From finger friction to brain activation: Tactile perception of the roughness of gratings

When mechanical engineering inspired from physiology improves postural-related somatosensory processes

Despite numerous studies uncovering the neural signature of tactile processing, tactile afferent inputs relating to the contact surface has not been studied so far. Foot tactile receptors being the first stimulated by the relative movement of the foot skin and the underneath moving support play an important role in the sensorimotor transformation giving rise to a postural reaction. A biomimetic surface, i.e., complying with the skin dermatoglyphs and tactile receptors characteristics should facilitate the cortical processes. Participants (n = 15) stood either on a biomimetic surface or on two control surfaces, when a sudden acceleration of the supporting surface was triggered (experiment 1). A larger intensity and shorter somatosensory response (i.e., SEP) was evoked by the biomimetic surface motion. This result and the associated decrease of theta activity (5-7 Hz) over the posterior parietal cortex suggest that increasing the amount of sensory input processing could make the balance task less challenging when standing on a biomimetic surface. This key point was confirmed by a second experiment (n = 21) where a cognitive task was added, hence decreasing the attentional resources devoted to the balance motor task. Greater efficiency of the postural reaction was observed while standing on the biomimetic than on the control surfaces.

Friction and neuroimaging of active and passive tactile touch

Two types of exploratory touch including active sliding and passive sliding are usually encountered in the daily life. The friction behavior of the human finger against the surface of objects is important in tactile perception. The neural mechanisms correlating to tribological behavior are not fully understood. This study investigated the tactile response of active and passive finger friction characterized with functional near-infrared spectroscopy (fNIRS). The friction test and fNIRS test were performed simultaneously using the tactile stimulus of polytetrafluoroethylene (PTFE) specimens. Results showed that the sliding modes did not obviously influence the friction property of skin. While three cortex regions were activated in the prefrontal cortex (PFC), showing a higher activation level of passive sliding. This revealed that the tribological performance was not a simple parameter to affect tactile perception, and the difference in cortical hemodynamic activity of active and passive touch was also recognised. The movement-related blood flow changes revealed the role of PFC in integrating tactile sensation although there was no estimation task on roughness perception.

Stimulation enhancement effect of the combination of exoskeleton-assisted hand rehabilitation and fingertip haptic stimulation

Introduction

Providing stimulation enhancements to existing hand rehabilitation training methods may help stroke survivors achieve better treatment outcomes. This paper presents a comparison study to explore the stimulation enhancement effects of the combination of exoskeleton-assisted hand rehabilitation and fingertip haptic stimulation by analyzing behavioral data and event-related potentials.

Methods

The stimulation effects of the touch sensations created by a water bottle and that created by cutaneous fingertip stimulation with pneumatic actuators are also investigated. Fingertip haptic stimulation was combined with exoskeleton-assisted hand rehabilitation while the haptic stimulation was synchronized with the motion of our hand exoskeleton. In the experiments, three experimental modes, including exoskeleton-assisted grasping motion without haptic stimulation (Mode 1), exoskeleton-assisted grasping motion with haptic stimulation (Mode 2), and exoskeleton-assisted grasping motion with a water bottle (Mode 3), were compared.

Results

The behavioral analysis results showed that the change of experimental modes had no significant effect on the recognition accuracy of stimulation levels (p = 0.658), while regarding the response time, exoskeleton-assisted grasping motion with haptic stimulation was the same as grasping a water bottle (p = 0.441) but significantly different from that without haptic stimulation (p = 0.006). The analysis of event-related potentials showed that the primary motor cortex, premotor cortex, and primary somatosensory areas of the brain were more activated when both the hand motion assistance and fingertip haptic feedback were provided using our proposed method (P300 amplitude 9.46 μV). Compared to only applying exoskeleton-assisted hand motion, the P300 amplitude was significantly improved by providing both exoskeleton-assisted hand motion and fingertip haptic stimulation (p = 0.006), but no significant differences were found between any other two modes (Mode 2 vs. Mode 3: p = 0.227, Mode 1 vs. Mode 3: p = 0.918). Different modes did not significantly affect the P300 latency (p = 0.102). Stimulation intensity had no effect on the P300 amplitude (p = 0.295, 0.414, 0.867) and latency (p = 0.417, 0.197, 0.607).

Discussion

Thus, we conclude that combining exoskeleton-assisted hand motion and fingertip haptic stimulation provided stronger stimulation on the motor cortex and somatosensory cortex of the brain simultaneously; the stimulation effects of the touch sensations created by a water bottle and that created by cutaneous fingertip stimulation with pneumatic actuators are similar.

Soft Electronics for Health Monitoring Assisted by Machine Learning

Due to the development of the novel materials, the past two decades have witnessed the rapid advances of soft electronics. The soft electronics have huge potential in the physical sign monitoring and health care. One of the important advantages of soft electronics is forming good interface with skin, which can increase the user scale and improve the signal quality. Therefore, it is easy to build the specific dataset, which is important to improve the performance of machine learning algorithm. At the same time, with the assistance of machine learning algorithm, the soft electronics have become more and more intelligent to realize real-time analysis and diagnosis. The soft electronics and machining learning algorithms complement each other very well. It is indubitable that the soft electronics will bring us to a healthier and more intelligent world in the near future. Therefore, in this review, we will give a careful introduction about the new soft material, physiological signal detected by soft devices, and the soft devices assisted by machine learning algorithm. Some soft materials will be discussed such as two-dimensional material, carbon nanotube, nanowire, nanomesh, and hydrogel. Then, soft sensors will be discussed according to the physiological signal types (pulse, respiration, human motion, intraocular pressure, phonation, etc.). After that, the soft electronics assisted by various algorithms will be reviewed, including some classical algorithms and powerful neural network algorithms. Especially, the soft device assisted by neural network will be introduced carefully. Finally, the outlook, challenge, and conclusion of soft system powered by machine learning algorithm will be discussed.

Triple and Quadruple Surface Pattern Memories in Nanoimprinted Polymer Blends

Trigger-responsive surfaces with multiple surface properties have wide-ranging application potential from surfaces with trigger-responsive fluid flow to cell culture to optical effects; such surfaces can be achieved through surface morphological changes. Although multiple shape-memory effects are successful in bulk polymers, there is limited programing and recovery of multiple surface memories due to the challenges in fabricating multiple surface topographies with good controllability. Here, we report the synergy between the polymer blend formulation and the thermal nanoimprinting process to achieve multiple microtopography memories. A series of immiscible blends consisting of poly(caprolactone) (PCL) and polyethylene (PE) with distinct thermal transitions governed by distinct crystallization events were augmented with improved elasticity through preferential cross-linking in the polymer blend. The effect of preferential cross-linking by dicumyl peroxide on the elastic property of the PCL/PE has been found to be nonlinearly dependent on the blend composition. This approach enabled triple and quadruple surface pattern fixity and recovery in nanoimprinted PCL/PE blends. Specifically, we demonstrated the recovery of a micropillar structure (diameter: 20 μm and height: 10 μm) from a hierarchical micrograting topography (width: 2 μm and height: 2 μm) when exposed to a thermal stimulus at 60 °C for 180 s. Furthermore, we also demonstrated the recovery of a deformed micrograting followed by a secondary recovery of the micropillar structure.

Study of event-related potentials by withdrawal friction on the fingertip

OBJECTIVES

The lack of understanding about the brain's reaction processes in perceiving touch and separation between skin and object surfaces is a barrier to the development of existing brain-computer interface technologies and virtual haptics. These technologies are limited in their ability to advance. It leaves prosthesis users with a limited amount of tactile information that they can feel. This study aims to determine whether distinct surface aspects of various items trigger different reactions from the brain when friction is removed from the surface.

METHODS

When friction is suddenly removed from the surface of an item, a technique called event-related potential, (ERP) is used to study the features of people's EEGs. It is done after the subject has actively explored the object's surface. A 64-channels EEG collecting system was utilized to acquire EEG data from the individuals. [Corrections added on 5 December 2022, after first online publication: The preceding sentence has been updated.] The event-related potentials for friction removal were generated using the Oddball paradigm, and the samples consisted of sandpaper with three distinct degrees of roughness. We utilized a total of 20 participants, 10 of whom were male, and 10 of whom were female, with a mean age of 21 years.

RESULTS

It was discovered that the P3 component of event-related potentials, which is essential for cognition, was noticeably absent in the friction withdrawal response for various roughnesses. It was the case regardless of whether the surface was smooth or rough. Moreover, there was no statistically significant difference between the P1 andP2 components, which suggests that the brain could not recognize the surface properties of objects with varying roughness as the friction withdrawal was being performed.

CONCLUSIONS

It has been demonstrated that tactile recognition does not occur after friction withdrawal. The findings of this paper could have significant repercussions for future research involving the study of haptic perception and brain-computer interaction in prosthetic hands. It is a step toward future research on the mechanisms underlying human tactile perception, so think of it as preparation.

Effect of neuromorphic transcutaneous electrical nerve stimulation (nTENS) of cortical functional networks on tactile perceptions: An event-related electroencephalogram study

BACKGROUND

Transcutaneous electrical nerve stimulation (TENS) is generally applied for tactile feedback in the field of prosthetics. The distinct mechanisms of evoked tactile perception between stimulus patterns in conventional TENS (cTENS) and neuromorphic TENS (nTENS) are relatively unknown. This is the first study to investigate the neurobiological effect of nTENS for cortical functional mechanism in evoked tactile perception.

METHODS

Twenty-one healthy participants were recruited in this study. Electroencephalogram (EEG) was recorded while the participants underwent a tactile discrimination task. One cTENS pattern (square pattern) and two nTENS patterns (electromyography and single motor unit patterns) were applied to evoke tactile perception in four fingers, including the right and left index and little fingers. EEG was preprocessed and somatosensory-evoked potentials (SEPs) were determined. Then, source-level functional networks based on graph theory were evaluated, including clustering coefficient, path length, global efficiency, and local efficiency in six frequency bands.

RESULTS

Behavioral results suggested that the single motor units (SMU) pattern of nTENS was the most natural tactile perception. SEPs results revealed that SMU pattern exhibited significant shorter latency in P1 and N1 components than the other patterns, while nTENS patterns have significantly longer latency in P3 component than cTENS pattern. Cortical functional networks showed that the SMU pattern had the lowest short path and highest efficiency in beta and gamma bands.

CONCLUSION

This study highlighted that distinct TENS patterns could affect brain activities. The new characteristics in tactile manifestation of nTENS would provide insights for the application of tactile perception restoration.

Neural Coding of Vibration Intensity

Vibrotactile feedback technology has become widely used in human-computer interaction due to its low cost, wearability, and expressiveness. Although neuroimaging studies have investigated neural processes associated with different types of vibrotactile feedback, encoding vibration intensity in the brain remains largely unknown. The aim of this study is to investigate neural processes associated with vibration intensity using electroencephalography. Twenty-nine healthy participants (aged 18-40 years, nine females) experienced vibrotactile feedback at the distal phalanx of the left index finger with three vibration intensity conditions: no vibration, low-intensity vibration (1.56 g), and high-intensity vibration (2.26 g). The alpha and beta band event-related desynchronization (ERD) as well as P2 and P3 event-related potential components for each of the three vibration intensity conditions are obtained. Results demonstrate that the ERD in the alpha band in the contralateral somatosensory and motor cortex areas is significantly associated with the vibration intensity. The average power spectral density (PSD) of the peak period of the ERD (400-600 ms) is significantly stronger for the high- and low-vibration intensity conditions compared to the no vibration condition. Furthermore, the average PSD of the ERD rebound (700-2,000 ms) is significantly maintained for the high-vibration intensity compared to low-intensity and no vibration conditions. Beta ERD signals the presence of vibration. These findings inform the development of quantitative measurements for vibration intensities based on neural signals.

Brain activation related to the tactile perception of touching ridged texture using fingers

BACKGROUND

Humans can recognize the physical properties of objects by touching them, even when vision is unavailable. Tactile perception is important for humans in interacting with the environment. The triangular ridged textures are usually added to surface to improve the grip reliability of products, but the sharp edge of triangular ridge induces sharp and uncomfortable feeling.

MATERIALS AND METHODS

To study the effect of the edge shape of triangular ridged texture on brain activity, functional magnetic resonance imaging technique was used to obtain the blood oxygen level-dependent (BOLD) signal of subjects during the touching of textured surfaces. Samples with sharp, round, and flat shape ridged textures were chosen as the tactile stimulus.

RESULTS

The contralateral postcentral gyrus, the precentral gyrus, the inferior parietal lobule, and the supramarginal gyrus, corresponding with the functional regions of the primary somatosensory cortex (SI), the secondary somatosensory cortex (SII), and the primary motor cortex (MI) were related to the perception of three shape ridged textures. The main brain activation located in the postcentral gyrus and the SI. The tactile information of three shape ridged textures was received by Brodmann area (BA) 3 of the SI, and then inputted to BA 2 of the SI, the further tactile discrimination of shape of ridged textures was involved in BA40 of the SII. The intensity, the areas, and the percent signal change (PSC) of brain activation that were evoked by different shape ridged textures were related to the geometric structures of the ridged textures. The more complex the geometric structures of texture are, the larger the intensity, the area, and the PSC in brain activation are. The negative BOLD responses of the ipsilateral sensory cortex that were evoked by the flat ridged texture indicated the ipsilateral neuronal inhibition within the sensory systems. The bilateral precuneus, the superior parietal gyrus, and the inferior parietal gyrus, corresponding with the functional areas of the SII (BA40) and the SSA(BA7), were involved in the tactile discriminate of the differences in shapes of ridged textures. The differences in brain activation were related to the differences in geometric structures of the ridged texture. The larger the differences in geometric structure of texture are, the larger the differences in brain activation are. This study revealed the activated location of brain related to the tactile stimulation of different edge shape of ridged textures and the relationship between the geometric structures of ridged texture and brain activities. This research contributes to optimize surface tactile characteristics on products, especially effective surface textures design for good grip.

Ultrathin and Highly Tough Hydrogel Films for Multifunctional Strain Sensors

With good flexibility and biocompatibility, hydrogel-based sensors have been widely used in human motion detection, artificial intelligence, human-machine interface, and other fields. Previous research on hydrogel-based sensors has focused on improving the mechanical properties and signal transmission sensitivity. With the development of human smart devices, there is an increasing demand for hydrogel sensor comfort and more application functions, such as ultrathin structures and recognition functions for contact surfaces, which are realized with higher requirements for the thickness, flexibility, friction resistance, and biocompatibility of hydrogels. Inspired by the ultrathin and flexible characteristics of human organ biofilms, we constructed conductive hydrogel films by using the flim-casting and glycerol-H₂O secondary hydration methods. This ultrathin structure enables the hydrogel films to have a high elongation at break of 523.3%, a stress of 3.5 MPa, and a good friction resistance. Combined with the excellent sensing properties (gauge factor = 2.1 and a response time of 200 ms), the hydrogel film-based sensor can not only record human motion signals but also recognize the surface texture and roughness of objects, such as glass, brushes, wood, and sandpaper with mesh sizes of 80, 50, and 24, accurately. In addition, this hydrogel film has a series of excellent properties such as UV shielding, antiswelling ability, and good biocompatibility. This research provides a novel way for the development of emerging soft-material smart devices, such as hydrogel-based electronic skin and soft robots.

Quantifying the Generation Process of Multi-Level Tactile Sensations via ERP Component Investigation

Humans obtain characteristic information such as texture and weight of external objects, relying on the brain's integration and classification of tactile information; however, the decoding mechanism of multi-level tactile information is relatively elusive from the temporal sequence. In this paper, nonvariant frequency, along with the variant pulse width of electrotactile stimulus, was performed to generate multi-level pressure sensation. Event-related potentials (ERPs) were measured to investigate the mechanism of whole temporal tactile processing. Five ERP components, containing P100-N140-P200-N200-P300, were observed. By establishing the relationship between stimulation parameters and ERP component amplitudes, we found the following: (1) P200 is the most significant component for distinguishing multi-level tactile sensations; (2) P300 is correlated well with the subjective judgment of tactile sensation. The temporal sequence of brain topographies was implemented to clarify the spatiotemporal characteristics of the tactile process, which conformed to the serial processing model in neurophysiology and cortical network response area described by fMRI. Our results can help further clarify the mechanism of tactile sequential processing, which can be applied to improve the tactile BCI performance, sensory enhancement, and clinical diagnosis for doctors to evaluate the tactile process disorders by examining the temporal ERP components.

Decoding the coupling between the brain and skin reactions in auditory stimulation by information-based analysis of EEG and GSR signals

BACKGROUND

The analysis of brain activity in different conditions is an important research area in neuroscience.

OBJECTIVE

This paper analyzed the correlation between the brain and skin activities in rest and stimulations by information-based analysis of electroencephalogram (EEG) and galvanic skin resistance (GSR) signals.

METHODS

We recorded EEG and GSR signals of eleven subjects during rest and auditory stimulations using three pieces of music that were differentiated based on their complexity. Then, we calculated the Shannon entropy of these signals to quantify their information contents.

RESULTS

The results showed that music with greater complexity has a more significant effect on altering the information contents of EEG and GSR signals. We also found a strong correlation (r= 0.9682) among the variations of the information contents of EEG and GSR signals. Therefore, the activities of the skin and brain are correlated in different conditions.

CONCLUSION

This analysis technique can be utilized to evaluate the correlation among the activities of various organs versus brain activity in different conditions.

Investigation of Tactile Perception Evoked by Ridged Texture Using ERP and Non-linear Methods

The triangular ridged surface can improve the grip reliability of products, but the sharp edge of triangular ridge induces sharp and uncomfortable feeling. To study the effect of edge shape (sharp, round, and flat shape) of triangular ridges on brain activity during touching, electroencephalograph (EEG) signals during tactile perception were evaluated using event-related potentials (ERP) and non-linear analysis methods. The results showed that the early component of P100 and P200, and the late component of P300 were successfully induced during perceiving the ridged texture. The edge shape features affect the electrical activity of brain during the tactile perceptions. The sharp shape feature evoked fast P100 latency and high P100 amplitude. The flat texture with complex (sharp and flat) shape feature evoked fast P200 latency, high P200 amplitude and RQA parameters. Both of the sharp shape and complex shape feature tended to evoke high peak amplitude of P300. The large-scale structures of recurrence plots (RPs) and recurrence quantification analysis (RQA) parameters can visually and quantitatively characterize the evolution regulation of the dynamic behavior of EEG system along with the tactile process. This study proved that RPs and RQA were protential methods for the feature extraction and state recognition of EEG during tactile perception of textured surface. This research contributes to optimize surface tactile characteristics on products, especially effective surface textures design for good grip.