Non-invasive Neuromodulation to Provide Haptic Feedback During Functional Tasks
Department
Biomedical Engineering
Faculty Advisor
Ranu Jung
Start Date
1-10-2020 2:00 AM
End Date
1-10-2020 3:00 AM
Abstract
Sensory feedback plays an essential role in everyday tasks, including planning and control of even simple movements, such as reaching for an object. Artificial tactile (haptic) feedback can be used to provide useful sensory information while interacting with objects in virtual reality environments or during the operation of robotic devices such as prosthetic limbs. Current haptic feedback approaches include cumbersome mechanical stimulation (vibration/pressure) devices that are not intuitive and limit the user's actions. Previously, a non-invasive electrical neurostimulation platform was developed to evoke artificial haptic feedback in the hand by activating the nerves in the wrist, without causing discomfort or distracting sensations under the stimulator. In this study, the neurostimulation platform was used to provide task-related haptic feedback to able-bodied participants in order to investigate the degree to which the artificial tactile information enables the user to perform functional tasks such as classifying virtual objects and controlling the grasping force outputs or a robotic hand. A hand aperture tracking system was developed using a markerless near-infrared camera system (Leap Motion) which recognizes the position of the hand and fingers without the use of mounted sensors. Validation tests were completed in order to characterize the accuracy of the tracking system. Hand aperture measurements were recorded under different conditions (hand tilt and distance from the sensor) and compared to the actual aperture values. A calibration curve was derived to correct the sensor output, reducing the average tracking error from 38.38 +/- 12.71% to 10.01 +/- 10.92%. A pilot study was performed to test the tracking system during virtual object classification tasks. The participant was first fitted with surface electrodes that delivered electrical pulses to the median nerve within the right wrist. The stimulation parameters were set to evoke graded, distally referred sensations of force, based on the hand aperture readings. For each virtual object profile, the participant was asked to close their hand slowly to match the size of the object. Once contact was made, the participant was asked to "squeeze" the virtual object slightly to increase the perceived force levels while exploring the size and firmness of each profile. The participant was asked to classify each virtual object into one of four categories: small-soft, small-rigid, large-soft, or large-rigid. The order of presentation of each profile was randomized, without consecutive presentations of the same profile. In this pilot study, the participant was able to identify 37 out of 40 objects correctly (92.5% accuracy). In future trials, an intermediate category of size and firmness will be included, increasing the total number of distinct object profiles from four (2x2 matrix) to nine (3x3 matrix). Additionally, participants will complete force output matching tasks with and without visual or sensory feedback to assess the potential benefits of such feedback in the graded control of force outputs.
File Type
Event
Non-invasive Neuromodulation to Provide Haptic Feedback During Functional Tasks
Sensory feedback plays an essential role in everyday tasks, including planning and control of even simple movements, such as reaching for an object. Artificial tactile (haptic) feedback can be used to provide useful sensory information while interacting with objects in virtual reality environments or during the operation of robotic devices such as prosthetic limbs. Current haptic feedback approaches include cumbersome mechanical stimulation (vibration/pressure) devices that are not intuitive and limit the user's actions. Previously, a non-invasive electrical neurostimulation platform was developed to evoke artificial haptic feedback in the hand by activating the nerves in the wrist, without causing discomfort or distracting sensations under the stimulator. In this study, the neurostimulation platform was used to provide task-related haptic feedback to able-bodied participants in order to investigate the degree to which the artificial tactile information enables the user to perform functional tasks such as classifying virtual objects and controlling the grasping force outputs or a robotic hand. A hand aperture tracking system was developed using a markerless near-infrared camera system (Leap Motion) which recognizes the position of the hand and fingers without the use of mounted sensors. Validation tests were completed in order to characterize the accuracy of the tracking system. Hand aperture measurements were recorded under different conditions (hand tilt and distance from the sensor) and compared to the actual aperture values. A calibration curve was derived to correct the sensor output, reducing the average tracking error from 38.38 +/- 12.71% to 10.01 +/- 10.92%. A pilot study was performed to test the tracking system during virtual object classification tasks. The participant was first fitted with surface electrodes that delivered electrical pulses to the median nerve within the right wrist. The stimulation parameters were set to evoke graded, distally referred sensations of force, based on the hand aperture readings. For each virtual object profile, the participant was asked to close their hand slowly to match the size of the object. Once contact was made, the participant was asked to "squeeze" the virtual object slightly to increase the perceived force levels while exploring the size and firmness of each profile. The participant was asked to classify each virtual object into one of four categories: small-soft, small-rigid, large-soft, or large-rigid. The order of presentation of each profile was randomized, without consecutive presentations of the same profile. In this pilot study, the participant was able to identify 37 out of 40 objects correctly (92.5% accuracy). In future trials, an intermediate category of size and firmness will be included, increasing the total number of distinct object profiles from four (2x2 matrix) to nine (3x3 matrix). Additionally, participants will complete force output matching tasks with and without visual or sensory feedback to assess the potential benefits of such feedback in the graded control of force outputs.