7 research outputs found
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A Thermoelectric Display for Assessment of Touch Sensory Deficits
This thesis employed systems modeling and engineering design methods in order to study the `thermal grill illusion' (TGI), a perceptual illusion in which a spatial configuration of warm and cool elements produce a paradoxical pseudo-burning sensation. The motivation for this study was derived from the possibility to develop new methods for assessing peripheral sensory deficits affecting the sense of touch, associated with peripheral neuropathy. Thermal grill stimuli, consisting of spatial configurations of alternating warm and cool elements, are non-injurious and can elicit rapid and unambiguous perceptual responses, whose absence might provide a reliable indicator of sensory loss, although this has not been previously investigated, and is only indirectly addressed in this thesis. An integrated custom electrothermal display was optimized for delivering thermal grill stimuli to the body. In order to validate the display technique, a thermodynamic model accounting for heat exchange (diffusion) through the skin was developed and the model predictions were compared with thermal perception. I calibrated and assessed the approach in perceptual experiments with healthy human subjects
A Sonomyography-based Muscle Computer Interface for Individuals with Spinal Cord Injury
Impairment of hand functions in individuals with spinal cord injury (SCI)
severely disrupts activities of daily living. Recent advances have enabled
rehabilitation assisted by robotic devices to augment the residual function of
the muscles. Traditionally, non-invasive electromyography-based peripheral
neural interfaces have been utilized to sense volitional motor intent to drive
robotic assistive devices. However, the dexterity and fidelity of control that
can be achieved with electromyography-based control have been limited due to
inherent limitations in signal quality. We have developed and tested a
muscle-computer interface (MCI) utilizing sonomyography to provide control of a
virtual cursor for individuals with motor-incomplete spinal cord injury. We
demonstrate that individuals with SCI successfully gained control of a virtual
cursor by utilizing contractions of muscles of the wrist joint. The
sonomyography-based interface enabled control of the cursor at multiple graded
levels demonstrating the ability to achieve accurate and stable endpoint
control. Our sonomyography-based muscle-computer interface can enable dexterous
control of upper-extremity assistive devices for individuals with
motor-incomplete SCI
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Using principles of motor control to analyze performance of human machine interfaces.
There have been significant advances in biosignal extraction techniques to drive external biomechatronic devices or to use as inputs to sophisticated human machine interfaces. The control signals are typically derived from biological signals such as myoelectric measurements made either from the surface of the skin or subcutaneously. Other biosignal sensing modalities are emerging. With improvements in sensing modalities and control algorithms, it is becoming possible to robustly control the target position of an end-effector. It remains largely unknown to what extent these improvements can lead to naturalistic human-like movement. In this paper, we sought to answer this question. We utilized a sensing paradigm called sonomyography based on continuous ultrasound imaging of forearm muscles. Unlike myoelectric control strategies which measure electrical activation and use the extracted signals to determine the velocity of an end-effector; sonomyography measures muscle deformation directly with ultrasound and uses the extracted signals to proportionally control the position of an end-effector. Previously, we showed that users were able to accurately and precisely perform a virtual target acquisition task using sonomyography. In this work, we investigate the time course of the control trajectories derived from sonomyography. We show that the time course of the sonomyography-derived trajectories that users take to reach virtual targets reflect the trajectories shown to be typical for kinematic characteristics observed in biological limbs. Specifically, during a target acquisition task, the velocity profiles followed a minimum jerk trajectory shown for point-to-point arm reaching movements, with similar time to target. In addition, the trajectories based on ultrasound imaging result in a systematic delay and scaling of peak movement velocity as the movement distance increased. We believe this is the first evaluation of similarities in control policies in coordinated movements in jointed limbs, and those based on position control signals extracted at the individual muscle level. These results have strong implications for the future development of control paradigms for assistive technologies
Using principles of motor control to analyze performance of human machine interfaces
Abstract There have been significant advances in biosignal extraction techniques to drive external biomechatronic devices or to use as inputs to sophisticated human machine interfaces. The control signals are typically derived from biological signals such as myoelectric measurements made either from the surface of the skin or subcutaneously. Other biosignal sensing modalities are emerging. With improvements in sensing modalities and control algorithms, it is becoming possible to robustly control the target position of an end-effector. It remains largely unknown to what extent these improvements can lead to naturalistic human-like movement. In this paper, we sought to answer this question. We utilized a sensing paradigm called sonomyography based on continuous ultrasound imaging of forearm muscles. Unlike myoelectric control strategies which measure electrical activation and use the extracted signals to determine the velocity of an end-effector; sonomyography measures muscle deformation directly with ultrasound and uses the extracted signals to proportionally control the position of an end-effector. Previously, we showed that users were able to accurately and precisely perform a virtual target acquisition task using sonomyography. In this work, we investigate the time course of the control trajectories derived from sonomyography. We show that the time course of the sonomyography-derived trajectories that users take to reach virtual targets reflect the trajectories shown to be typical for kinematic characteristics observed in biological limbs. Specifically, during a target acquisition task, the velocity profiles followed a minimum jerk trajectory shown for point-to-point arm reaching movements, with similar time to target. In addition, the trajectories based on ultrasound imaging result in a systematic delay and scaling of peak movement velocity as the movement distance increased. We believe this is the first evaluation of similarities in control policies in coordinated movements in jointed limbs, and those based on position control signals extracted at the individual muscle level. These results have strong implications for the future development of control paradigms for assistive technologies
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Proprioceptive Sonomyographic Control: A novel method for intuitive and proportional control of multiple degrees-of-freedom for individuals with upper extremity limb loss
Technological advances in multi-articulated prosthetic hands have outpaced the development of methods to intuitively control these devices. In fact, prosthetic users often cite "difficulty of use" as a key contributing factor for abandoning their prostheses. To overcome the limitations of the currently pervasive myoelectric control strategies, namely unintuitive proportional control of multiple degrees-of-freedom, we propose a novel approach: proprioceptive sonomyographic control. Unlike myoelectric control strategies which measure electrical activation of muscles and use the extracted signals to determine the velocity of an end-effector; our sonomyography-based strategy measures mechanical muscle deformation directly with ultrasound and uses the extracted signals to proportionally control the position of an end-effector. Therefore, our sonomyography-based control is congruent with a prosthetic user's innate proprioception of muscle deformation in the residual limb. In this work, we evaluated proprioceptive sonomyographic control with 5 prosthetic users and 5 able-bodied participants in a virtual target achievement and holding task for 5 different hand motions. We observed that with limited training, the performance of prosthetic users was comparable to that of able-bodied participants and thus conclude that proprioceptive sonomyographic control is a robust and intuitive prosthetic control strategy