good Robotics Symposium see:
https://dgrs.umd.edu/
