The Use of Tactile Sensors in Oral and Maxillofacial Surgery: An Overview

BACKGROUND

This overview aimed to characterize the type, development, and use of haptic technologies for maxillofacial surgical purposes. The work aim is to summarize and evaluate current advantages, drawbacks, and design choices of presented technologies for each field of application in order to address and promote future research as well as to provide a global view of the issue.

METHODS

Relevant manuscripts were searched electronically through Scopus, MEDLINE/PubMed, and Cochrane Library databases until 1 November 2022.

RESULTS

After analyzing the available literature, 31 articles regarding tactile sensors and interfaces, sensorized tools, haptic technologies, and integrated platforms in oral and maxillofacial surgery have been included. Moreover, a quality rating is provided for each article following appropriate evaluation metrics.

DISCUSSION

Many efforts have been made to overcome the technological limits of computed assistant diagnosis, surgery, and teaching. Nonetheless, a research gap is evident between dental/maxillofacial surgery and other specialties such as endovascular, laparoscopic, and microsurgery; especially for what concerns electrical and optical-based sensors for instrumented tools and sensorized tools for contact forces detection. The application of existing technologies is mainly focused on digital simulation purposes, and the integration into Computer Assisted Surgery (CAS) is far from being widely actuated. Virtual reality, increasingly adopted in various fields of surgery (e.g., sino-nasal, traumatology, implantology) showed interesting results and has the potential to revolutionize teaching and learning. A major concern regarding the actual state of the art is the absence of randomized control trials and the prevalence of case reports, retrospective cohorts, and experimental studies. Nonetheless, as the research is fast growing, we can expect to see many developments be incorporated into maxillofacial surgery practice, after adequate evaluation by the scientific community.

Uneven Terrain Recognition Using Neuromorphic Haptic Feedback

Recent years have witnessed relevant advancements in the quality of life of persons with lower limb amputations thanks to the technological developments in prosthetics. However, prostheses that provide information about the foot-ground interaction, and in particular about terrain irregularities, are still missing on the market. The lack of tactile feedback from the foot sole might lead subjects to step on uneven terrains, causing an increase in the risk of falling. To address this issue, a biomimetic vibrotactile feedback system that conveys information about gait and terrain features sensed by a dedicated insole has been assessed with intact subjects. After having shortly experienced both even and uneven terrains, the recruited subjects discriminated them with an accuracy of 87.5%, solely relying on the replay of the vibrotactile feedback. With the objective of exploring the human decoding mechanism of the feedback startegy, a KNN classifier was trained to recognize the uneven terrains. The outcome suggested that the subjects achieved such performance with a temporal dynamics of 45 ms. This work is a leap forward to assist lower-limb amputees to appreciate the floor conditions while walking, adapt their gait and promote a more confident use of their artificial limb.

EEG-based methods for recovery prognosis of patients with disorders of consciousness: A systematic review

OBJECTIVE

Disorders of consciousness (DoC) are acquired conditions of severely altered consciousness. Electroencephalography (EEG)-derived biomarkers have been studied as clinical predictors of consciousness recovery. Therefore, this study aimed to systematically review the methods, features, and models used to derive prognostic EEG markers in patients with DoC in a rehabilitation setting.

METHODS

We conducted a systematic literature search of EEG-based strategies for consciousness recovery prognosis in five electronic databases.

RESULTS

The search resulted in 2964 papers. After screening, 15 studies were included in the review. Our analyses revealed that simpler experimental settings and similar filtering cut-off frequencies are preferred. The results of studies were categorised by extracting qualitative and quantitative features. The quantitative features were further classified into evoked/event-related potentials, spectral measures, entropy measures, and graph-theory measures. Despite the variety of methods, features from all categories, including qualitative ones, exhibited significant correlations with DoC prognosis. Moreover, no agreement was found on the optimal set of EEG-based features for the multivariate prognosis of patients with DoC, which limits the computational methods applied for outcome prediction and correlation analysis to classical ones. Nevertheless, alpha power, reactivity, and higher complexity metrics were often found to be predictive of consciousness recovery.

CONCLUSIONS

This study's findings confirm the essential role of qualitative EEG and suggest an important role for quantitative EEG. Their joint use could compensate for their reciprocal limitations.

SIGNIFICANCE

This study emphasises the need for further efforts toward guidelines on standardised EEG analysis pipeline, given the already proven role of EEG markers in the recovery prognosis of patients with DoC.

Seedless Hydrothermal Growth of ZnO Nanorods as a Promising Route for Flexible Tactile Sensors

Hydrothermal growth of ZnO nanorods has been widely used for the development of tactile sensors, with the aid of ZnO seed layers, favoring the growth of dense and vertically aligned nanorods. However, seed layers represent an additional fabrication step in the sensor design. In this study, a seedless hydrothermal growth of ZnO nanorods was carried out on Au-coated Si and polyimide substrates. The effects of both the Au morphology and the growth temperature on the characteristics of the nanorods were investigated, finding that smaller Au grains produced tilted rods, while larger grains provided vertical rods. Highly dense and high-aspect-ratio nanorods with hexagonal prismatic shape were obtained at 75 °C and 85 °C, while pyramid-like rods were grown when the temperature was set to 95 °C. Finite-element simulations demonstrated that prismatic rods produce higher voltage responses than the pyramid-shaped ones. A tactile sensor, with an active area of 1 cm², was fabricated on flexible polyimide substrate and embedding the nanorods forest in a polydimethylsiloxane matrix as a separation layer between the bottom and the top Au electrodes. The prototype showed clear responses upon applied loads of 2-4 N and vibrations over frequencies in the range of 20-800 Hz.

Perception of Time-Discrete Haptic Feedback on the Waist is Invariant With Gait Events

The effectiveness of haptic feedback devices highly depends on the perception of tactile stimuli, which differs across body parts and can be affected by movement. In this study, a novel wearable sensory feedback apparatus made of a pair of pressure-sensitive insoles and a belt equipped with vibrotactile units is presented; the device provides time-discrete vibrations around the waist, synchronized with biomechanically-relevant gait events during walking. Experiments with fifteen healthy volunteers were carried out to investigate users' tactile perception on the waist. Stimuli of different intensities were provided at twelve locations, each time synchronously with one pre-defined gait event (i.e. heel strike, flat foot or toe off), following a pseudo-random stimulation sequence. Reaction time, detection rate and localization accuracy were analyzed as functions of the stimulation level and site and the effect of gait events on perception was investigated. Results revealed that above-threshold stimuli (i.e. vibrations characterized by acceleration amplitudes of 1.92g and 2.13g and frequencies of 100 Hz and 150 Hz, respectively) can be effectively perceived in all the sites and successfully localized when the intertactor spacing is set to 10 cm. Moreover, it was found that perception of time-discrete vibrations was not affected by phase-related gating mechanisms, suggesting that the waist could be considered as a preferred body region for delivering haptic feedback during walking.

An Improved Strategy for Detection and Localization of Nodules in Liver Tissues by a 16 MHz Needle Ultrasonic Probe Mounted on a Robotic Platform

This study presents an improved strategy for the detection and localization of small size nodules (down to few mm) of agar in excised pork liver tissues via pulse-echo ultrasound measurements performed with a 16 MHz needle probe. This work contributes to the development of a new generation of medical instruments to support robotic surgery decision processes that need information about cancerous tissues in a short time (minutes). The developed ultrasonic probe is part of a scanning platform designed for the automation of surgery-associated histological analyses. It was coupled with a force sensor to control the indentation of tissue samples placed on a steel plate. For the detection of nodules, we took advantage of the property of nodules of altering not only the acoustical properties of tissues producing ultrasound attenuation, but also of developing patterns at their boundary that can modify the shape and the amplitude of the received echo signals from the steel plate supporting the tissues. Besides the Correlation Index Amplitude (CIA), which is linked to the overall amplitude changes of the ultrasonic signals, we introduced the Correlation Index Shape (CIS) linked to their shape changes. Furthermore, we applied AND-OR logical operators to these correlation indices. The results were found particularly helpful in the localization of the irregular masses of agar we inserted into some excised liver tissues, and in the individuation of the regions of major interest over which perform the vertical dissections of tissues in an automated analysis finalized to histopathology. We correctly identified up to 89% of inclusions, with an improvement of about 14% with respect to the result obtained (78%) from the analysis performed with the CIA parameter only.

Fluidic Haptic Interface for Mechano-Tactile Feedback

Notable advancements have been achieved in providing amputees with sensation through invasive and non-invasive haptic feedback systems such as mechano-, vibro-, electro-tactile and hybrid systems. Purely mechanical-driven feedback approaches, however, have been little explored. In this paper, we now created a haptic feedback system that does not require any external power source (such as batteries) or other electronic components (see Fig. 1 ). The system is low-cost, lightweight, adaptable and robust against external impact (such as water). Hence, it will be sustainable in many aspects. We have made use of latest multi-material 3D printing technology (Stratasys Objet500 Connex3) being able to fabricate a soft sensor and a mechano-tactile feedback actuator made of a rubber (TangoBlack Plus) and plastic (VeroClear) material. When forces are applied to the fingertip sensor, fluidic pressure inside the system acts on the membrane of the feedback actuator resulting in mechano-tactile sensation. Our [Formula: see text] feedback actuator is able to transmit a force range between 0.2 N (the median touch threshold) and 2.1 N (the maximum force transmitted by the feedback actuator at a 3 mm indentation) corresponding to force range exerted to the fingertip sensor of 1.2-18.49 N.

A Machine-Learning-Based Approach to Solve Both Contact Location and Force in Soft Material Tactile Sensors

This study addresses a design and calibration methodology based on numerical finite element method (FEM) modeling for the development of a soft tactile sensor able to simultaneously solve the magnitude and the application location of a normal load exerted onto its surface. The sensor entails the integration of a Bragg grating fiber optic sensor in a Dragon Skin 10 polymer brick (110 mm length, 24 mm width). The soft polymer mediates the transmission of the applied load to the buried fiber Bragg gratings (FBGs), and we also investigated the effect of sensor thickness on receptive field and sensitivity, both with the developed model and experimentally. Force-controlled indentations of the sensor (up to 2.5 N) were carried out through a cylindrical probe applied along the direction of the optical fiber (over an ∼90 mm span in length). A finite element model of the sensor was built and experimentally validated for 1 and 6 mm thicknesses of the soft polymeric encapsulation material, considering that the latter thickness resulted from numerical simulations as leading to optimal cross talk and sensitivity, given the chosen soft material. The FEM model was also used to train a neural network so as to obtain the inverse sensor function. Using four FBG transducers embedded in the 6-mm-thick soft polymer, the proposed machine learning approach managed to accurately detect both load magnitude (R = 0.97) and location (R = 0.99) over the whole experimental range. The proposed system could be used for developing tactile sensors that can be effectively used for a broad range of applications.

Tactile Decoding of Edge Orientation With Artificial Cuneate Neurons in Dynamic Conditions

Generalization ability in tactile sensing for robotic manipulation is a prerequisite to effectively perform tasks in ever-changing environments. In particular, performing dynamic tactile perception is currently beyond the ability of robotic devices. A biomimetic approach to achieve this dexterity is to develop machines combining compliant robotic manipulators with neuroinspired architectures displaying computational adaptation. Here we demonstrate the feasibility of this approach for dynamic touch tasks experimented by integrating our sensing apparatus in a 6 degrees of freedom robotic arm via a soft wrist. We embodied in the system a model of spike-based neuromorphic encoding of tactile stimuli, emulating the discrimination properties of cuneate nucleus neurons based on pathways with differential delay lines. These strategies allowed the system to correctly perform a dynamic touch protocol of edge orientation recognition (ridges from 0 to 40°, with a step of 5°). Crucially, the task was robust to contact noise and was performed with high performance irrespectively of sensing conditions (sensing forces and velocities). These results are a step forward toward the development of robotic arms able to physically interact in real-world environments with tactile sensing.

Ubiquitous Neocortical Decoding of Tactile Input Patterns

Whereas functional localization historically has been a key concept in neuroscience, direct neuronal recordings show that input of a particular modality can be recorded well outside its primary receiving areas in the neocortex. Here, we wanted to explore if such spatially unbounded inputs potentially contain any information about the quality of the input received. We utilized a recently introduced approach to study the neuronal decoding capacity at a high resolution by delivering a set of electrical, highly reproducible spatiotemporal tactile afferent activation patterns to the skin of the contralateral second digit of the forepaw of the anesthetized rat. Surprisingly, we found that neurons in all areas recorded from, across all cortical depths tested, could decode the tactile input patterns, including neurons of the primary visual cortex. Within both somatosensory and visual cortical areas, the combined decoding accuracy of a population of neurons was higher than for the best performing single neuron within the respective area. Such cooperative decoding indicates that not only did individual neurons decode the input, they also did so by generating responses with different temporal profiles compared to other neurons, which suggests that each neuron could have unique contributions to the tactile information processing. These findings suggest that tactile processing in principle could be globally distributed in the neocortex, possibly for comparison with internal expectations and disambiguation processes relying on other modalities.

An innovative robotic platform for magnetically-driven painless colonoscopy

Colorectal cancer (CRC) represents a significant medical threat with a dramatic impact on the healthcare system with around 1.3 million patients worldwide, causing more than 700 thousand deaths annually. A key-aspect to successful and cost-effective disease management is represented by the early detection of CRC at asymptomatic stage. For this reason, population screening is highly recommended for patients older than 50 years or at high risk for familiarity. Currently, the standard endoscopic techniques do not meet this need. In recent years, innovative endoscopic robotic techniques and active locomotion devices have been developed as alternatives to conventional colonoscopy. The magnetically-driven robotic platform, presented by the authors, is conceived to perform less invasive and more comfortable colonoscopy with the aim to promote screening campaigns for detection of early colorectal neoplasm.

Long-latency components of somatosensory evoked potentials during passive tactile perception of gratings

Perception of tactile stimuli elicits Somatosensory Evoked Potentials (SEPs) that can be recorded via non-invasive electroencephalography (EEG). However, it is not yet clear how SEPs localization, shape and latency are modulated by different stimuli during mechanical tactile stimulation of fingertips. The aim of this work is thus to characterize SEPs generated by the tactile perception of gratings during dynamic passive stimulation of the dominant fingertip by means of a mechatronic platform. Results show that a random sequence of stimuli elicited SEPs with two long-latency components: (i) a negative deflection around 140 ms located in the frontal-central-parietal side in the contralateral hemisphere; (ii) a positive deflection around 250 ms located in the frontal-central midline. Time-frequency analysis revealed significant continuous bilateral desynchronization in the alpha band throughout the passive stimulation. These results are a fundamental step towards building a model of brain responses during perception of tactile stimuli for future benchmarking studies.

Neuromorphic Artificial Touch for Categorization of Naturalistic Textures

We implemented neuromorphic artificial touch and emulated the firing behavior of mechanoreceptors by injecting the raw outputs of a biomimetic tactile sensor into an Izhikevich neuronal model. Naturalistic textures were evaluated with a passive touch protocol. The resulting neuromorphic spike trains were able to classify ten naturalistic textures ranging from textiles to glass to BioSkin, with accuracy as high as 97%. Remarkably, rather than on firing rate features calculated over the stimulation window, the highest achieved decoding performance was based on the precise spike timing of the neuromorphic output as captured by Victor Purpura distance. We also systematically varied the sliding velocity and the contact force to investigate the role of sensing conditions in categorizing the stimuli via the artificial sensory system. We found that the decoding performance based on the timing of neuromorphic spike events was robust for a broad range of sensing conditions. Being able to categorize naturalistic textures in different sensing conditions, these neurorobotic results pave the way to the use of neuromorphic tactile sensors in future real-life neuroprosthetic applications.

Frontiers of robotic endoscopic capsules: a review

Digestive diseases are a major burden for society and healthcare systems, and with an aging population, the importance of their effective management will become critical. Healthcare systems worldwide already struggle to insure quality and affordability of healthcare delivery and this will be a significant challenge in the midterm future. Wireless capsule endoscopy (WCE), introduced in 2000 by Given Imaging Ltd., is an example of disruptive technology and represents an attractive alternative to traditional diagnostic techniques. WCE overcomes conventional endoscopy enabling inspection of the digestive system without discomfort or the need for sedation. Thus, it has the advantage of encouraging patients to undergo gastrointestinal (GI) tract examinations and of facilitating mass screening programmes. With the integration of further capabilities based on microrobotics, e.g. active locomotion and embedded therapeutic modules, WCE could become the key-technology for GI diagnosis and treatment. This review presents a research update on WCE and describes the state-of-the-art of current endoscopic devices with a focus on research-oriented robotic capsule endoscopes enabled by microsystem technologies. The article also presents a visionary perspective on WCE potential for screening, diagnostic and therapeutic endoscopic procedures.

Intraneural stimulation elicits discrimination of textural features by artificial fingertip in intact and amputee humans

Restoration of touch after hand amputation is a desirable feature of ideal prostheses. Here, we show that texture discrimination can be artificially provided in human subjects by implementing a neuromorphic real-time mechano-neuro-transduction (MNT), which emulates to some extent the firing dynamics of SA1 cutaneous afferents. The MNT process was used to modulate the temporal pattern of electrical spikes delivered to the human median nerve via percutaneous microstimulation in four intact subjects and via implanted intrafascicular stimulation in one transradial amputee. Both approaches allowed the subjects to reliably discriminate spatial coarseness of surfaces as confirmed also by a hybrid neural model of the median nerve. Moreover, MNT-evoked EEG activity showed physiologically plausible responses that were superimposable in time and topography to the ones elicited by a natural mechanical tactile stimulation. These findings can open up novel opportunities for sensory restoration in the next generation of neuro-prosthetic hands.

DOI:http://dx.doi.org/10.7554/eLife.09148.001

Our hands provide us with a wide variety of information about our surroundings, enabling us to detect pain, temperature and pressure. Our sense of touch also allows us to interact with objects by feeling their texture and solidity. However, completely reproducing a sense of touch in artificial or prosthetic hands has proven challenging. While commercial prostheses can mimic the range of movements of natural limbs, even the latest experimental prostheses have only a limited ability to ‘feel’ the objects being manipulated. Oddo, Raspopovic et al. have now brought this ability a step closer by exploiting an artificial fingertip and appropriate neural interfaces through which different textures can be identified.

The initial experiments were performed in four healthy volunteers with intact limbs. Oddo, Raspopovic et al. connected the artificial fingertip to the volunteers via an electrode inserted into a nerve in the arm. When moved over a rough surface, sensors in the fingertip produced patterns of electrical pulses that stimulated the nerve, causing the volunteers to feel like they were touching the surface. The volunteers were even able to tell the difference between the different surface textures the artificial fingertip moved across.

The temporary electrodes used in this group of volunteers are unsuitable for use with prosthetic limbs because they can easily be knocked out of position. Therefore, in a further experiment involving a volunteer who had undergone an arm amputation a number of years previously, Oddo, Raspopovic et al. tested an implanted electrode array that could, in principle, remain in place long-term. This volunteer could also identify the different textures the artificial fingertip touched, with a slightly higher degree of accuracy than the previous group of intact volunteers. Further studies are now required to explore the potential of this approach in larger groups of volunteers.

DOI:http://dx.doi.org/10.7554/eLife.09148.002

Insights and Perspectives on Sensory-Motor Integration and Rehabilitation

The present review focuses on the flow and interaction of somatosensory-motor signals in the central and peripheral nervous system. Specifically, where incoming sensory signals from the periphery are processed and interpreted to initiate behaviors, and how ongoing behaviors produce sensory consequences encoded and used to fine-tune subsequent actions. We describe the structure–function relations of this loop, how these relations can be modeled and aspects of somatosensory-motor rehabilitation. The work reviewed here shows that it is imperative to understand the fundamental mechanisms of the somatosensory-motor system to restore accurate motor abilities and appropriate somatosensory feedback. Knowledge of the salient neural mechanisms of sensory-motor integration has begun to generate innovative approaches to improve rehabilitation training following neurological impairments such as stroke. The present work supports the integration of basic science principles of sensory-motor integration into rehabilitation procedures to create new solutions for sensory-motor disorders.

PARLOMA – A Novel Human-Robot Interaction System for Deaf-Blind Remote Communication

Deaf-blindness forces people to live in isolation. At present, there is no existing technological solution enabling two (or many) deaf-blind people to communicate remotely among themselves in tactile Sign Language (t-SL). When resorting to t-SL, deaf-blind people can communicate only with people physically present in the same place, because they are required to reciprocally explore their hands to exchange messages. We present a preliminary version of PARLOMA, a novel system to enable remote communication between deaf-blind persons. It is composed of a low-cost depth sensor as the only input device, paired with a robotic hand as the output device. Essentially, any user can perform hand-shapes in front of the depth sensor. The system is able to recognize a set of hand-shapes that are sent over the web and reproduced by an anthropomorphic robotic hand. PARLOMA can work as a “telephone” for deaf-blind people. Hence, it will dramatically improve the quality of life of deaf-blind persons. PARLOMA has been presented and supported by the main Italian deaf-blind association, Lega del Filo d'Oro. End users are involved in the design phase.

Microfabricated tactile sensors for biomedical applications: a review

During the last decades, tactile sensors based on different sensing principles have been developed due to the growing interest in robotics and, mainly, in medical applications. Several technological solutions have been employed to design tactile sensors; in particular, solutions based on microfabrication present several attractive features. Microfabrication technologies allow for developing miniaturized sensors with good performance in terms of metrological properties (e.g., accuracy, sensitivity, low power consumption, and frequency response). Small size and good metrological properties heighten the potential role of tactile sensors in medicine, making them especially attractive to be integrated in smart interfaces and microsurgical tools. This paper provides an overview of microfabricated tactile sensors, focusing on the mean principles of sensing, i.e., piezoresistive, piezoelectric and capacitive sensors. These sensors are employed for measuring contact properties, in particular force and pressure, in three main medical fields, i.e., prosthetics and artificial skin, minimal access surgery and smart interfaces for biomechanical analysis. The working principles and the metrological properties of the most promising tactile, microfabricated sensors are analyzed, together with their application in medicine. Finally, the new emerging technologies in these fields are briefly described.

Restoring natural sensory feedback in real-time bidirectional hand prostheses

Hand loss is a highly disabling event that markedly affects the quality of life. To achieve a close to natural replacement for the lost hand, the user should be provided with the rich sensations that we naturally perceive when grasping or manipulating an object. Ideal bidirectional hand prostheses should involve both a reliable decoding of the user's intentions and the delivery of nearly "natural" sensory feedback through remnant afferent pathways, simultaneously and in real time. However, current hand prostheses fail to achieve these requirements, particularly because they lack any sensory feedback. We show that by stimulating the median and ulnar nerve fascicles using transversal multichannel intrafascicular electrodes, according to the information provided by the artificial sensors from a hand prosthesis, physiologically appropriate (near-natural) sensory information can be provided to an amputee during the real-time decoding of different grasping tasks to control a dexterous hand prosthesis. This feedback enabled the participant to effectively modulate the grasping force of the prosthesis with no visual or auditory feedback. Three different force levels were distinguished and consistently used by the subject. The results also demonstrate that a high complexity of perception can be obtained, allowing the subject to identify the stiffness and shape of three different objects by exploiting different characteristics of the elicited sensations. This approach could improve the efficacy and "life-like" quality of hand prostheses, resulting in a keystone strategy for the near-natural replacement of missing hands.

Physical factors influencing pleasant touch during passive fingertip stimulation

OBJECTIVE

Tactile explorations with the fingertips provide information regarding the physical properties of surfaces and their relative pleasantness. Previously, we performed an investigation in the active touch domain and linked several surface properties (i.e. frictional force fluctuations and net friction) with their pleasantness levels. The aim of the present study was to investigate physical factors being important for pleasantness perception during passive fingertip stimulation. Specifically we were interested to see whether factors, such as surfaces' topographies or their frictional characteristics could influence pleasantness. Furthermore, we ascertained how the stimulus pleasantness level was impacted by (i) the normal force of stimulus application (FN) and (ii) the stimulus temperature (TS).

METHODS AND RESULTS

The right index fingertips of 22 blindfolded participants were stimulated using 27 different stimuli, which varied in average roughness (Ra) and TS. A 4-axis robot moved the stimuli horizontally under participants' fingertips with three levels of FN. The robot was equipped with force sensors, which recorded the FN and friction force (FT) during stimulation. Participants rated each stimulus according to a three-level pleasantness scale, as very pleasant (scored 0), pleasant (scored 1), or unpleasant (scored 2). These ordinal pleasantness ratings were logarithmically transformed into linear and unidimensional pleasantness measures with the Rasch model. Statistical analyses were conducted to investigate a possible link between the stimulus properties (i.e. Ra, FN, FT, and TS) and their respective pleasantness levels. Only the mean Ra and FT values were negatively correlated with pleasantness. No significant correlation was detected between FN or TS and pleasantness.

CONCLUSION

Pleasantness perception, resulting from passive fingertip stimulation, seems to be influenced by the surfaces' average roughness levels and average FT occurring during fingertip stimulation.

Piezoelectric energy harvesting solutions

This paper reviews the state of the art in piezoelectric energy harvesting. It presents the basics of piezoelectricity and discusses materials choice. The work places emphasis on material operating modes and device configurations, from resonant to non-resonant devices and also to rotational solutions. The reviewed literature is compared based on power density and bandwidth. Lastly, the question of power conversion is addressed by reviewing various circuit solutions.

Roughness encoding in human and biomimetic artificial touch: spatiotemporal frequency modulation and structural anisotropy of fingerprints

The influence of fingerprints and their curvature in tactile sensing performance is investigated by comparative analysis of different design parameters in a biomimetic artificial fingertip, having straight or curved fingerprints. The strength in the encoding of the principal spatial period of ridged tactile stimuli (gratings) is evaluated by indenting and sliding the surfaces at controlled normal contact force and tangential sliding velocity, as a function of fingertip rotation along the indentation axis. Curved fingerprints guaranteed higher directional isotropy than straight fingerprints in the encoding of the principal frequency resulting from the ratio between the sliding velocity and the spatial periodicity of the grating. In parallel, human microneurography experiments were performed and a selection of results is included in this work in order to support the significance of the biorobotic study with the artificial tactile system.

Artificial Roughness Encoding with a Bio-inspired MEMS- based Tactile Sensor Array

A compliant 2×2 tactile sensor array was developed and investigated for roughness encoding. State of the art cross shape 3D MEMS sensors were integrated with polymeric packaging providing in total 16 sensitive elements to external mechanical stimuli in an area of about 20 mm², similarly to the SA1 innervation density in humans. Experimental analysis of the bio-inspired tactile sensor array was performed by using ridged surfaces, with spatial periods from 2.6 mm to 4.1 mm, which were indented with regulated 1N normal force and stroked at constant sliding velocity from 15 mm/s to 48 mm/s. A repeatable and expected frequency shift of the sensor outputs depending on the applied stimulus and on its scanning velocity was observed between 3.66 Hz and 18.46 Hz with an overall maximum error of 1.7%. The tactile sensor could also perform contact imaging during static stimulus indentation. The experiments demonstrated the suitability of this approach for the design of a roughness encoding tactile sensor for an artificial fingerpad.

A simple highly efficient non invasive EMG-based HMI

Muscle activity recorded non-invasively is sufficient to control a mobile robot if it is used in combination with an algorithm for its asynchronous analysis. In this paper, we show that several subjects successfully can control the movements of a robot in a structured environment made up of six rooms by contracting two different muscles using a simple algorithm. After a small training period, subjects were able to control the robot with performances comparable to those achieved manually controlling the robot.

Effect of the acute sublingual administration of ketanserin in hypertensive patients

The purpose of this study has been to compare the acute antihypertensive effect of a dose of 20 mg of ketanserin in 18 patients after sublingual administration and in 19 after oral administration. In three patients ketanserin and ketanserin-ol plasma levels were measured after both sublingual and oral administration. The results showed a more rapid, considerable antihypertensive effect after sublingual administration. In addition, the high plasma levels of ketanserin-ol, the metabolite produced by hepatic reduction of ketanserin, reached after sublingual administration, rather than transmucosal absorption, indicate that the clinical effect observed is due to more rapid dissolution of the tablet formulation and liberation of the active drug.