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1. Stiffness Perception using Transcutaneous Electrical Stimulation during Active and Passive Prosthetic Control

   https://doi.org/10.1109/EMBC44109.2020.9176078  

   Vargas, Luis ; Huang, Helen ; Zhu, Yong ; Hu, Xiaogang ( July 2020 , International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC))

   null (Ed.)

   Haptic feedback allows an individual to identify various object properties. In this preliminary study, we determined the performance of stiffness recognition using transcutaneous nerve stimulation when a prosthetic hand was moved passively or was controlled actively by the subjects. Using a 2×8 electrode grid placed along the subject's upper arm, electrical stimulation was delivered to evoke somatotopic sensation along their index finger. Stimulation intensity, i.e. sensation strength, was modulated using the fingertip forces from a sensorized prosthetic hand. Object stiffness was encoded based on the rate of change of the evoked sensation as the prosthesis grasped one of three objects of different stiffness levels. During active control, sensation was modulated in real time as recorded forces were converted to stimulation amplitudes. During passive control, prerecorded force traces were randomly selected from a pool. Our results showed that the accuracy of object stiffness recognition was similar in both active and passive conditions. A slightly lower accuracy was observed during active control in one subject, which indicated that the sensorimotor integration processes could affect haptic perception for some users. 

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2. Quantitative Characterization of Haptic Sensory Adaptation Evoked Through Transcutaneous Nerve Stimulation

   https://doi.org/10.1109/ICHMS56717.2022.9980598  

   Prabhu, Nita ; Vargas, Luis ; Hu, Xiaogang ( November 2022 , 2022 IEEE 3rd International Conference on Human-Machine Systems (ICHMS))

   Objective: Haptic perception is an important component of bidirectional human-machine interactions that allow users to better interact with their environment. Artificial haptic sensation along an individual’s hand can be evoked via noninvasive electrical nerve stimulation; however, continuous stimulation can result in adaptation of sensory perception over time. In this study, we sought to quantify the adaptation profile via the change in perceived sensation intensity over time. Approach: Noninvasive stimulation of the peripheral nerve bundles evoked haptic perception using a 2x5 electrode grid placed along the medial side of the upper arm near the median and ulnar nerves. An electrode pair that evoked haptic sensation along the forearm and hand was selected. During a trial of 110-s of continuous stimulation, a constant stimulus amplitude just below the motor threshold was delivered. Each subject was instructed to press on a force transducer producing a force amplitude matched with the perceived intensity of haptic sensation. Main Findings: A force decay (i.e., intensity of sensation) was observed in all 7 subjects. Variations in the rate of decay and the start of decay across subjects were also observed. Significance: The preliminary findings established the sensory adaptation profile of peripheral nerve stimulation. Accounting for these subject-specific profiles of adaptation can allow for more stable communication between a robotic device and a user. Additionally, sensory adaptation characterization can promote the development of new stimulation strategies that can mitigate these observed adaptations, allowing for a better and more stable human-machine interaction experience. 

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3. Distally-referred surface electrical nerve stimulation (DR-SENS) for haptic feedback

   https://doi.org/10.1088/1741-2552/ad0563  

   Mesias, Luis ; Gormez, M. Akif ; Tyler, Dustin J. ; Makowski, Nathaniel S. ; Graczyk, Emily L. ; Fu, Michael J. ( December 2023 , Journal of Neural Engineering)

   Objective.This study’s objective is to understand distally-referred surface electrical nerve stimulation (DR-SENS) and evaluates the effects of electrode placement, polarity, and stimulation intensity on the location of elicited sensations in non-disabled individuals.Approach.A two-phased human experiment was used to characterize DR-SENS. In Experiment One, we explored 182 electrode combinations to identify a subset of electrode position combinations that would be most likely to elicit distally-referred sensations isolated to the index finger without discomfort. In Experiment Two, we further examined this subset of electrode combinations to determine the effect of stimulation intensity and electrode position on perceived sensation location. Stimulation thresholds were evaluated using parameter estimation by sequential testing and sensation locations were characterized using psychometric intensity tests.Main Results.We found that electrode positions distal to the wrist can consistently evoke distally referred sensations with no significant polarity dependency. The finger-palm combination had the most occurrences of distal sensations, and the different variations of this combination did not have a significant effect on sensation location. Increasing stimulation intensity significantly expanded the area of the sensation, moved the most distal sensation distally, and moved the vertical centroid proximally. Also, a large anodic-leading electrode at the elbow mitigated all sensation at the anodic-leading electrode site while using symmetric stimulation waveforms. Furthermore, this study showed that the most intense sensation for a given percept can be distally referred. Lastly, for each participant, at least one of the finger-palm combinations evaluated in this study worked at both perception threshold and maximum comfortable stimulation intensities.Significance.These findings show that a non-invasive surface electrical stimulation charge modulated haptic interface can be used to elicit distally-referred sensations on non-disabled users. Furthermore, these results inform the design of novel haptic interfaces and other applications of surface electrical stimulation based haptic feedback on electrodes positioned distally from the wrist.

    

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4. Activation of Superficial and Deep Finger Flexors through Transcutaneous Nerve Stimulation

   https://doi.org/10.1109/JBHI.2020.3041669  

   Shin, Henry ; Hawari, Marwan A. ; Hu, Xiaogang ( October 2020 , IEEE Journal of Biomedical and Health Informatics)

   null (Ed.)

   Objective: Functional electrical stimulation (FES) is a common technique to elicit muscle contraction and help improve muscle strength. Traditional FES over the muscle belly typically only activates superficial muscle regions. In the case of hand FES, this prevents the activation of the deeper flexor muscles which control the distal finger joints. Here, we evaluated whether an alternative transcutaneous nerve-bundle stimulation approach can activate both superficial and deep extrinsic finger flexors using a high-density stimulation grid. Methods: Transverse ultrasound of the forearm muscles was used to obtain cross-sectional images of the underlying finger flexors during stimulated finger flexions and kinematically-matched voluntary motions. Finger kinematics were recorded, and an image registration method was used to capture the large deformation of the muscle regions during each flexion. This deformation was used as a surrogate measure of the contraction of muscle tissue, and the regions of expanding tissue can identify activated muscles. Results: The nerve-bundle stimulation elicited contractions in the superficial and deep finger flexors. Both separate and concurrent activation of these two muscles were observed. Joint kinematics of the fingers also matched the expected regions of muscle contractions. Conclusions: Our results showed that the nerve-bundle stimulation technique can activate the deep extrinsic finger flexors, which are typically not accessible via traditional surface FES. Significance: Our nerve-bundle stimulation method enables us to produce the full range of motion of different joints necessary for various functional grasps, which could benefit future neuroprosthetic applications. 

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5. Artifact propagation in electrocorticography stimulation

   Lim, J. ; Wang, P.T. ; Shaw, S.J. ; Armacost, M. ; Gong, H. ; Liu, C.Y. ; Heydari, P. ; Do, A.H. ; Nenadic, Z. ( May 2018 , Seventh International BCI Meeting, Abstract Book)

   Introduction:Current brain-computer interfaces (BCIs) primarily rely on visual feedback. However, visual feedback may not be sufficient for applications such as movement restoration, where somatosensory feedback plays a crucial role. For electrocorticography (ECoG)-based BCIs, somatosensory feedback can be elicited by cortical surface electro-stimulation [1]. However, simultaneous cortical stimulation and recording is challenging due to stimulation artifacts. Depending on the orientation of stimulating electrodes, their distance to the recording site, and the stimulation intensity, these artifacts may overwhelm the neural signals of interest and saturate the recording bioamplifiers, making it impossible to recover the underlying information [2]. To understand how these factors affect artifact propagation, we performed a preliminary characterization of ECoG signals during cortical stimulation.Materials/Methods/ResultsECoG electrodes were implanted in a 39-year old epilepsy patient as shown in Fig. 1. Pairs of adjacent electrodes were stimulated as a part of language cortical mapping. For each stimulating pair, a charge-balanced biphasic square pulse train of current at 50 Hz was delivered for five seconds at 2, 4, 6, 8 and 10 mA. ECoG signals were recorded at 512 Hz. The signals were then high-pass filtered (≥1.5 Hz, zero phase), and the 5-second stimulation epochs were segmented. Within each epoch, artifact-induced peaks were detected for each electrode, except the stimulating pair, where signals were clipped due to amplifier saturation. These peaks were phase-locked across electrodes and were 20 ms apart, thus matching the pulse train frequency. The response was characterized by calculating the median peak within the 5-second epochs. Fig. 1 shows a representative response of the right temporal grid (RTG), with the stimulation channel at RTG electrodes 14 and 15. It also shows a hypothetical amplifier saturation contour of an implantable, bi-directional, ECoG-based BCI prototype [2], assuming the supply voltage of 2.2 V and a gain of 66 dB. Finally, we quantify the worstcase scenario by calculating the largest distance between the saturation contour and the midpoint of each stimulating channel.Discussion:Our results indicate that artifact propagation follows a dipole potential distribution with the extent of the saturation region (the interior of the white contour) proportional to the stimulation amplitude. In general, the artifacts propagated farthest when a 10 mA current was applied with the saturation regions extending from 17 to 32 mm away from the midpoint of the dipole. Consistent with the electric dipole model, this maximum spread happened along the direction of the dipole moment. An exception occurred at stimulation channel RTG11-16, for which an additional saturation contour emerged away from the dipole contour (not shown), extending the saturation region to 41 mm. Also, the worst-case scenario was observed at 6 mA stimulation amplitude. This departure could be a sign of a nonlinear, switch-like behavior, wherein additional conduction pathways could become engaged in response to sufficiently high stimulation.Significance:While ECoG stimulation is routinely performed in the clinical setting, quantitative studies of the resulting signals are lacking. Our preliminary study demonstrates that stimulation artifacts largely obey dipole distributions, suggesting that the dipole model could be used to predict artifact propagation. Further studies are necessary to ascertain whether these results hold across other subjects and combinations of stimulation/recording grids. Once completed, these studies will reveal practical design constraints for future implantable bi-directional ECoG-based BCIs. These include parameters such as the distances between and relative orientations of the stimulating and recording electrodes, the choice of the stimulating electrodes, the optimal placement of the reference electrode, and the maximum stimulation amplitude. These findings would also have important implications for the design of custom, low-power bioamplifiers for implantable bi-directional ECoG-based BCIs.References:[1] Hiremath, S. V., et al. "Human perception of electrical stimulation on the surface of somatosensory cortex." PloS one 12.5 (2017): e0176020.[2] Rouse, A. G., et al. "A chronic generalized bi-directional brain-machine interface." Journal of Neural Engineering 8.3 (2011): 036018 

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