Stimulation discomfort comparison of asynchronous and synchronous methods with multi-field electrodes

Functional Electrical Stimulation (FES) is a technique that consists on applying electrical current pulses to artificially activate motor nerve fibers and produce muscle contractions to achieve functional movements. The main applications of FES are within the rehabilitation field, in which this technique is used to aid recovery or to restore lost motor functions. People that benefit of FES are usually patients with neurological disorders which result in motor dysfunctions; most common patients include stroke and spinal cord injury (SCI). Neuroprosthesis are devices that have their basis in FES technique, and their aim is to bridge interrupted or damaged neural paths between the brain and upper or lower limbs. One of the aims of neuroprosthesis is to artificially generate muscle contractions that produce functional movements, and therefore, assist impaired people by making them able to perform activities of daily living (ADL). FES applies current pulses and stimulates nerve fibers by means of electrodes, which can be either implanted or surface electrodes. Both of them have advantages and disadvantages. Implanted electrodes need open surgery to place them next to the nerve root, so these electrodes carry many disadvantages that are produced by the use of invasive techniques. In return, as the electrodes are attached to the nerve, they make it easier to achieve selective functional movements. On the contrary, surface electrodes are not invasive and are easily attached or detached on the skin. Main disadvantages of surface electrodes are the difficulty of selectively stimulating nerve fibers and uncomfortable feeling perceived by users due to sensory nerves located in the skin. Electrical stimulation surface electrode technology has improved significantly through the years and recently, multi-field electrodes have been suggested. This multi-field or matrix electrode approach brings many advantages to FES; among them it is the possibility of easily applying different stimulation methods and techniques. The main goal of this thesis is therefore, to test two stimulation methods, which are asynchronous and synchronous stimulation, in the upper limb with multi-field electrodes. To this end, a purpose-built wrist torque measuring system and a graphic user interface were developed to measure wrist torque produced with each of the methods and to efficiently carry out the experiments. Then, both methods were tested on 15 healthy subjects and sensitivity results were analyzed for different cases. Results show that there are significant differences between methods regarding sensation in some cases, which can affect effectiveness or success of FES.Tecnalia and Fundación Iñaki Goenag

An implantable micro-system for neural prosthesis control and sensory feedback restoration in amputees

In this work, the prototype of an electronic bi-directional interface between the Peripheral Nervous System (PNS) and a neuro-controlled hand prosthesis is presented. The system is composed of two Integrated Circuits (ICs): a standard CMOS device for neural recording and a High Voltage (HV) CMOS device for neural stimulation. The integrated circuits have been realized in two different 0.35μm CMOS processes available fromAustriaMicroSystem(AMS). The recoding IC incorporates 8 channels each including the analog front-end and the A/D conversion based on a sigma delta architecture. It has a total area of 16.8mm2 and exhibits an overall power consumption of 27.2mW. The neural stimulation IC is able to provide biphasic current pulses to stimulate 8 electrodes independently. A voltage booster generates a 17V voltage supply in order to guarantee the programmed stimulation current even in case of high impedances at the electrode-tissue interface in the order of tens of k­. The stimulation patterns, generated by a 5-bit current DAC, are programmable in terms of amplitude, frequency and pulse width. Due to the huge capacitors of the implemented voltage boosters, the stimulation IC has a wider area of 18.6mm2. In addition, a maximum power consumption of 29mW was measured. Successful in-vivo experiments with rats having a TIME electrode implanted in the sciatic nerve were carried out, showing the capability of recording neural signals in the tens of microvolts, with a global noise of 7μVrms , and to selectively elicit the tibial and plantarmuscles using different active sites of the electrode. In order to get a completely implantable interface, a biocompatible and biostable package was designed. It hosts the developed ICs with the minimal electronics required for their proper operation. The package consists of an alumina tube closed at both extremities by two ceramic caps hermetically sealed on it. Moreover, the two caps serve as substrate for the hermetic feedthroughs to enable the device powering and data exchange with the external digital controller implemented on a Field-Programmable Gate Array (FPGA) board. The package has an outer diameter of 7mm and a total length of 26mm. In addition, a humidity and temperature sensor was also included inside the package to allow future hermeticity and life-time estimation tests. Moreover, a wireless, wearable and non-invasive EEG recording system is proposed in order to improve the control over the artificial limb,by integrating the neural signals recorded from the PNS with those directly acquired from the brain. To first investigate the system requirements, a Component-Off-The-Shelf (COTS) device was designed. It includes a low-power 8- channel acquisition module and a Bluetooth (BT) transceiver to transmit the acquired data to a remote platform. It was designed with the aimof creating a cheap and user-friendly system that can be easily interfaced with the nowadays widely spread smartphones or tablets by means of a mobile-based application. The presented system, validated through in-vivo experiments, allows EEG signals recording at different sample rates and with a maximum bandwidth of 524Hz. It was realized on a 19cm2 custom PCB with a maximum power consumption of 270mW

Rehabilitation Engineering

Population ageing has major consequences and implications in all areas of our daily life as well as other important aspects, such as economic growth, savings, investment and consumption, labour markets, pensions, property and care from one generation to another. Additionally, health and related care, family composition and life-style, housing and migration are also affected. Given the rapid increase in the aging of the population and the further increase that is expected in the coming years, an important problem that has to be faced is the corresponding increase in chronic illness, disabilities, and loss of functional independence endemic to the elderly (WHO 2008). For this reason, novel methods of rehabilitation and care management are urgently needed. This book covers many rehabilitation support systems and robots developed for upper limbs, lower limbs as well as visually impaired condition. Other than upper limbs, the lower limb research works are also discussed like motorized foot rest for electric powered wheelchair and standing assistance device

Haptics: Science, Technology, Applications

This open access book constitutes the proceedings of the 13th International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2022, held in Hamburg, Germany, in May 2022. The 36 regular papers included in this book were carefully reviewed and selected from 129 submissions. They were organized in topical sections as follows: haptic science; haptic technology; and haptic applications

High-aspect-ratio tridimensional electrode arrays for neural applications

Tese de Doutoramento em Engenharia Biomédica.Neural electrodes are a valuable tool that allows neuroscientists to monitor the neural activity of the brain with great spatial and temporal resolution. Micro and nanotechnology has allowed the development of high-density neural electrode arrays. In the present work, two different materials were used to perform neural arrays, namely silicon and aluminum. The main objective was the ability to reach areas of the brain between 2 mm and 4 mm deep due to its importance in small animal models such as the rat. In such animals, important brain structures such as the hippocampus are situated in this range of depth. Another key objective was the fabrication of probes with high-aspect-ratio in order to minimize tissue displacement and consequent adverse reactions caused by implantation. Four different prototypes each using a specific fabrication approach, were performed and described in detail. Two of these prototypes were performed with aluminum while the other two were performed with silicon. Standard microfabrication processes such as dicing, wet-etching, physical vapor deposition, and non-standard processes such as thermomigration, aluminum anodizing, polymer casting, and sanding were used. The combination of these standard and nonstandard processes allowed a simpler and cheaper fabrication approach when compared with commercially available arrays. The first aluminum prototype was composed by 100 micropillars with a gold electrode at each tip. The aluminum micropillars were encapsulated by aluminum oxide and were 3 mm long with an aspect-ratio of 12:1. The second version was composed by 25 micropillars encapsulated with medical grade epoxy each with a platinum electrode at the tip. Each micropillar was 3 mm long with an aspect-ratio of 19:1. The first silicon prototype was composed by 100 silicon micropillars, each 3 mm long with an aspect-ratio of 5:1. The second version was composed by 36 silicon micropillars encapsulated with medical grade epoxy, each with a platinum electrode at the tip. Each micropillar was 4 mm long with an aspect-ratio of 22:1. A slanted version of the second prototype was also fabricated, allowing progressively increasing penetration depths. Mechanical characterization was performed by implantation in agar gel and porcine cadaver brain while electrical characterization was performed by electrochemical impedance tests as well as cyclic voltammetry. Overall, aluminum showed to be a suitable alternative to silicon in terms of structural material. Also, a dicing based approach proved to be a cost-effective method able to perform high-aspect-ratio neural arrays.Os elétrodos neuronais são uma ferramenta que proporciona aos neurocientistas a capacidade de monitorizar a atividade neuronal do cérebro com uma grande resolução temporal e espacial. As micro e nanotecnologias proporcionaram o desenvolvimento de matrizes de elétrodos neuronais com alta densidade. No presente trabalho dois materiais foram usados para fabricar matrizes de elétrodos neuronais, nomeadamente o silício e o alumínio. O objetivo principal foi a capacidade de chegar a zonas do cérebro entre os 2 mm e 4 mm de profundidade devido a sua importância em modelos animais de pequeno porte como o rato. Nestes animais, estruturas cerebrais importantes como o hipocampo estão situadas nesta gama de profundidades. Outro objetivo chave foi o fabrico de elétrodos com alta razão de aspeto, de forma a minimizar a compressão de tecido neuronal e consequentes reações adversas causadas pela implantação. Quatro protótipos, cada um utilizando um tipo de fabrico específico foram desenvolvidos e descritos em detalhe. Dois desses protótipos foram fabricados com alumínio, enquanto os outros dois foram feitos em silício. Foram usados processos de microfabrico standard como corte com disco, corrosão química, deposição de filmes finos, e também processos não standard como termomigração, anodização do alumínio, molde de polímeros e lixamento. A combinação de processos standard e não standard permitiram uma abordagem de fabrico mais simples e barata quando comparada com a abordagem utilizada em elétrodos comercialmente disponíveis. O primeiro protótipo de alumínio foi composto por 100 micropilares com um elétrodo de ouro na ponta. Os micropilares de alumínio foram encapsulados com óxido de alumínio e tinham 3 mm de comprimento resultando numa razão de aspeto de 12:1. A segunda versão foi composta por 25 micropilares encapsulados com epóxi biocompatível, cada com um elétrodo de platina na ponta. Cada micropillar tinha 3 mm de comprimento com uma razão de aspeto de 5:1. O primeiro protótipo de silício foi composto por 100 micropilares de silício, cada com 3 mm de comprimento e com razão de aspeto de 5:1. A segunda versão foi composta por 36 micropilares de silício encapsulados com epóxi biocompatível e cada com um elétrodo de platina na ponta. Cada micropillar tinha 4 mm de comprimento resultando numa razão de aspeto de 22:1. Uma versão inclinada do segundo protótipo também foi fabricada, permitindo profundidades de penetração progressivas. A caracterização mecânica foi feita através de implantações em gelatina de agar e em cérebro de porco, enquanto a caracterização elétrica foi feita através de testes de impedância eletroquímica assim como testes de voltametria cíclica. No geral, o alumínio demonstrou ser uma alternativa viável ao silício em termos de material estrutural. A abordagem baseada no corte com disco provou ser um método económico capaz de realizar matrizes de elétrodos neuronais de grande razão de aspeto.Portuguese Foundation for Science and Technology (FCT) (SFRH/BD/89509/2012)

Automatic Pain Assessment by Learning from Multiple Biopotentials

Kivun täsmällinen arviointi on tärkeää kivunhallinnassa, erityisesti sairaan- hoitoa vaativille ipupotilaille. Kipu on subjektiivista, sillä se ei ole pelkästään aistituntemus, vaan siihen saattaa liittyä myös tunnekokemuksia. Tällöin itsearviointiin perustuvat kipuasteikot ovat tärkein työkalu, niin auan kun potilas pystyy kokemuksensa arvioimaan. Arviointi on kuitenkin haasteellista potilailla, jotka eivät itse pysty kertomaan kivustaan. Kliinisessä hoito- työssä kipua pyritään objektiivisesti arvioimaan esimerkiksi havainnoimalla fysiologisia muuttujia kuten sykettä ja käyttäytymistä esimerkiksi potilaan kasvonilmeiden perusteella. Tutkimuksen päätavoitteena on automatisoida arviointiprosessi hyödyntämällä koneoppimismenetelmiä yhdessä biosignaalien prosessointnin kanssa. Tavoitteen saavuttamiseksi mitattiin autonomista keskushermoston toimintaa kuvastavia biopotentiaaleja: sydänsähkökäyrää, galvaanista ihoreaktiota ja kasvolihasliikkeitä mittaavaa lihassähkökäyrää. Mittaukset tehtiin terveillä vapaaehtoisilla, joille aiheutettiin kokeellista kipuärsykettä. Järestelmän kehittämiseen tarvittavaa tietokantaa varten rakennettiin biopotentiaaleja keräävä Internet of Things -pohjainen tallennusjärjestelmä. Koostetun tietokannan avulla kehitettiin biosignaaleille prosessointimenetelmä jatku- vaan kivun arviointiin. Signaaleista eroteltiin piirteitä sekuntitasoon mukautetuilla aikaikkunoilla. Piirteet visualisoitiin ja tarkasteltiin eri luokittelijoilla kivun ja kiputason tunnistamiseksi. Parhailla luokittelumenetelmillä saavutettiin kivuntunnistukseen 90% herkkyyskyky (sensitivity) ja 84% erottelukyky (specificity) ja kivun voimakkuuden arviointiin 62,5% tarkkuus (accuracy). Tulokset vahvistavat kyseisen käsittelytavan käyttökelpoisuuden erityis- esti tunnistettaessa kipua yksittäisessä arviointi-ikkunassa. Tutkimus vahvistaa biopotentiaalien avulla kehitettävän automatisoidun kivun arvioinnin toteutettavuuden kokeellisella kivulla, rohkaisten etenemään todellisen kivun tutkimiseen samoilla menetelmillä. Menetelmää kehitettäessä suoritettiin lisäksi vertailua ja yhteenvetoa automaattiseen kivuntunnistukseen kehitettyjen eri tutkimusten välisistä samankaltaisuuksista ja eroista. Tarkastelussa löytyi signaalien eroavaisuuksien lisäksi tutkimusmuotojen aiheuttamaa eroa arviointitavoitteisiin, mikä hankaloitti tutkimusten vertailua. Lisäksi pohdit- tiin mitkä perinteisten prosessointitapojen osiot rajoittavat tai edistävät ennustekykyä ja miten, sekä tuoko optimointi läpimurtoa järjestelmän näkökulmasta.Accurate pain assessment plays an important role in proper pain management, especially among hospitalized people experience acute pain. Pain is subjective in nature which is not only a sensory feeling but could also combine affective factors. Therefore self-report pain scales are the main assessment tools as long as patients are able to self-report. However, it remains a challenge to assess the pain from the patients who cannot self-report. In clinical practice, physiological parameters like heart rate and pain behaviors including facial expressions are observed as empirical references to infer pain objectively. The main aim of this study is to automate such process by leveraging machine learning methods and biosignal processing. To achieve this goal, biopotentials reflecting autonomic nervous system activities including electrocardiogram and galvanic skin response, and facial expressions measured with facial electromyograms were recorded from healthy volunteers undergoing experimental pain stimulus. IoT-enabled biopotential acquisition systems were developed to build the database aiming at providing compact and wearable solutions. Using the database, a biosignal processing flow was developed for continuous pain estimation. Signal features were extracted with customized time window lengths and updated every second. The extracted features were visualized and fed into multiple classifiers trained to estimate the presence of pain and pain intensity separately. Among the tested classifiers, the best pain presence estimating sensitivity achieved was 90% (specificity 84%) and the best pain intensity estimation accuracy achieved was 62.5%. The results show the validity of the proposed processing flow, especially in pain presence estimation at window level. This study adds one more piece of evidence on the feasibility of developing an automatic pain assessment tool from biopotentials, thus providing the confidence to move forward to real pain cases. In addition to the method development, the similarities and differences between automatic pain assessment studies were compared and summarized. It was found that in addition to the diversity of signals, the estimation goals also differed as a result of different study designs which made cross dataset comparison challenging. We also tried to discuss which parts in the classical processing flow would limit or boost the prediction performance and whether optimization can bring a breakthrough from the system’s perspective

Wearable, low-power CMOS ISFETs and compensation circuits for on-body sweat analysis

Complementary metal-oxide-semiconductor (CMOS) technology has been a key driver behind the trend of reduced power consumption and increased integration of electronics in consumer devices and sensors. In the late 1990s, the integration of ion-sensitive field-effect transistors (ISFETs) into unmodified CMOS helped to create advancements in lab-on-chip technology through highly parallelised and low-cost designs. Using CMOS techniques to reduce power and size in chemical sensing applications has already aided the realisation of portable, battery-powered analysis platforms, however the possibility of integrating these sensors into wearable devices has until recently remained unexplored. This thesis investigates the use of CMOS ISFETs as wearable electrochemical sensors, specifically for on-body sweat analysis. The investigation begins by evaluating the ISFET sensor for wearable applications, identifying the key advantages and challenges that arise in this pursuit. A key requirement for wearable devices is a low power consumption, to enable a suitable operational life and small form factor. From this perspective, ISFETs are investigated for low power operation, to determine the limitations when trying to push down the consumption of individual sensors. Batteryless ISFET operation is explored through the design and implementation of a 0.35 \si{\micro\metre} CMOS ISFET sensing array, operating in weak-inversion and consuming 6 \si{\micro\watt}. Using this application-specific integrated circuit (ASIC), the first ISFET array powered by body heat is demonstrated and the feasibility of using near-field communication (NFC) for wireless powering and data transfer is shown. The thesis also presents circuits and systems for combatting three key non-ideal effects experienced by CMOS ISFETs, namely temperature variation, threshold voltage offset and drift. An improvement in temperature sensitivity by a factor of three compared to an uncompensated design is shown through measured results, while adding less than 70 \si{\nano\watt} to the design. A method of automatically biasing the sensors is presented and an approach to using spatial separation of sensors in arrays in applications with flowing fluids is proposed for distinguishing between signal and sensor drift. A wearable device using the ISFET-based system is designed and tested with both artificial and natural sweat, identifying the remaining challenges that exist with both the sensors themselves and accompanying components such as microfluidics and reference electrode. A new ASIC is designed based on the discoveries of this work and aimed at detecting multiple analytes on a single chip. %Removed In the latter half of the thesis, Finally, the future directions of wearable electrochemical sensors is discussed with a look towards embedded machine learning to aid the interpretation of complex fluid with time-domain sensor arrays. The contributions of this thesis aim to form a foundation for the use of ISFETs in wearable devices to enable non-invasive physiological monitoring.Open Acces

Biomechatronics: Harmonizing Mechatronic Systems with Human Beings

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

Haptics: Science, Technology, Applications

This open access book constitutes the proceedings of the 12th International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2020, held in Leiden, The Netherlands, in September 2020. The 60 papers presented in this volume were carefully reviewed and selected from 111 submissions. The were organized in topical sections on haptic science, haptic technology, and haptic applications. This year's focus is on accessibility

Touching on elements for a non-invasive sensory feedback system for use in a prosthetic hand

Hand amputation results in the loss of motor and sensory functions, impacting activities of daily life and quality of life. Commercially available prosthetic hands restore the motor function but lack sensory feedback, which is crucial to receive information about the prosthesis state in real-time when interacting with the external environment. As a supplement to the missing sensory feedback, the amputee needs to rely on visual and audio cues to operate the prosthetic hand, which can be mentally demanding. This thesis revolves around finding potential solutions to contribute to an intuitive non-invasive sensory feedback system that could be cognitively less burdensome and enhance the sense of embodiment (the feeling that an artificial limb belongs to one’s own body), increasing acceptance of wearing a prosthesis.A sensory feedback system contains sensors to detect signals applied to the prosthetics. The signals are encoded via signal processing to resemble the detected sensation delivered by actuators on the skin. There is a challenge in implementing commercial sensors in a prosthetic finger. Due to the prosthetic finger’s curvature and the fact that some prosthetic hands use a covering rubber glove, the sensor response would be inaccurate. This thesis shows that a pneumatic touch sensor integrated into a rubber glove eliminates these errors. This sensor provides a consistent reading independent of the incident angle of stimulus, has a sensitivity of 0.82 kPa/N, a hysteresis error of 2.39±0.17%, and a linearity error of 2.95±0.40%.For intuitive tactile stimulation, it has been suggested that the feedback stimulus should be modality-matched with the intention to provide a sensation that can be easily associated with the real touch on the prosthetic hand, e.g., pressure on the prosthetic finger should provide pressure on the residual limb. A stimulus should also be spatially matched (e.g., position, size, and shape). Electrotactile stimulation has the ability to provide various sensations due to it having several adjustable parameters. Therefore, this type of stimulus is a good candidate for discrimination of textures. A microphone can detect texture-elicited vibrations to be processed, and by varying, e.g., the median frequency of the electrical stimulation, the signal can be presented on the skin. Participants in a study using electrotactile feedback showed a median accuracy of 85% in differentiating between four textures.During active exploration, electrotactile and vibrotactile feedback provide spatially matched modality stimulations, providing continuous feedback and providing a displaced sensation or a sensation dispatched on a larger area. Evaluating commonly used stimulation modalities using the Rubber Hand Illusion, modalities which resemble the intended sensation provide a more vivid illusion of ownership for the rubber hand.For a potentially more intuitive sensory feedback, the stimulation can be somatotopically matched, where the stimulus is experienced as being applied on a site corresponding to their missing hand. This is possible for amputees who experience referred sensation on their residual stump. However, not all amputees experience referred sensations. Nonetheless, after a structured training period, it is possible to learn to associate touch with specific fingers, and the effect persisted after two weeks. This effect was evaluated on participants with intact limbs, so it remains to evaluate this effect for amputees.In conclusion, this thesis proposes suggestions on sensory feedback systems that could be helpful in future prosthetic hands to (1) reduce their complexity and (2) enhance the sense of body ownership to enhance the overall sense of embodiment as an addition to an intuitive control system