Evolution of the CPG with Sensory Feedback for Bipedal Locomotion

2005 ◽  
pp. 714-726 ◽  
Author(s):  
Sooyol Ok ◽  
DuckSool Kim
Keyword(s):  
Sensory Feedback ◽  
Bipedal Locomotion

Human Cerebral Potentials During Motor Training Under Different Forms of Sensory Feedback

1999 ◽  
Vol 13 (4) ◽  
pp. 234-244
Author(s):  
Uwe Niederberger ◽  
Wolf-Dieter Gerber
Keyword(s):  
Healthy Subjects ◽  
Sensory Feedback ◽  
Motor Task ◽  
Tactile Feedback ◽  
Proprioceptive Feedback ◽  
Motor Training ◽  
Feedback Group ◽  
Emg Feedback ◽  
The Right ◽  
Training Success

Abstract In two experiments with four and two groups of healthy subjects, a novel motor task, the voluntary abduction of the right big toe, was trained. This task cannot usually be performed without training and is therefore ideal for the study of elementary motor learning. A systematic variation of proprioceptive, tactile, visual, and EMG feedback was used. In addition to peripheral measurements such as the voluntary range of motion and EMG output during training, a three-channel EEG was recorded over Cz, C3, and C4. The movement-related brain potential during distinct periods of the training was analyzed as a central nervous parameter of the ongoing learning process. In experiment I, we randomized four groups of 12 subjects each (group P: proprioceptive feedback; group PT: proprioceptive and tactile feedback; group PTV: proprioceptive, tactile, and visual feedback; group PTEMG: proprioceptive, tactile, and EMG feedback). Best training results were reported from the PTEMG and PTV groups. The movement-preceding cortical activity, in the form of the amplitude of the readiness potential at the time of EMG onset, was greatest in these two groups. Results of experiment II revealed a similar effect, with a greater training success and a higher electrocortical activation under additional EMG feedback compared to proprioceptive feedback alone. Sensory EMG feedback as evaluated by peripheral and central nervous measurements appears to be useful in motor training and neuromuscular re-education.

Display and sensory-feedback persistence in determining memory

1970 ◽  
Author(s):  
Harvey M. Sussman ◽  
Karl U. Smith
Keyword(s):  
Sensory Feedback

Precise Computer Controlled Positioning of Robot End Effectors Using Sensory Feedback

1988 ◽  
Author(s):  
J.C. Wang ◽  
J.S.H. Tsai ◽  
B.C. McInnis ◽  
L.S. Shieh
Keyword(s):  
Sensory Feedback ◽  
Computer Controlled ◽  
End Effectors

The Utility of Interappendicular Connections in Bipedal Locomotion

2017 ◽  
Vol 23 (12) ◽  
pp. 1734-1740 ◽  
Author(s):  
David McMillan ◽  
Ray de Leon ◽  
Pierre A. Guertin ◽  
Christine Dy
Keyword(s):  
Bipedal Locomotion

Muscles

2018 ◽  
Author(s):  
Iain A. Anderson ◽  
Benjamin M. O’Brien
Keyword(s):  
Sensory Feedback ◽  
Artificial Muscles ◽  
Combustion Engines ◽  
Electric Motors ◽  
Home Appliances ◽  
Leg Muscles ◽  
Mechanical Devices ◽  
Control Surfaces

Mechanical devices that include home appliances, automobiles, and airplanes are typically driven by electric motors or combustion engines through gearboxes and other linkages. Airplane wings, for example, have hinged control surfaces such as ailerons. Now imagine a wing that has no hinged control surfaces or linkages but that instead bends or warps to assume an appropriate shape, like the wing of a bird. Such a device could be enabled using an electro-active polymer technology based on electronic artificial muscles. Artificial muscles act directly on a structure, like our leg muscles that are attached by tendon to our bones and that through phased contraction enable us to walk. Sensory feedback from our muscles enables proprioceptive control. So, for artificial muscles to be used appropriately we need to pay attention not only to mechanisms for muscle actuation but also to how we can incorporate self-sensing feedback for the control of position.

The role of enhanced plantar-surface sensory feedback on lower limb EMG during planned gait termination

2021 ◽  
pp. 1-11
Author(s):  
Kelly A. Robb ◽  
Jordan D. Hyde ◽  
Stephen D. Perry
Keyword(s):  
Lower Limb ◽  
Sensory Feedback ◽  
Gait Termination ◽  
Plantar Surface

scholarly journals Sensory feedback-dependent coding of arm position in local field potentials of the posterior parietal cortex

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Paul VanGilder ◽  
Ying Shi ◽  
Gregory Apker ◽  
Christopher A. Buneo
Keyword(s):  
Local Field ◽  
Sensory Feedback ◽  
Posterior Parietal Cortex ◽  
Spectral Power ◽  
Field Potential ◽  
Beta Activity ◽  
Beta Band ◽  
Arm Position ◽  
Multisensory Interactions ◽  
Spiking Activity

AbstractAlthough multisensory integration is crucial for sensorimotor function, it is unclear how visual and proprioceptive sensory cues are combined in the brain during motor behaviors. Here we characterized the effects of multisensory interactions on local field potential (LFP) activity obtained from the superior parietal lobule (SPL) as non-human primates performed a reaching task with either unimodal (proprioceptive) or bimodal (visual-proprioceptive) sensory feedback. Based on previous analyses of spiking activity, we hypothesized that evoked LFP responses would be tuned to arm location but would be suppressed on bimodal trials, relative to unimodal trials. We also expected to see a substantial number of recording sites with enhanced beta band spectral power for only one set of feedback conditions (e.g. unimodal or bimodal), as was previously observed for spiking activity. We found that evoked activity and beta band power were tuned to arm location at many individual sites, though this tuning often differed between unimodal and bimodal trials. Across the population, both evoked and beta activity were consistent with feedback-dependent tuning to arm location, while beta band activity also showed evidence of response suppression on bimodal trials. The results suggest that multisensory interactions can alter the tuning and gain of arm position-related LFP activity in the SPL.

scholarly journals Joint speed feedback improves myoelectric prosthesis adaptation after perturbed reaches in non amputees

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Eric J. Earley ◽  
Reva E. Johnson ◽  
Jonathon W. Sensinger ◽  
Levi J. Hargrove
Keyword(s):  
Sensory Feedback ◽  
Feedforward Control ◽  
Feedback System ◽  
Augmented Feedback ◽  
Myoelectric Prosthesis ◽  
Reaching Task ◽  
Prosthesis Control ◽  
High Uncertainty ◽  
Relevant Factors ◽  
Positional Control

AbstractAccurate control of human limbs involves both feedforward and feedback signals. For prosthetic arms, feedforward control is commonly accomplished by recording myoelectric signals from the residual limb to predict the user’s intent, but augmented feedback signals are not explicitly provided in commercial devices. Previous studies have demonstrated inconsistent results when artificial feedback was provided in the presence of vision; some studies showed benefits, while others did not. We hypothesized that negligible benefits in past studies may have been due to artificial feedback with low precision compared to vision, which results in heavy reliance on vision during reaching tasks. Furthermore, we anticipated more reliable benefits from artificial feedback when providing information that vision estimates with high uncertainty (e.g. joint speed). In this study, we test an artificial sensory feedback system providing joint speed information and how it impacts performance and adaptation during a hybrid positional-and-myoelectric ballistic reaching task. We found that overall reaching errors were reduced after perturbed control, but did not significantly improve steady-state reaches. Furthermore, we found that feedback about the joint speed of the myoelectric prosthesis control improved the adaptation rate of biological limb movements, which may have resulted from high prosthesis control noise and strategic overreaching with the positional control and underreaching with the myoelectric control. These results provide insights into the relevant factors influencing the improvements conferred by artificial sensory feedback.

scholarly journals Training with Agency-Inspired Feedback from an Instrumented Glove to Improve Functional Grasp Performance

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1173
Author(s):  
Mingxiao Liu ◽  
Samuel Wilder ◽  
Sean Sanford ◽  
Soha Saleh ◽  
Noam Y. Harel ◽  
...  
Keyword(s):  
Sensory Feedback ◽  
Small Object ◽  
Intentional Binding ◽  
Audio Feedback ◽  
Instrumented Glove ◽  
Sensory Consequence ◽  
Preliminary Study ◽  
Future Work ◽  
Flex Sensors ◽  
Functional Task

Sensory feedback from wearables can be effective to learn better movement through enhanced information and engagement. Facilitating greater user cognition during movement practice is critical to accelerate gains in motor function during rehabilitation following brain or spinal cord trauma. This preliminary study presents an approach using an instrumented glove to leverage sense of agency, or perception of control, to provide training feedback for functional grasp. Seventeen able-bodied subjects underwent training and testing with a custom-built sensor glove prototype from our laboratory. The glove utilizes onboard force and flex sensors to provide inputs to an artificial neural network that predicts achievement of “secure” grasp. Onboard visual and audio feedback was provided during training with progressively shorter time delay to induce greater agency by intentional binding, or perceived compression in time between an action (grasp) and sensory consequence (feedback). After training, subjects demonstrated a significant reduction (p < 0.05) in movement pathlength and completion time for a functional task involving grasp-move-place of a small object. Future work will include a model-based algorithm to compute secure grasp, virtual reality immersion, and testing with clinical populations.

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