Touch Detection Research Articles

Sexual dimorphism in the dorsal root ganglia of neonatal mice identified by protein expression profiling with single-cell mass cytometry

Development of neuronal and glial populations in the dorsal root ganglia (DRG) is required for detection of touch, body position, temperature, and noxious stimuli. While female-male differences in somatosensory perception have been previously reported, no study has examined global sex differences in the abundance of DRG cell types, and the developmental origin of these differences has not been characterized. To investigate whether sex-specific differences in neuronal and glial cell types arise in the DRG during development, we performed single-cell mass cytometry analysis on sex-separated DRGs from 4 separate litter replicates of postnatal day 0 (P0) C57/BL6 mouse pups. In this analysis, we observed that females had a higher abundance of total neurons (p = 0.0266), as well as an increased abundance of TrkB+ (p = 0.031) and TrkC+ (p = 0.04) neurons for mechanoreception and proprioception, while males had a higher abundance of TrkA+ (p = 0.025) neurons for thermoreception and nociception. Pseudotime comparison of the female and male datasets indicates that male neurons are more mature and differentiated than female neurons at P0. These findings warrant further studies to determine whether these differences are maintained across development, and their impact on somatosensory perception.

Development of robust sensor packages for autonomous underwater vehicles

New generations of robots are designed to support humans with a variety of partially or fully automated services. Such flexible and mobile service robots cooperate with humans or even act completely independent. To achieve this, it is necessary to significantly improve their capabilities in terms of environment perception, data processing and movement. At the same time, they must meet the highest standards of reliability and safety. Innovative electronics enable the necessary improvements and thus appropriate robot behavior. The aim of the Bionic RoboSkin project is to enhance the possibilities of a robot platform that is capable of autonomously navigating its respective environment by means of a flexible bionic sensor skin. The sensor platform is an autonomous underwater vehicle [AUV] that is based on the bionic principles of a Manta Ray [1, 2, 3]. The newly developed sensor skin consists of a textile composite as a carrier for sensor elements and provides moisture-resistant electrical connections for energy supply and communication. The integrated sensor modules enable both the detection of touch and approach and the exploration of the environment. The functionality of the sensor skin is targeting two service robotics applications: autonomous surveying of underwater structures (e.g. inspection of pipelines) and semi-autonomous geo-exploration in difficult-to-access areas (e.g. monitoring in tunnel construction). As a result, the paper presents the concept of a modular packaging platform for the use in a harsh marine environment. The technologies used for the miniaturization of the sensor module by PCB embedding and for outer housing development will be discussed in detail and a strong focus is put on packaging material properties in sub-marine conditions.

From 2D to 3D

Mid-air text entry on virtual keyboards suffers from the lack of tactile feedback, which brings challenges to both tap detection and input prediction. In this paper, we explored the feasibility of single-finger typing on virtual QWERTY keyboards in mid-air. We first conducted a study to examine users' 3D typing behavior on different sizes of virtual keyboards. Results showed that the participants perceived the vertical projection of the lowest point on the keyboard during a tap as the target location and inferring taps based on the intersection between the finger and the keyboard was not applicable. Aiming at this challenge, we derived a novel input prediction algorithm that took the uncertainty in tap detection into a calculation as probability, and performed probabilistic decoding that could tolerate false detection. We analyzed the performance of the algorithm through a full-factorial simulation. Results showed that the SVM-based probabilistic touch detection together with a 2D elastic probabilistic decoding algorithm (elasticity = 2) could achieve the optimal top-5 accuracy of 94.2%. In the evaluation user study, the participants reached a single-finger typing speed of 26.1 WPM with 3.2% uncorrected word-level error rate, which was significantly better than both tap-based and gesture-based baseline techniques. Also, the proposed technique received the highest preference score from the users, proving its usability in real text entry tasks.

Quantitative Sensory Changes Following Posterior Spinal Fusion to Treat Adolescent Idiopathic Scoliosis.

Sensory changes surrounding the incision frequently develop after posterior spinal fusion (PSF) to treat adolescent idiopathic scoliosis (AIS). Anecdotally, patients may experience sensory changes on the chest wall. Such postsurgical sensory changes are not well described quantitatively. This study aims to evaluate the presence, intensity, and duration of mechanical sensory changes in AIS patients postoperatively. A prospective cohort of AIS patients, 10 to 21 years old, was followed. Quantitative sensory testing (QST) included touch detection threshold [mechanical detection threshold (MDT)] and pain detection threshold (MPT), using VonFrey monofilaments and pinprick stimulators. QST was performed at 3 sites at T6: the right and left chest at the nipple line and adjacent to the incision below the inferior angle of the scapula. QST at the thenar eminence was the control. QST was collected at baseline, 3 days, 1, and 6 months postoperative. Thirty-four patients (21% males; mean age: 14.9 years old; median preoperative curve: 58 degrees) completed all testing. Mean deformity correction was 64% (SD: 10.4). Adjacent to the incision site, MDT was significantly higher compared with baseline at 3 days and 1 month ( P < 0.001) but not at 6 months ( P = 0.19), whereas MPT was significantly higher at 3 days, ( P < 0.001), 1 month ( P < 0.001), and 6 months ( P = 0.001). For the chest wall in all patients, MPT was higher on the left chest at 3 days ( P = 0.04) and on the right chest at 3 days ( P = 0.022) and 1 month ( P = 0.05). For patients with right-sided curves, MDT ( P = 0.01) and MPT ( P = 0.015) overall were significantly higher on the concave side (left) chest postoperatively. PSF is associated with sensory disturbances that are detectable within days, persist at 1 month, and improve at 6 months postoperatively adjacent to the incision and on the chest wall. We suspect that these sensory changes are transient. Describing postoperative sensory changes will help us better set postoperative expectations for patients undergoing PSF. Level I.

A Hydrogel-Based Electronic Skin for Touch Detection Using Electrical Impedance Tomography.

Recent advancement in wearable and robot-assisted healthcare technology gives rise to the demand for smart interfaces that allow more efficient human-machine interaction. In this paper, a hydrogel-based soft sensor for subtle touch detection is proposed. Adopting the working principle of a biomedical imaging technology known as electrical impedance tomography (EIT), the sensor produces images that display the electrical conductivity distribution of its sensitive region to enable touch detection. The sensor was made from a natural gelatin hydrogel whose electrical conductivity is considerably less than that of human skin. The low conductivity of the sensor enabled a touch-detection mechanism based on a novel short-circuiting approach, which resulted in the reconstructed images being predominantly affected by the electrical contact between the sensor and fingertips, rather than the conventionally used piezoresistive response of the sensing material. The experimental results indicated that the proposed sensor was promising for detecting subtle contacts without the necessity of exerting a noticeable force on the sensor.

Mechanotransduction events at the physiological site of touch detection.

Afferents of peripheral mechanoreceptors innervate the skin of vertebrates, where they detect physical touch via mechanically gated ion channels (mechanotransducers). While the afferent terminal is generally understood to be the primary site of mechanotransduction, the functional properties of mechanically activated (MA) ionic current generated by mechanotransducers at this location remain obscure. Until now, direct evidence of MA current and mechanically induced action potentials in the mechanoreceptor terminal has not been obtained. Here, we report patch-clamp recordings from the afferent terminal innervating Grandry (Meissner) corpuscles in the bill skin of a tactile specialist duck. We show that mechanical stimulation evokes MA current in the afferent with fast kinetics of activation and inactivation during the dynamic phases of the mechanical stimulus. These responses trigger rapidly adapting firing in the afferent detected at the terminal and in the afferent fiber outside of the corpuscle. Our findings elucidate the initial electrogenic events of touch detection in the mechanoreceptor nerve terminal.

Touch detection in augmented Omni-surface for human-robot teaming

This paper proposes an architecture that augments arbitrary surfaces into an interactive touching interface. The proposed architecture can detect the number of touching fingertips of human operators by detecting and recognizing the fingertips with a convolutional neural network (CNN). The inputs of the CNN model are images that are acquired by an RGB-D sensor. The aligned depth information acquired by the RGB-D sensor generates the plane model, which determines whether fingertips are touching the surface or not. Instead of the traditional plane modeling method that can only be used for flat surfaces, the proposed system can also work on curved surfaces. Corresponding gestures are defined based on the detected touching fingers on the surface. The feedback of the robots is projected on the working surface accordingly with an interactive projector. Compared to conventional programming interfaces, directly touching is much more natural for human beings. Based on the experiments, the proposed system could reduce the massive training time of operators.

Piezoelectric thick film for power-efficient haptic actuator

Emerging haptic technology based on piezoelectric actuators enables to realize innovative tactile human–machine interface. The standard solution is based on stand-alone bulk ceramics glued directly on the haptic device. Thin-film actuators with metal–insulator–metal structure have been developed to directly integrate actuators on haptic plates. The thickness of thin films is limited to 2 μm, leading to large capacitance and, thus, too high-power consumption. To solve this issue, we developed haptic devices based on a 10 μm-thick PZT film deposited on a 0.65 mm-thick platinized silicon substrate. These thick films are made of a PZT composite slurry associated with sol-gel sol infiltration. They are dense and exhibit a permittivity of 1000 and dielectric loss lower than 0.05. Our fabricated haptic device containing three actuators connected in series exhibits an antisymmetric Lamb wave resonant mode at 62.0 kHz, in line with finite element modeling. At the limit of touch detection (1 μm out of plane deflection), the power consumption of the haptic device is 150 mW at 40 V. This represents a 15-fold consumption reduction with respect to the same haptic device made with 0.5 μm-thick PZT thin films.

Reducing the Latency of Touch Tracking on Ad-hoc Surfaces

Touch sensing on ad-hoc surfaces has the potential to transform everyday surfaces in the environment - desks, tables and walls - into tactile, touch-interactive surfaces, creating large, comfortable interactive spaces without the cost of large touch sensors. Depth sensors are a promising way to provide touch sensing on arbitrary surfaces, but past systems have suffered from high latency and poor touch detection accuracy. We apply a novel state machine-based approach to analyzing touch events, combined with a machine-learning approach to predictively classify touch events from depth data with lower latency and higher touch accuracy than previous approaches. Our system can reduce end-to-end touch latency to under 70ms, comparable to conventional capacitive touchscreens. Additionally, we open-source our dataset of over 30,000 touch events recorded in depth, infrared and RGB for the benefit of future researchers.

Drosophila ppk19 encodes a proton-gated and mechanosensitive ion channel

In Drosophila larvae, nociceptive mdIV sensory neurons detect diverse noxious stimuli and prompt a nociceptive rolling response. Intriguingly, the same neurons also regulate stereotyped larval movement. The channels responsible for transducing these stimuli into electric signals are not yet fully identified. Here we undertook genetic and electrophysiological analysis of Ppk19, a member of the Deg/ENaC family of cationic channels. ppk19 mutants exhibited an impaired nociceptive rolling response upon mechanical force and acid, but no impairment in response to noxious temperature and gentle touch. Mutants also exhibited defective larval movement. RNAi against ppk19 in mdIV neurons likewise produced larvae with defects in mechanical and acid nociception and larval movement, but no impairment in detection of heat and gentle touch. Cultured cells transfected with ppk19 produced currents in acid and hypotonic solution, suggesting that ppk19 encodes an ion channel that responds to acid and cell swelling. Taken together, these findings suggest that Ppk19 acts in mdIV neurons as a proton- and mechano-gated ion channel to mediate acid- and mechano-responsive nociception and larval movement.

Columnar Lesions in Barrel Cortex Persistently Degrade Object Location Discrimination Performance.

Primary sensory cortices display functional topography, suggesting that even small cortical volumes may underpin perception of specific stimuli. Traditional loss-of-function approaches have a relatively large radius of effect (>1 mm), and few studies track recovery following loss-of-function perturbations. Consequently, the behavioral necessity of smaller cortical volumes remains unclear. In the mouse primary vibrissal somatosensory cortex (vS1), "barrels" with a radius of ∼150 μm receive input predominantly from a single whisker, partitioning vS1 into a topographic map of well defined columns. Here, we train animals implanted with a cranial window over vS1 to perform single-whisker perceptual tasks. We then use high-power laser exposure centered on the barrel representing the spared whisker to produce lesions with a typical volume of one to two barrels. These columnar-scale lesions impair performance in an object location discrimination task for multiple days without disrupting vibrissal kinematics. Animals with degraded location discrimination performance can immediately perform a whisker touch detection task with high accuracy. Animals trained de novo on both simple and complex whisker touch detection tasks showed no permanent behavioral deficits following columnar-scale lesions. Thus, columnar-scale lesions permanently degrade performance in object location discrimination tasks.

Detecting Touch and Grasp Gestures Using a Wrist-Worn Optical and Inertial Sensing Network

Freehand gesture-based interaction promises to enable rich interaction in applications such as augmented reality, virtual reality, human-robot interaction, and robotic prosthetic devices. However, current sensing approaches are limited to mid-air whole hand gestures and fail to identify small-scale tactile interactions with unsensorized environments. Detecting tactile interactions may unlock potential new applications in augmented reality and human-robot interaction in which unsensorized surfaces are used as touch input devices. This work presents a novel wrist-worn sensing device that combines near-infrared and inertial measurement unit sensing to enable high-accuracy detection of surface touch and grasp interactions. Two convolutional neural networks were used to map device inputs to detect touch events, and classify them by gesture type or direction. We evaluated the accuracy and temporal precision of our system for event detection and classification. Results from an in-lab user study of 12 participants showed an average of 97% touch detection accuracy and 98% grasp detection accuracy. In our study, we found that near-infrared and inertial sensing are complementary and can be used in tandem to effectively address both touch event detection and directionality classification.

A realistic morpho-anatomical connection strategy for modelling full-scale point-neuron microcircuits

The modeling of extended microcircuits is emerging as an effective tool to simulate the neurophysiological correlates of brain activity and to investigate brain dysfunctions. However, for specific networks, a realistic modeling approach based on the combination of available physiological, morphological and anatomical data is still an open issue. One of the main problems in the generation of realistic networks lies in the strategy adopted to build network connectivity. Here we propose a method to implement a neuronal network at single cell resolution by using the geometrical probability volumes associated with pre- and postsynaptic neurites. This allows us to build a network with plausible connectivity properties without the explicit use of computationally intensive touch detection algorithms using full 3D neuron reconstructions. The method has been benchmarked for the mouse hippocampus CA1 area, and the results show that this approach is able to generate full-scale brain networks at single cell resolution that are in good agreement with experimental findings. This geometric reconstruction of axonal and dendritic occupancy, by effectively reflecting morphological and anatomical constraints, could be integrated into structured simulators generating entire circuits of different brain areas facilitating the simulation of different brain regions with realistic models.

Perceived timing of cutaneous vibration and intracortical microstimulation of human somatosensory cortex

BackgroundIntracortical microstimulation (ICMS) of somatosensory cortex can partially restore the sense of touch. Though ICMS bypasses much of the neuraxis, prior studies have found that conscious detection of touch elicited by ICMS lags behind the detection of cutaneous vibration. These findings may have been influenced by mismatched stimulus intensities, which can impact temporal perception. ObjectiveEvaluate the relative latency at which intensity-matched vibration and ICMS are perceived by a human participant. MethodsOne person implanted with microelectrode arrays in somatosensory cortex performed reaction time and temporal order judgment (TOJ) tasks. To measure reaction time, the participant reported when he perceived vibration or ICMS. In the TOJ task, vibration and ICMS were sequentially presented and the participant reported which stimulus occurred first. To verify that the participant could distinguish between stimuli, he also performed a modality discrimination task, in which he indicated if he felt vibration, ICMS, or both. ResultsWhen vibration was matched in perceived intensity to high-amplitude ICMS, vibration was perceived, on average, 48 ms faster than ICMS. However, in the TOJ task, both sensations arose at comparable latencies, with points of subjective simultaneity not significantly different from zero. The participant could discriminate between tactile modalities above chance level but was more inclined to report feeling vibration than ICMS. ConclusionsThe latencies of ICMS-evoked percepts are slower than their mechanical counterparts. However, differences in latencies are small, particularly when stimuli are matched for intensity, implying that ICMS-based somatosensory feedback is rapid enough to be effective in neuroprosthetic applications.

The off-line effect of affective touch on multisensory integration and tactile perceptual accuracy during the somatic signal detection task.

Affective touch refers to the emotional and motivational facets of tactile sensation and has been linked to the activation of a specialised system of mechanosensory afferents (the CT system), that respond optimally to slow caress-like touch. Affective touch has been shown to play an important role in the building of the bodily self: the multisensory integrated global awareness of one’s own body. Here we investigated the effects of affective touch on subsequent tactile awareness and multisensory integration using the Somatic Signal Detection Task (SSDT). During the SSDT, participants were required to detect near-threshold tactile stimulation on their cheek, in the presence/absence of a concomitant light. Participants repeated the SSDT twice, before and after receiving a touch manipulation. Participants were divided into two groups: one received affective touch (CT optimal; n = 32), and the second received non-affective touch (non-CT optimal; n = 34). Levels of arousal (skin conductance levels, SCLs) and mood changes after the touch manipulation were also measured. Affective touch led to an increase in tactile accuracy, as indicated by less false reports of touch and a trend towards higher tactile sensitivity during the subsequent SSDT. Conversely, non-affective touch was found to induce a partial decrease in the correct detection of touch possibly due to a desensitization of skin mechanoreceptors. Both affective and non-affective touch induced a more positive mood and higher SCLs in participants. The increase in SCLs was greater after affective touch. We conclude that receiving affective touch enhances the sense of bodily self therefore increasing perceptual accuracy and awareness. Higher SCLs are suggested to be a possible mediator linking affective touch to a greater tactile accuracy. Clinical implications are discussed.

Transparent Piezoelectric Polymer-Based Materials for Energy Harvesting and Multitouch Detection Devices

Energy harvesting devices allowing to recover wasted energy from the environment are increasingly being developed. Mechanical energy is one of the most interesting sources for energy harvesting, and piezoelectric materials present excellent overall properties for the scavenging of that energy. Piezoelectric polymers, and, in particular, poly(vinylidene fluoride), show appropriate mechanical properties for large amplitude movements, higher piezoelectric coefficients, and transparency and can be easily integrated into devices. A transparent piezoelectric energy harvesting device has been developed with screen-printed transparent (72%) and conductive (42 Ω/sq) electrodes on PVDF sheets with a d33 = −23 pC/N, generating about P ∼ 12 μW and P ∼ 8 μW under pressing and bending modes, corresponding to an energy per cycle of E∼ 37 nJ and E ∼ 55 nJ, respectively. The piezoelectric energy harvesting characteristics of the materials have been also theoretically evaluated, and the applicability of the materials for touch detection has been demonstrated.

Inclusive Adaptation of Existing Board Games for Gamers with and without Visual Impairments using a Spatial Augmented Reality Framework for Touch Detection and Audio Feedback

Board games allow us to share collective entertainment experiences. They entertain because of the interactions between players, physical manipulation of tokens and decision making. Unfortunately, most board games exclude people with visual impairments as they were not initially designed for players with special needs. Through a user-centered design process with an accessible game library and visually impaired players, we observed challenges and solutions in making existing board games accessible through handcrafted solutions (tactile stickers, braille labels, etc.). In a second step, we used Spatial Augmented Reality (SAR), to make existing board games inclusive by adding interactivity (GameARt). In a case study with an existing board game considered as not accessible (Jamaica), we designed an interactive SAR version with touch detection (JamaicAR). We evaluated this prototype in a user study with 5 groups of 3 players each, including sighted, low vision and blind players. All players, independent of visual status, were able to play the Augmented Reality game. Moreover, the game was rated positively by all players regarding attractiveness, play engrossment, enjoyment and social connectivity. Our work shows that Spatial Augmented Reality has the potential to make board games accessible to people with visual impairments when handcrafted adaptations fall short.

Research on Real-time Sensing Technology of Aerospace Interactive Behavior Based on Infrared Array Force Tactile

Aerospace robots can replace astronauts to complete dangerous work in the expanded space. How to efficiently and reliably interact with robots in complex and harsh space environment has become an urgent problem and technical challenge. Based on the infrared array force tactile technology, an infrared point force touch detection system is developed to realize the intention sensing of aerospace human-robot interaction. Based on multipoint positioning technology combined with image method and global combined optimal tracking method, the control software is designed, and the effective human-robot interaction in the process of cooperation is realized. Finally, the touch panel test effect of the system is given. This research can provide a theoretical basis for the practical application of aerospace human-robot interaction.

A novel and robust method of indexing the uncoded stripes for multi‐line based structured light application

Finding the correspondence between the captured and projected uncoded stripe pattern, which is called the indexing problem, has proved to be difficult to overcome reliably. Due to the interference of the non-ideal phenomena, the extracted stripe might be lost, increased or shifted undetectably. This letter proposes a graph-matching based method to address this problem. The captured stripes are categorized into two parts according to whether they should be offset after projection. For the non-offset stripes, they can be accurately indexed by the predetermined projection pattern. Based on the structural similarity that exists on the two kinds of stripes, we establish two graphs and match them to index the offset stripes fast and effectively. Thus, the iterative process in the previous study is avoided and the troublesome issues are solved. The proposed method is applied to the virtual touchpad scheme to make an arbitrary surface touch-sensitiveness. Experimental results show that the ameliorated virtual touchpad scheme yields an average touch detection accuracy of 96.07%, and the indexing accuracy evaluated by randomly selected patterns is 100%.

An Assessment of the Hopping Strategy and Inter-Limb Asymmetry during the Triple Hop Test: A Test–Retest Pilot Study

The aims of the present study are to: (1) determine within- and between-session reliability of multiple metrics obtained during the triple hop test; and (2) determine any systematic bias in both the test and inter-limb asymmetry scores for these metrics. Thirteen male young American football athletes performed three trials of a triple hop test on each leg on two separate occasions. In addition to the total distance hopped, manual detection of touch down and toe-off were calculated via video analysis, enabling flight time (for each hop), ground contact time (GCT), reactive strength index (RSI), and leg stiffness (between hops) to be calculated. Results showed all coefficient of variation (CV) values were ≤ 10.67% and intraclass correlation coefficients (ICC) ranged from moderate to excellent (0.53–0.95) in both test sessions. Intrarater reliability showed excellent reliability for all metrics (CV ≤ 3.60%, ICC ≥ 0.97). No systematic bias was evident between test sessions for raw test scores (g = −0.34 to 0.32) or the magnitude of asymmetry (g = −0.19 to 0.43). However, ‘real’ changes in asymmetry (i.e., greater than the CV in session 1) were evident on an individual level for all metrics. For the direction of asymmetry, kappa coefficients revealed poor-to-fair levels of agreement between test sessions for all metrics (K = −0.10 to 0.39), with the exception of the first hop (K = 0.69). These data show that, given the inherent limitations of distance jumped in the triple hop test, practitioners can confidently gather a range of reliable data when computed manually, provided sufficient test familiarization is conducted. In addition, although the magnitude of asymmetry appears to show only small changes between test sessions, limb dominance does appear to fluctuate between test sessions, highlighting the value of also monitoring the direction of the imbalance.