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181 results for “tactile”
Primary somatosensory cortical processing in tactile communication
<p>Touch is an essential form of non-verbal communication. While language and its neural basis are widely studied, tactile communication is less well understood. We used fMRI and multivariate pattern analyses in pairs of emotionally close adults to examine the neural basis of human-to-human tactile communication. In each pair, a participant was designated either as sender or as receiver. The sender was instructed to communicate specific messages by touching only the arm of the receiver, who was inside the scanner. The receiver then identified the message based on the touch expression alone. We designed two multivariate decoder algorithms – one based on the sender’s intent (sender-decoder), and another based on the receiver’s response (receiver-decoder). We identified several brain areas that significantly predicted behavioral accuracy of the receiver. Regarding our a priori region of interest, the receiver’s primary somatosensory cortex (S1), both decoders were able to accurately differentiate the messages based on neural activity patterns here. The receiver-decoder, which relied on the receivers’ interpretations of the touch expressions, outperformed the sender-decoder, which relied on the sender’s intent. Our results identified a network of brain areas involved in human-to-human tactile communication and supported the notion of non-sensory factors being represented in S1.</p> <p>Log files per subject and run (end of file name: subID_run_log.csv)</p> <p>response mat file per subject receiver_only and sender_only</p> <p>readresponsemat_SVM_S1...m = reads in response mat files and performs SVM classification</p> <p>ECOC_S1.m = decoding code</p> <p>Normalized brain scan data can be found here: https://zenodo.org/records/4925648</p>
Magnetic Hair Tactile Sensor for Directional Pressure Detection
<p><span>Tactile sensing in the human body is achieved via the skin. This has inspired the fabrication of synthetic skins with pressure sensors for potential applications in robotics, bio-medicine, and human-machine interfaces. Tactile sensors based on magnetic elements are promising as they provide high sensitivity and a wide dynamic range. However, current magnetic tactile sensors mostly detect pressures of solid objects and operate at relatively high forces about 100 mN. Here, we address these limitations by manufacturing soft, stretchable, and hair-like structures that are permanently magnetized to achieve high-resolution, cost-effective, and high-resolution pressure sensing. Combining these hair-like structures with advances in 3D magnetic-field measurements allows us to monitor directional tactile pressures without solid contact. To prove the concept of this technology, we built a bio-inspired soft device with a hairy structure that senses and reports environmental mechanical stresses, similar to that of human skin. Simple self-assembly of the soft magnetic hair structure makes our approach easy to scale for large-area applications.</span></p>
Sim2Real Bilevel Adaptation for Object Surface Classification using Vision-Based Tactile Sensors, dataset
<p>This is the dataset used in the 'Sim2Real Bilevel Adaptation for Object Surface Classification using Vision-Based Tactile Sensors.' It contains 2 folders:</p> <ol> <li><strong>train_diffusion</strong>: a set of 5,000 images used to train the diffusion model.</li> <li><strong>translated</strong>: a set of approximately 50,000 images converted via a diffusion model pre-trained on a small set of real images.</li> </ol> <p>The 'translated' folder contains a <code>labels.csv</code> file, providing the corresponding label for every image.</p>
Dataset from 'Klever, L., Voudouris, D., Fiehler, K., & Billino, J. (2019). Age effects on sensorimotor predictions: What drives increased tactile suppression during reaching? Journal of Vision, 19(9):9, 1-17. doi:10.1167/19.9.9
<p>Dataset associated with the following publication:</p> <p>Klever, L., Voudouris, D., Fiehler, K., & Billino, J. (2019). Age effects on sensorimotor predictions: What drives increased tactile suppression during reaching? Journal of Vision.</p> <p>--------------------------------------------------------------</p> <p>We provide two files; one data file contains data on which analyses are based, the other one gives the column labels for the data file.</p> <p>-------------------------------------------------------------</p> <p>For further questions, please contact:<br> lena.klever[at]psychol.uni-giessen.de</p> <p> </p>
Seeing the piles of the velvet bending under our finger sliding over a tactile stimulator improves the feeling of the fabric
<p>Using friction modulation to simulate fabrics with a tactile stimulator (i.e. virtual surface) is not<br>sufficient to render fabric touch and even more so for hairy fabrics. We hypothesized that seeing<br>the pile of the velvet darken or lighten depending on changes in the finger movement direction<br>on the virtual surface should improve the velvet fabric rendering.</p> <p><strong>Experiment 1</strong> : Participants actively rubbed a tactile device or a velvet fabric looking at a screen that showed a synthesized image of a velvet which either remained static (V-static) or darkening/lightening with the direction of touch (V-moving). We showed that in V-moving condition, the touched surface was always perceived rougher, which is a descriptor of a real velvet<strong>.</strong></p> <p><em>Files : data_brutes.csv</em> and <em> ordre_xx_c.csv</em> for data,<em> Calculus_data_expe1.Rmd</em> for code</p> <p><strong>Experiment 2</strong> : Using electroencephalography and sources localization analyses, we found increased activity in the occipital and inferiorparietal lobes when seeing dark and shinning traces during back and forth finger<br>movements over the virtual surface. This suggests that these two posterior cortical regions work<br>together to evaluate visuo-tactile congruence between the seen and the felt (tactile). The visuotactile binding, evidenced by neural synchronization (specifically, theta band [5-7 Hz] oscillation) in the left inferior posterior parietal lobule, is consistent with enhanced integration of information and likely contributed to the emergence of a more realistic velvet representation. </p> <p><em>Files </em>: <em>EEG time frequency individual data.xlsx</em> and all <em>.eeg</em></p>
Tactile Stimulation in a Healthy Mexican Sample: An EEG Database
<p>Tecnologico de Monterrey School of Engineering and Sciences </p> <p>NeuroTechs Research Group</p> <p><strong>Context:</strong> This dataset includes electroencephalographic (EEG) recordings from 34 healthy, young adults in Mexico, collected to study the somatosensory system's responses to a range of tactile stimuli. The study employs innovative NeuroSense tactile stimulators to explore how the brain processes touch sensations when subjected to stimuli such as air, vibration, and caress at four distinct intensity levels.</p> <p><strong>Objective: </strong>The objective of this database is to understand the cortical processing of tactile stimuli including air, vibration and caress using EEG.</p> <p><strong>Main Outcome Measure:</strong> The main outcome measure is the EEG recordings which include the evoked responses of the somatosensory system to each type of stimulus and intensities. These measurements allow for an in-depth analysis of the cortical dynamics involved in processing touch.</p> <p><strong>Limitations</strong>: One limitation of the database is its focus on a relatively small and specific population, which could affect the generalizability of the findings. Additionally, the data is dependent on the accuracy and consistency of the stimulus delivery and EEG recording during the experimental sessions.</p> <p><strong>Generalizability:</strong> While the findings provide significant insights into the neural processing of tactile stimuli within the central nervous system, their generalizability might be limited due to the specialized nature of the stimuli and the controlled experimental conditions. However, the dataset serves as a valuable resource for developing diagnostic and therapeutic strategies for somatosensory impairments and advancing research in neuroscience and somatosensory rehabilitation.</p>
Effects of a Vibro-Tactile P300 Based Brain-Computer Interface on the Coma Recovery Scale-Revised in Patients With Disorders of Consciousness
<p>Persons diagnosed with disorders of consciousness (DOC) typically suffer from motor and cognitive disabilities. Recent research has shown that non-invasive brain-computer interface (BCI) technology could help assess these patients’ cognitive functions and command following abilities. 20 DOC patients participated in the study and performed 10 vibro-tactile P300 BCI sessions over 10 days with 8–12 runs each day. Vibrotactile tactors were placed on the each patient’s left and right wrists and one foot. Patients were instructed, via earbuds, to concentrate and silently count vibrotactile pulses on either their left or right wrist that presented a target stimulus and to ignore the others. Changes of the BCI classification accuracy were investigated over the 10 days. In addition, the Coma Recovery Scale-Revised (CRS-R) score was measured before and after the 10 vibro-tactile P300 sessions. In the first run, 10 patients had a classification accuracy above chance level (>12.5%). In the best run, every patient reached an accuracy ≥60%. The grand average accuracy in the first session for all patients was 40%. In the best session, the grand average accuracy was 88% and the median accuracy across all sessions was 21%. The CRS-R scores compared before and after 10 VT3 sessions for all 20 patients, are showing significant improvement (<em>p</em> = 0.024). Twelve of the twenty patients showed an improvement of 1 to 7 points in the CRS-R score after the VT3 BCI sessions (mean: 2.6). Six patients did not show a change of the CRS-R and two patients showed a decline in the score by 1 point. Every patient achieved at least 60% accuracy at least once, which indicates successful command following. This shows the importance of repeated measures when DOC patients are assessed. The improvement of the CRS-R score after the 10 VT3 sessions is an important issue for future experiments to test the possible therapeutic applications of vibro-tactile and related BCIs with a larger patient group.</p>
Precise and stable edge orientation signaling by human first-order tactile neurons
<p><span>Fast-adapting type 1 (FA-1) and slow-adapting type 1 (SA-1) first-order neurons in the human tactile system have distal axons that branch in the skin and form many transduction sites, yielding receptive fields with many highly sensitive zones or 'subfields'. We previously demonstrated that this arrangement allows FA-1 and SA-1 neurons to signal the geometric features of touched objects, specifically the orientation of raised edges scanned with the fingertips. Here we show that such signaling operates for fine edge orientation differences (5–20°) and is stable across a broad range of scanning speeds (15–180 mm/s); that is, under conditions relevant for real-world hand use. We found that both FA-1 and SA-1 neurons weakly signal fine edge orientation differences via the intensity of their spiking responses and only when considering a single scanning speed. Both neuron types showed much stronger edge orientation signaling in the sequential structure of the evoked spike trains and FA-1 neurons performed better than SA-1 neurons. Represented in the spatial domain, the sequential structure was strikingly invariant across scanning speeds, especially those naturally used in tactile spatial discrimination tasks. This speed invariance suggests that neurons' responses are structured via sequential stimulation of their subfields and thus links this capacity to their terminal organization in the skin. Indeed, the spatial precision of elicited action potentials rationally matched spatial acuity of subfield arrangements, which corresponds to a spatial period similar to the dimensions of individual fingertip ridges.</span></p>
Audio-tactile syllables EEG Dataset
<p>Dataset setting out to investigate behavioural and EEG responses to syllables coupled with tactile pulses at a 5Hz rhythm. The raw behavioural and EEG data is provided here.</p> <p><strong>#Introduction</strong></p> <p>This dataset contains the behavioural response to one syllable discrimination task in which subjects were subjected to regular tactile stimuli followed by a syllable in noise. It also contains the EEG response recorded during the task. There were 16 subjects, which IDs are : 'camembert', 'leader', 'bristol', 'policeman', 'frenchship', 'preacher', 'pretzel2new', 'canada', 'rotiqueen', 'kitten', 'batman', '2d', 'laundry2', 'bearcub', 'stopwatch' and 'tala'.</p> <p><strong>#Content</strong></p> <p>The dataset contains a folder named after each subject: these contain the eeg recordings for each of them as well as behavioural data. </p> <ul> <li><strong>id_Entrainment.csv: </strong>This csv file contains all the behvioural data about the subject (id). The different fields are as follow: <ul> <li>Trial: The ID of the current trial</li> <li>Type: Whether the tactile stimuli was audio-tactile rhythmic, audio-tactile random or audio-only</li> <li>Phase: In case it is audio-tactile, what is the phase between the onset of the vowel and the tactile rhythm. Note that we refer here to the phase relative to the rhythm of the tactile stimuli and not a measured rhythm. This choice was made as to sample the delays between audio and tactile as to be between 1 and 2 periods away from the rhythm we would expect to emerge from brain activity. The four phases can easily be translated to the following audio-tactile delays between the last tactile pulse and the onset of the syllable as: 150ms, 200ms, 250ms, 300ms.</li> <li>Score: 1 if the right syllable was selected by the subject, 0 otherwise.</li> <li>Syllable: the presented syllable out of the following set: ka, ga, ba, pa, da, ta</li> <li>Gender: The gender of the speaking voice, m for male, f for female</li> <li>Shift: A random shift between the onset of the trial and the first tactile pulse. Note that this value is representing the number of samples at a sampling frequency of 39062.5 (imposed by our hardware: TDT RX8)</li> <li>Random: The number of the random tactile stimulation. Since these were generated procedurally, we recorded them for reference, however, they do not play a part in the analysis. </li> </ul> </li> <li><strong>id.eeg, id.vhdr, id.vmrk:</strong> These correspond to the recorded data. More information on these file formats can be found on the <a href="https://www.fieldtriptoolbox.org/getting_started/brainvision/">Brian vision webpage</a>. </li> </ul> <p><strong>#EEG Data Format</strong></p> <p>We recorded continuous EEG from the participants over an hour at 1kHz. </p> <p>In addition to the 63 channels, there is also Stimtrack channel labelled as 'Sound' which was tracking an addition of the auditory and tactile stimuli and allowed to track the sent stimuli as well as the alignment. The corresponding files can be found using the provided .csv file.</p> <p> The .vmrk file provided contains the timing of the triggers sent at the start of each trial and can help with tracking the progress in the experiment. </p>
Dataset from 'Klever, L., Beyvers, M., Fiehler, K., Mamassian, P., & Billino, J. (2023). Cross-modal metacognition: Visual and tactile confidence share a common scale. Journal of Vision, 23(5): 3, 1-16. doi: https://doi.org/10.1167/jov.23.5.1
<p>We provide two files:<br> - "data.txt": data file containing the data of our final sample (N=54) on which analyses are based<br> - "column_description.txt": description file providing information on the content of each column in the data file</p> <p>___________________________________________<br> For further questions, please contact:<br> jutta.billino[at]psychol.uni-giessen.de</p>
Tactile model of Museum Insel, Berlin, DE
>Since 2011, a bronze model of the Museum Island, donated by the Rotary Clubs of Berlin-Süd and Berlin-Nord, has been on display there to help visitors – both with and without visual impairments – orient themselves and to educate them about the urban development and historical significance of this UNESCO World Heritage Site. ~ https://www.smb.museum/en/whats-new/detail/handover-ceremony-for-newly-expanded-tactile-model-of-berlins-museum-island/ 505 images, iPhone 13 Pro, RealityCapture ## 💾 9.9 Million face model available in the additional file download:  Source: Objaverse 1.0 / Sketchfab
Safety and Efficacy of Vibro-tactile Feedback for Patients Who Underwent Lower Limb Amputation
ClinicalTrials.gov study NCT05895253. IPD Sharing: YES. Countries: 1. Publications: 1.
Passive Tactile Stimulation for Stroke Rehabilitation
ClinicalTrials.gov study NCT03814889. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Usability of Vibro-tactile Stimulation to Treat Spasmodic Dysphonia
ClinicalTrials.gov study NCT06111027. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Data From: Tactile Echoes: Multisensory Augmented Reality for the Hand
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Data and code from: Sub-surface deformation of individual fingerprint ridges during tactile interactions
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Towards human-resolution haptics: A high bandwidth, high density, wearable tactile display
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Explosion-powered eversible tactile displays
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Alpha modulation of spiking activity across multiple brain regions in mice performing a tactile selective detection task
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Dataset for finger motion and contact by a second finger influence the tactile perception of electrovibration
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