Development of a simple MR-compatible vibrotactile stimulator using a planar-coil-type actuator

NeuroSense: A non-invasive and configurable somatosensory stimulator with OPENVIBE communication

Understanding the somatosensory system and its abnormalities requires the development of devices that can accurately stimulate the human skin. New methods for assessing the somatosensory system can enhance the diagnosis, treatments, and prognosis for individuals with somatosensory impairments. Therefore, the design of NeuroSense, a tactile stimulator that evokes three types of daily life sensations (touch, air and vibration) is described in this work. The prototype aims to evoke quantitative assessments to evaluate the functionality of the somatosensory system and its abnormal conditions that affect the quality of life. In addition, the device has proven to have varying intensities and onset latencies that produces somatosensory evoked potentials and energy desynchronization on somatosensory cortex.

Changes in the BOLD signal of S1 and BA3 per finger/phalanx as a response to high-frequency vibratory stimulation

PURPOSE AND METHOD

The purpose of this study was to determine the changes in the Blood Oxygen Level Dependent signal of Primary somatosensory area (S1) and Brodmann area 3 (BA3) per finger and phalanx in comparison to the activation voxel when 250 Hz vibratory stimulation with high sensitivity for the Pacinian corpuscle was given to the four fingers and three phalanges.

RESULTS

The result of analyzing the activation voxel showed a significant difference for S1 per finger and phalanx, but for BA3, no significant difference was observed despite a similar trend to S1. In contrast, the activation intensity (BOLD) displayed a significant difference for S1 per finger and phalanx and for BA3, where the activation voxel had no significant variation. In addition, while the result of S1 did not indicate whether the index or the little fingers had the highest sensitivity based on the BOLD signal per finger, the result of BA3 marked the strongest BOLD signal for the little finger as a response to 250 Hz vibratory stimulation. The activation intensity per phalanx was the highest for the intermediate phalanx for S1 and BA3, which was in line with a previous study comparing the activation voxel.

CONCLUSIONS

The method based on the intensity of the nerve activation is presumed to have high sensitivity as the signal intensity is monitored within a specific, defined area. Thus, for the extraction of brain activation patterns of micro-domains, such as BA3, monitoring the BOLD signal that reflects the nerve activation intensity more sensitively is likely to be advantageous.

Assessing MR-compatibility of somatosensory stimulation devices: A systematic review on testing methodologies

Functional magnetic resonance imaging (fMRI) has been extensively used as a tool to map the brain processes related to somatosensory stimulation. This mapping includes the localization of task-related brain activation and the characterization of brain activity dynamics and neural circuitries related to the processing of somatosensory information. However, the magnetic resonance (MR) environment presents unique challenges regarding participant and equipment safety and compatibility. This study aims to systematically review and analyze the state-of-the-art methodologies to assess the safety and compatibility of somatosensory stimulation devices in the MR environment. A literature search, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement guidelines, was performed in PubMed, Scopus, and Web of Science to find original research on the development and testing of devices for somatosensory stimulation in the MR environment. Nineteen records that complied with the inclusion and eligibility criteria were considered. The findings are discussed in the context of the existing international standards available for the safety and compatibility assessment of devices intended to be used in the MR environment. In sum, the results provided evidence for a lack of uniformity in the applied testing methodologies, as well as an in-depth presentation of the testing methodologies and results. Lastly, we suggest an assessment methodology (safety, compatibility, performance, and user acceptability) that can be applied to devices intended to be used in the MR environment.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42021257838.

Development and Preliminary Validation of a Pneumatic Focal Vibration System to the Mitigation of Post-Stroke Spasticity

Some evidence has demonstrated that focal vibration (FV) plays an important role in the mitigation of spasticity. However, the research on developing the FV system to mitigate the spasticity effectively has been seldom reported. To relieve post-stroke spasticity, a new pneumatic FV system has been proposed in this paper. An image processing approach, in which the edge of vibration actuator was identified by the Canny edge detector, was utilized to quantify this system's parameters: the frequency ranging from 44 Hz to 128 Hz and the corresponding amplitude. Taking one FV protocol with the frequency of 87 Hz and the amplitude 0.28 mm of this system as an example, a clinical experiment was carried out. In the clinical experiment, FV was applied over the muscle belly of the antagonist of spastic muscle for twelve chronic spastic stroke patients. Spasticity was quantified by the muscle compliance and area under the curve for muscle (AUC_muscle). The result has demonstrated that, in the state of flexion of spastic muscle, the AUC_muscle and muscle compliance of the spastic muscle significantly increased immediately after FV compared with before-FV, illustrating the mitigation of the spasticity. This study will not only provide a potential tool to relieve post-stroke spasticity, but also contribute to improving the sensory and motor function of patients with other neurological diseases, e.g. spinal cord injury, multiple sclerosis, Parkinson and dystonia, etc.

A Simple and Compact MR-Compatible Electromagnetic Vibrotactile Stimulator

We have developed a low-cost electromagnetic vibrotactile stimulator that uses the magnetic field of an MR scanner as a permanent magnet to power a vibrating motor. A simple variable current power supply is controlled by software using a USB data acquisition controller. In our study, the function of our novel stimulator was verified in a vibration frequency discrimination working memory task, in which various ranges of frequencies and amplitudes are delivered in MRI scanner. Furthermore, our functional MRI study revealed activations of the primary and secondary somatosensory cortices during the perception of tactile stimulation. Therefore, the new designed electromagnetic vibrotactile stimulator is capable of generating various frequencies of tactile stimuli and represents a powerful and useful tool for studying somatosensory functions with functional MRI.

Neural Categorization of Vibrotactile Frequency in Flutter and Vibration Stimulations: An fMRI Study

As the use of wearable haptic devices with vibrating alert features is commonplace, an understanding of the perceptual categorization of vibrotactile frequencies has become important. This understanding can be substantially enhanced by unveiling how neural activity represents vibrotactile frequency information. Using functional magnetic resonance imaging (fMRI), this study investigated categorical clustering patterns of the frequency-dependent neural activity evoked by vibrotactile stimuli with gradually changing frequencies from 20 to 200 Hz. First, a searchlight multi-voxel pattern analysis (MVPA) was used to find brain regions exhibiting neural activities associated with frequency information. We found that the contralateral postcentral gyrus (S1) and the supramarginal gyrus (SMG) carried frequency-dependent information. Next, we applied multidimensional scaling (MDS) to find low-dimensional neural representations of different frequencies obtained from the multi-voxel activity patterns within these regions. The clustering analysis on the MDS results showed that neural activity patterns of 20-100 Hz and 120-200 Hz were divided into two distinct groups. Interestingly, this neural grouping conformed to the perceptual frequency categories found in the previous behavioral studies. Our findings therefore suggest that neural activity patterns in the somatosensory cortical regions may provide a neural basis for the perceptual categorization of vibrotactile frequency.

Inter- and Intradigit Somatotopic Map of High-Frequency Vibration Stimulations in Human Primary Somatosensory Cortex

Although more about the somatotopic mapping of fingers continues to be uncovered, there is lack of mapping attempts regarding the integration of within-finger and across-finger somatotopic coordinates in Broadmann area (BA) 3. This study aimed to address the issue by finding an inter-/intradigit somatotopic map with high-frequency (250 Hz) vibrotactile stimulation. Functional magnetic resonance imaging (fMRI) data were acquired while stimulation was applied to 3 phalanxes (distal [p1], intermediate [p2], and proximal [p3] phalanx) of 4 fingers (index, middle, ring, and little finger) for a total of 12 finger-phalanx combinations for a human. Inter-, intra-, and inter-/intradigit distances were calculated from peak activation coordinates in BA 3 for each combination. With regard to interdigit dimensions, the somatotopic coordinates proceeded in the lateral-to-medial direction for the index, middle, ring, and little fingers consecutively. This trend is comparable to that generated from low-frequency stimulation modalities (flutter stimulation). The somatotopic distances between fingers were greatest when p1 was compared across fingers. From an intradigit perspective, stimulation on p1, p2, and p3 yielded BA 3 peak coordinates aligned along the anterior-to-posterior and inferior-to-superior directions for all fingers. An inter-/intradigit map exhibited a radially propagating trend of distances calculated with respect to index p1 as a reference point; this provided an integrated view of inter- and intradigit somatotopies, which are traditionally discussed separately. We expect such an inter-/intradigit somatotopic map approach to contribute in generating a comprehensive somatotopic model of fingers.

Distributed functions of detection and discrimination of vibrotactile stimuli in the hierarchical human somatosensory system

According to the hierarchical view of human somatosensory network, somatic sensory information is relayed from the thalamus to primary somatosensory cortex (S1), and then distributed to adjacent cortical regions to perform further perceptual and cognitive functions. Although a number of neuroimaging studies have examined neuronal activity correlated with tactile stimuli, comparatively less attention has been devoted toward understanding how vibrotactile stimulus information is processed in the hierarchical somatosensory cortical network. To explore the hierarchical perspective of tactile information processing, we studied two cases: (a) discrimination between the locations of finger stimulation; and (b) detection of stimulation against no stimulation on individual fingers, using both standard general linear model (GLM) and searchlight multi-voxel pattern analysis (MVPA) techniques. These two cases were studied on the same data set resulting from a passive vibrotactile stimulation experiment. Our results showed that vibrotactile stimulus locations on fingers could be discriminated from measurements of human functional magnetic resonance imaging (fMRI). In particular, it was in case (a) we observed activity in contralateral posterior parietal cortex (PPC) and supramarginal gyrus (SMG) but not in S1, while in case; (b) we found significant cortical activations in S1 but not in PPC and SMG. These discrepant observations suggest the functional specialization with regard to vibrotactile stimulus locations, especially, the hierarchical information processing in the human somatosensory cortical areas. Our findings moreover support the general understanding that S1 is the main sensory receptive area for the sense of touch, and adjacent cortical regions (i.e., PPC and SMG) are in charge of a higher level of processing and may thus contribute most for the successful classification between stimulated finger locations.

Evaluation of somatosensory cortical differences between flutter and vibration tactile stimuli

In parallel with advances in haptic-based mobile computing systems, understanding of the neural processing of vibrotactile information becomes of great importance. In the human nervous system, two types of vibrotactile information, flutter and vibration, are delivered from mechanoreceptors to the somatosensory cortex through segregated neural afferents. To investigate how the somatosensory cortex differentiates flutter and vibration, we analyzed the cortical responses to vibrotactile stimuli with a wide range of frequencies. Specifically, we examined whether cortical activity changed most around 50 Hz, which is known as a boundary between flutter and vibration. We explored various measures to evaluate separability of cortical activity across frequency and found that the hypothesis margin method resulted in the greatest separability between flutter and vibration. This result suggests that flutter and vibration information may be processed by different neural processes in the somatosensory cortex.

Frequency-dependent patterns of somatosensory cortical responses to vibrotactile stimulation in humans: a fMRI study

In the human mechanosensation system, rapidly adapting afferents project sensory signals of flutter (5-50Hz) to the contralateral primary somatosensory cortex (S1) and bilateral secondary somatosensory cortex (S2) whereas Pacinian afferents project sensory signals of vibration (50-400Hz) to bilateral S2. However, it remains largely unknown how somatosensory cortical activity changes as a function of vibrotactile frequency. This functional magnetic resonance imaging (fMRI) study investigated frequency dependency of somatosensory cortical activity in humans by applying vibrotactile stimulation with various frequencies (20-200Hz) to the index finger. We found more frequency-dependent voxels in the upper bank of the lateral sulcus (LS) of S2 than in S1 and the posterior parietal cortex of S2. Our statistical spatial clustering analysis showed that two groups of positively or negatively frequency-dependent voxels formed distinct clusters, most clearly in the LS. Using a cortical separability index, we reaffirmed that somatosensory cortical activity was most separable at 50Hz, previously known to demarcate flutter and vibration. Our results suggest that the LS (S2) may play an important role in processing vibrotactile frequency information and that the somatosensory cortex may include spatially localized neural assemblies specialized to higher or lower vibrotactile frequency.