86 research outputs found

    Neuromorphic hardware for somatosensory neuroprostheses

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    In individuals with sensory-motor impairments, missing limb functions can be restored using neuroprosthetic devices that directly interface with the nervous system. However, restoring the natural tactile experience through electrical neural stimulation requires complex encoding strategies. Indeed, they are presently limited in effectively conveying or restoring tactile sensations by bandwidth constraints. Neuromorphic technology, which mimics the natural behavior of neurons and synapses, holds promise for replicating the encoding of natural touch, potentially informing neurostimulation design. In this perspective, we propose that incorporating neuromorphic technologies into neuroprostheses could be an effective approach for developing more natural human-machine interfaces, potentially leading to advancements in device performance, acceptability, and embeddability. We also highlight ongoing challenges and the required actions to facilitate the future integration of these advanced technologies

    Sensors for Robotic Hands: A Survey of State of the Art

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    Recent decades have seen significant progress in the field of artificial hands. Most of the surveys, which try to capture the latest developments in this field, focused on actuation and control systems of these devices. In this paper, our goal is to provide a comprehensive survey of the sensors for artificial hands. In order to present the evolution of the field, we cover five year periods starting at the turn of the millennium. At each period, we present the robot hands with a focus on their sensor systems dividing them into categories, such as prosthetics, research devices, and industrial end-effectors.We also cover the sensors developed for robot hand usage in each era. Finally, the period between 2010 and 2015 introduces the reader to the state of the art and also hints to the future directions in the sensor development for artificial hands

    I Feel You : Mahdollisuudet kosketusta aistivien, eläviä olentoja imitoivien kudottujen tekstiilien luomiseen

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    I Feel You is a speculative textile design project looking into the possibilities of creating multi-sensory electronic textile surfaces that imitate living beings. Specifically, this thesis aims to discover what kinds of textile surfaces people can identify through the sense of touch, what kind of touch is perceived as soothing, and how to bring reactivity into woven textiles. Finally, a series of speculative electronic textile pieces that react to touch was created. Textiles are multi-sensorial and interactive by nature and sensorial textiles can support people’s psychological needs, such as comfort and security. Sensors and active outputs integrated into the textiles can significantly impact what kind of tactile sensations and emotional associations can be connected to textiles. Traditional materials and techniques interweave with new technologies creating possibilities to design new types of interactions with textiles. The motivation of this thesis is to understand the possibilities that open up with these new functions without forgetting the traditional properties of textiles. In this thesis process, practical exploration and drawing from the literature survey go in hand. Theoretical and practical approaches take place simultaneously, forming an iterative process. In the framework of practice-based research, the somaesthetics design approach is applied as a research method. The embodied knowledge of a textile designer regarding the properties, materials, and structures has a crucial role in designing and evaluating passive and active haptic textile surfaces. Textile samples are created based on previous knowledge, learning in action, and the literature survey. They are evaluated in the process of making, compared, and developed with drawings from the literature, and used as a basis for creating design concepts, which in turn were used as a basis for the final textiles. The artistic work is a series of textile pieces that speculate on how textiles could create an illusion of being close to another living being. Finally, the series of interactive electronic textile pieces were exhibited in a gallery setting to gather feedback from visitors. In the design process of multi-sensory electronic textile surfaces, all of the elements entangle and affected each other: materials, woven structures, colors, and patterns, as well as sensing and actuating elements. When designing active haptic textile surfaces, traditional properties of textiles, such as materials and woven structures cannot be separated from the design process.I Feel You on spekulatiivinen tekstiilisuunnitteluprojekti, joka tutkii mahdollisuuksia luoda eläviä olentoja jäljitteleviä moniaistisia elektronisia tekstiilipintoja. Opinnäytetyön tavoitteena on selvittää, millaisia tekstiilipintoja ihmiset voivat tunnistaa tuntoaistin avulla, millainen kosketus koetaan rauhoittavaksi ja miten elävää olentoa jäljittelevää reaktiivisuutta voidaan tuoda kudottuihin tekstiileihin. Lopulta luotiin sarja spekulatiivisia elektronisia tekstiileitä, jotka reagoivat kosketukseen. Tekstiilit ovat moniaistisia ja vuorovaikutteisia jo luonnostaan. Pehmeät, moniaistiset tekstiilit voivat herättää esimerkiksi tuttuuden ja turvallisuuden tunteita. Tekstiilien erilaiset ominaisuudet voivatkin vastata ihmisten psyykkisiin tarpeisiin, kuten mukavuuteen ja turvallisuuteen. Tekstiileihin upotetut elektroniset toiminnot voivat merkittävästi lisätä niiden aistittvia ominaisuuksia, ja siten merkittävästi vaikuttaa siihen, millaisia tuntoaistimuksia ja emotionaalisia assosiaatioita tekstiileihin yhdistetään. Perinteiset materiaalit ja tekniikat kietoutuvat yhteen uusien teknologioiden kanssa luoden mahdollisuuksia suunnitella uudenlaisia vuorovaikutuksia tekstiilien kanssa. Tämän opinnäytetyö pyrkii ymmärtämään näiden uusien toimintojen myötä avautuvia mahdollisuuksia, unohtamatta kuitenkaan tekstiilien perinteisiä ominaisuuksia. Tässä opinnäytetyössä käytännön työ ja kirjallisuuskatsaus kulkevat käsi kädessä. Teoreettinen ja käytännöllinen työskentely tapahtuvat samanaikaisesti muodostaen iteratiivisen prosessin. Tutkimusmenetelmänä sovelletaan somasteettisen suunnittelun lähestymistapaa. Tekstiilisuunnittelijan kehollinen tieto tekstiilipintojen materiaaleista ja rakenteista on ratkaisevassa roolissa suunniteltaessa ja arvioitaessa passiivisia ja aktiivisia haptisia tekstiilipintoja. Kudotut tekstiilinäytteet syntyvät aikaisemman tiedon, kirjallisuuskatsauksen, sekä kokeilevan prosessin pohjalta. Syntyneitä näytteitä arvioidaan kudonnan prosessissa sekä verrataan kirjallisuuskatsaukseen. Ne toimivat pohjana luotaessa konsepteja, joita taas käytetään lopullisten tekstiilien perustana. Työn taiteellinen osuus on sarja tekstiilejä, jotka ehdottavat, kuinka tekstiilit voisivat luoda illuusion toisen elävän olennon läheisyydestä. Lopulta sarja interaktiivisia elektronisia tekstiilejä esitettiin galleritilassa, ja niiden aiheuttamista tuntemuksista kerättiin palautetta näyttelyvierailta. Moniaististen elektronisten tekstiilipintojen suunnitteluprosessissa kaikki osa-alueet kietoutuivat ja vaikuttivat toisiinsa: materiaalit, kudotut rakenteet, värit, kuosit sekä sensorit ja elektroniset aistipalautteet. Suunniteltaessa aktiivisesti reagoivia tekstiilipintoja, myöskään tekstiilien perinteisiä ominaisuuksia, kuten materiaaleja, kuoseja ja kudottuja rakenteita, ei voida erottaa suunnitteluprosessista

    Distributed Sensing and Stimulation Systems Towards Sense of Touch Restoration in Prosthetics

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    Modern prostheses aim at restoring the functional and aesthetic characteristics of the lost limb. To foster prosthesis embodiment and functionality, it is necessary to restitute both volitional control and sensory feedback. Contemporary feedback interfaces presented in research use few sensors and stimulation units to feedback at most two discrete feedback variables (e.g. grasping force and aperture), whereas the human sense of touch relies on a distributed network of mechanoreceptors providing high-fidelity spatial information. To provide this type of feedback in prosthetics, it is necessary to sense tactile information from artificial skin placed on the prosthesis and transmit tactile feedback above the amputation in order to map the interaction between the prosthesis and the environment. This thesis proposes the integration of distributed sensing systems (e-skin) to acquire tactile sensation, and non-invasive multichannel electrotactile feedback and virtual reality to deliver high-bandwidth information to the user. Its core focus addresses the development and testing of close-loop sensory feedback human-machine interface, based on the latest distributed sensing and stimulation techniques for restoring the sense of touch in prosthetics. To this end, the thesis is comprised of two introductory chapters that describe the state of art in the field, the objectives and the used methodology and contributions; as well as three studies distributed over stimulation system level and sensing system level. The first study presents the development of close-loop compensatory tracking system to evaluate the usability and effectiveness of electrotactile sensory feedback in enabling real-time close-loop control in prosthetics. It examines and compares the subject\u2019s adaptive performance and tolerance to random latencies while performing the dynamic control task (i.e. position control) and simultaneously receiving either visual feedback or electrotactile feedback for communicating the momentary tracking error. Moreover, it reported the minimum time delay needed for an abrupt impairment of users\u2019 performance. The experimental results have shown that electrotactile feedback performance is less prone to changes with longer delays. However, visual feedback drops faster than electrotactile with increased time delays. This is a good indication for the effectiveness of electrotactile feedback in enabling close- loop control in prosthetics, since some delays are inevitable. The second study describes the development of a novel non-invasive compact multichannel interface for electrotactile feedback, containing 24 pads electrode matrix, with fully programmable stimulation unit, that investigates the ability of able-bodied human subjects to localize the electrotactile stimulus delivered through the electrode matrix. Furthermore, it designed a novel dual parameter -modulation (interleaved frequency and intensity) and compared it to conventional stimulation (same frequency for all pads). In addition and for the first time, it compared the electrotactile stimulation to mechanical stimulation. More, it exposes the integration of virtual prosthesis with the developed system in order to achieve better user experience and object manipulation through mapping the acquired real-time collected tactile data and feedback it simultaneously to the user. The experimental results demonstrated that the proposed interleaved coding substantially improved the spatial localization compared to same-frequency stimulation. Furthermore, it showed that same-frequency stimulation was equivalent to mechanical stimulation, whereas the performance with dual-parameter modulation was significantly better. The third study presents the realization of a novel, flexible, screen- printed e-skin based on P(VDF-TrFE) piezoelectric polymers, that would cover the fingertips and the palm of the prosthetic hand (particularly the Michelangelo hand by Ottobock) and an assistive sensorized glove for stroke patients. Moreover, it developed a new validation methodology to examine the sensors behavior while being solicited. The characterization results showed compatibility between the expected (modeled) behavior of the electrical response of each sensor to measured mechanical (normal) force at the skin surface, which in turn proved the combination of both fabrication and assembly processes was successful. This paves the way to define a practical, simplified and reproducible characterization protocol for e-skin patches In conclusion, by adopting innovative methodologies in sensing and stimulation systems, this thesis advances the overall development of close-loop sensory feedback human-machine interface used for restoration of sense of touch in prosthetics. Moreover, this research could lead to high-bandwidth high-fidelity transmission of tactile information for modern dexterous prostheses that could ameliorate the end user experience and facilitate it acceptance in the daily life

    Electronic systems for the restoration of the sense of touch in upper limb prosthetics

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    In the last few years, research on active prosthetics for upper limbs focused on improving the human functionalities and the control. New methods have been proposed for measuring the user muscle activity and translating it into the prosthesis control commands. Developing the feed-forward interface so that the prosthesis better follows the intention of the user is an important step towards improving the quality of life of people with limb amputation. However, prosthesis users can neither feel if something or someone is touching them over the prosthesis and nor perceive the temperature or roughness of objects. Prosthesis users are helped by looking at an object, but they cannot detect anything otherwise. Their sight gives them most information. Therefore, to foster the prosthesis embodiment and utility, it is necessary to have a prosthetic system that not only responds to the control signals provided by the user, but also transmits back to the user the information about the current state of the prosthesis. This thesis presents an electronic skin system to close the loop in prostheses towards the restoration of the sense of touch in prosthesis users. The proposed electronic skin system inlcudes an advanced distributed sensing (electronic skin), a system for (i) signal conditioning, (ii) data acquisition, and (iii) data processing, and a stimulation system. The idea is to integrate all these components into a myoelectric prosthesis. Embedding the electronic system and the sensing materials is a critical issue on the way of development of new prostheses. In particular, processing the data, originated from the electronic skin, into low- or high-level information is the key issue to be addressed by the embedded electronic system. Recently, it has been proved that the Machine Learning is a promising approach in processing tactile sensors information. Many studies have been shown the Machine Learning eectiveness in the classication of input touch modalities.More specically, this thesis is focused on the stimulation system, allowing the communication of a mechanical interaction from the electronic skin to prosthesis users, and the dedicated implementation of algorithms for processing tactile data originating from the electronic skin. On system level, the thesis provides design of the experimental setup, experimental protocol, and of algorithms to process tactile data. On architectural level, the thesis proposes a design ow for the implementation of digital circuits for both FPGA and integrated circuits, and techniques for the power management of embedded systems for Machine Learning algorithms

    Force sensor in simulated skin and neural model mimic tactile SAI afferent spiking response to ramp and hold stimuli

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    The next generation of prosthetic limbs will restore sensory feedback to the nervous system by mimicking how skin mechanoreceptors, innervated by afferents, produce trains of action potentials in response to compressive stimuli. Prior work has addressed building sensors within skin substitutes for robotics, modeling skin mechanics and neural dynamics of mechanotransduction, and predicting response timing of action potentials for vibration. The effort here is unique because it accounts for skin elasticity by measuring force within simulated skin, utilizes few free model parameters for parsimony, and separates parameter fitting and model validation. Additionally, the ramp-and-hold, sustained stimuli used in this work capture the essential features of the everyday task of contacting and holding an object. This systems integration effort computationally replicates the neural firing behavior for a slowly adapting type I (SAI) afferent in its temporally varying response to both intensity and rate of indentation force by combining a physical force sensor, housed in a skin-like substrate, with a mathematical model of neuronal spiking, the leaky integrate-and-fire. Comparison experiments were then conducted using ramp-and-hold stimuli on both the spiking-sensor model and mouse SAI afferents. The model parameters were iteratively fit against recorded SAI interspike intervals (ISI) before validating the model to assess its performance. Model-predicted spike firing compares favorably with that observed for single SAI afferents. As indentation magnitude increases (1.2, 1.3, to 1.4 mm), mean ISI decreases from 98.81 ± 24.73, 54.52 ± 6.94, to 41.11 ± 6.11 ms. Moreover, as rate of ramp-up increases, ISI during ramp-up decreases from 21.85 ± 5.33, 19.98 ± 3.10, to 15.42 ± 2.41 ms. Considering first spikes, the predicted latencies exhibited a decreasing trend as stimulus rate increased, as is observed in afferent recordings. Finally, the SAI afferent’s characteristic response of producing irregular ISIs is shown to be controllable via manipulating the output filtering from the sensor or adding stochastic noise. This integrated engineering approach extends prior works focused upon neural dynamics and vibration. Future efforts will perfect measures of performance, such as first spike latency and irregular ISIs, and link the generation of characteristic features within trains of action potentials with current pulse waveforms that stimulate single action potentials at the peripheral afferent

    Novel Bidirectional Body - Machine Interface to Control Upper Limb Prosthesis

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    Objective. The journey of a bionic prosthetic user is characterized by the opportunities and limitations involved in adopting a device (the prosthesis) that should enable activities of daily living (ADL). Within this context, experiencing a bionic hand as a functional (and, possibly, embodied) limb constitutes the premise for mitigating the risk of its abandonment through the continuous use of the device. To achieve such a result, different aspects must be considered for making the artificial limb an effective support for carrying out ADLs. Among them, intuitive and robust control is fundamental to improving amputees’ quality of life using upper limb prostheses. Still, as artificial proprioception is essential to perceive the prosthesis movement without constant visual attention, a good control framework may not be enough to restore practical functionality to the limb. To overcome this, bidirectional communication between the user and the prosthesis has been recently introduced and is a requirement of utmost importance in developing prosthetic hands. Indeed, closing the control loop between the user and a prosthesis by providing artificial sensory feedback is a fundamental step towards the complete restoration of the lost sensory-motor functions. Within my PhD work, I proposed the development of a more controllable and sensitive human-like hand prosthesis, i.e., the Hannes prosthetic hand, to improve its usability and effectiveness. Approach. To achieve the objectives of this thesis work, I developed a modular and scalable software and firmware architecture to control the Hannes prosthetic multi-Degree of Freedom (DoF) system and to fit all users’ needs (hand aperture, wrist rotation, and wrist flexion in different combinations). On top of this, I developed several Pattern Recognition (PR) algorithms to translate electromyographic (EMG) activity into complex movements. However, stability and repeatability were still unmet requirements in multi-DoF upper limb systems; hence, I started by investigating different strategies to produce a more robust control. To do this, EMG signals were collected from trans-radial amputees using an array of up to six sensors placed over the skin. Secondly, I developed a vibrotactile system to implement haptic feedback to restore proprioception and create a bidirectional connection between the user and the prosthesis. Similarly, I implemented an object stiffness detection to restore tactile sensation able to connect the user with the external word. This closed-loop control between EMG and vibration feedback is essential to implementing a Bidirectional Body - Machine Interface to impact amputees’ daily life strongly. For each of these three activities: (i) implementation of robust pattern recognition control algorithms, (ii) restoration of proprioception, and (iii) restoration of the feeling of the grasped object's stiffness, I performed a study where data from healthy subjects and amputees was collected, in order to demonstrate the efficacy and usability of my implementations. In each study, I evaluated both the algorithms and the subjects’ ability to use the prosthesis by means of the F1Score parameter (offline) and the Target Achievement Control test-TAC (online). With this test, I analyzed the error rate, path efficiency, and time efficiency in completing different tasks. Main results. Among the several tested methods for Pattern Recognition, the Non-Linear Logistic Regression (NLR) resulted to be the best algorithm in terms of F1Score (99%, robustness), whereas the minimum number of electrodes needed for its functioning was determined to be 4 in the conducted offline analyses. Further, I demonstrated that its low computational burden allowed its implementation and integration on a microcontroller running at a sampling frequency of 300Hz (efficiency). Finally, the online implementation allowed the subject to simultaneously control the Hannes prosthesis DoFs, in a bioinspired and human-like way. In addition, I performed further tests with the same NLR-based control by endowing it with closed-loop proprioceptive feedback. In this scenario, the results achieved during the TAC test obtained an error rate of 15% and a path efficiency of 60% in experiments where no sources of information were available (no visual and no audio feedback). Such results demonstrated an improvement in the controllability of the system with an impact on user experience. Significance. The obtained results confirmed the hypothesis of improving robustness and efficiency of a prosthetic control thanks to of the implemented closed-loop approach. The bidirectional communication between the user and the prosthesis is capable to restore the loss of sensory functionality, with promising implications on direct translation in the clinical practice

    Biomechatronics: Harmonizing Mechatronic Systems with Human Beings

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    This eBook provides a comprehensive treatise on modern biomechatronic systems centred around human applications. A particular emphasis is given to exoskeleton designs for assistance and training with advanced interfaces in human-machine interaction. Some of these designs are validated with experimental results which the reader will find very informative as building-blocks for designing such systems. This eBook will be ideally suited to those researching in biomechatronic area with bio-feedback applications or those who are involved in high-end research on manmachine interfaces. This may also serve as a textbook for biomechatronic design at post-graduate level

    Microwire regenerative peripheral nerve interfaces with wireless recording and stimulation capabilities

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    A scalable microwire peripheral nerve interface was developed, which interacted with regenerated peripheral nerves in microchannel scaffolds. Neural interface technologies are envisioned to facilitate direct connections between the nervous system and external technologies such as limb prosthetics or data acquisition systems for further processing. Presented here is an animal study using a handcrafted microwire regenerative peripheral nerve interface, a novel neural interface device for communicating with peripheral nerves. The neural interface studies using animal models are crucial in the evaluation of efficacy and safety of implantable medical devices before their use in clinical studies.16-electrode microwire microchannel scaffolds were developed for both peripheral nerve regeneration and peripheral nerve interfacing. The microchannels were used for nerve regeneration pathways as a scaffolding material and the embedded microwires were used as a recording electrode to capture neural signals from the regenerated peripheral nerves. Wireless stimulation and recording capabilities were also incorporated to the developed peripheral nerve interface which gave the freedom of the complex experimental setting of wired data acquisition systems and minimized the potential infection of the animals from the wire connections

    Man to Machine, Applications in Electromyography

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