Online Learning for the Control of Human Standing via Spinal Cord Stimulation

Many applications in recommender systems or experimental design need to make decisions online. Each decision leads to a stochastic reward with initially unknown distribution, while new decisions are made based on the observations of previous rewards. To maximize the total reward, one needs to balance between exploring different strategies and exploiting currently optimal strategies within a given set of strategies. This is the underlying trade-off of a number of clinical neural engineering problems, including brain-computer interface, deep brain stimulation, and spinal cord injury therapy. In these systems, complex electronic and computational systems interact with the human central nervous system. A critical issue is how to control the agents to produce results which are optimal under some measure, for example, efficiently decoding the user's intention in a brain-computer interface or performs temporal and spatial specific stimulation in deep brain stimulation. This dissertation is motivated by electrical sipnal cord stimulation with high dimensional inputs(multi-electrode arrays). The stimulation is applied to promote the function and rehabilitation of the remaining neural circuitry below the spinal cord injury, and enable complex motor behaviors such as stepping and standing. To enable the careful tuning of these stimuli for each patient, the electrode arrays which deliver these stimuli have become increasingly more sophisticated, with a corresponding increase in the number of free parameters over which the stimuli need to be optimized. Since the number of stimuli is growing exponentially with the number of electrodes, algorithmic methods of selecting stimuli is necessary, particularly when the feedback is expensive to get. In many online learning settings, particularly those that involve human feedback, reliable feedback is often limited to pairwise preferences instead of real valued feedback. Examples include implicit or subjective feedback for information retrieval and recommender systems, such as clicks on search results, and subjective feedback on the quality of recommended care. Sometimes with real valued feedback, we require that the sampled function values exceed some prespecified ``safety'' threshold, a requirement that existing algorithms fail to meet. Examples include medical applications where the patients' comfort must be guaranteed; recommender systems aiming to avoid user dissatisfaction; and robotic control, where one seeks to avoid controls that cause physical harm to the platform. This dissertation provides online learning algorithms for several specific online decision-making problems. \selfsparring optimizes the cumulative reward with relative feedback. RankComparison deals with ranking feedback. \safeopt considers the optimization with real valued feedback and safety constraints. \cduel is designed for specific spinal cord injury therapy. A variant of \cduel was implemented in closed-loop human experiments, controlling which epidural stimulating electrodes are used in the spinal cord of SCI patients. The results obtained are compared with concurrent stimulus tuning carried out by human experimenter. These experiments show that this algorithm is at least as effective as the human experimenter, suggesting that this algorithm can be applied to the more challenging problems of enabling and optimizing complex, sensory-dependent behaviors, such as stepping and standing in SCI patients. In order to get reliable quantitative measurements besides comparisons, the standing behaviors of paralyzed patients under spinal cord stimulation are evaluated. The potential of quantifying the quality of bipedal standing in an automatic approach is also shown in this work.</p

Management of Degenerative Cervical Myelopathy and Spinal Cord Injury

The present Special Issue is dedicated to presenting current research topics in DCM and SCI in an attempt to bridge gaps in knowledge for both of the two main forms of SCI. The issue consists of fourteen studies, of which the majority were on DCM, the more common pathology, while three studies focused on tSCI. This issue includes two narrative reviews, three systematic reviews and nine original research papers. Areas of research covered include image studies, predictive modeling, prognostic factors, and multiple systemic or narrative reviews on various aspects of these conditions. These articles include the contributions of a diverse group of researchers with various approaches to studying SCI coming from multiple countries, including Canada, Czech Republic, Germany, Poland, Switzerland, United Kingdom, and the United States

Optimizing sensory stimulation in humans after spinal cord injury

Sensory stimulation has shown promise in improving human walking after spinal cord injury (SCI). Previous studies have demonstrated some improvement with open-loop, non-individualized sensory stimulation, but after SCI, there are many unique, individual changes in sensorimotor processing. These changes make a priori identification of the best sensory stimulation pattern difficult for any given individual. Real-time optimization provides a solution to this individuality problem, through optimizing sensory stimulation parameters for a given subject in on-line (in real-time). In this research, I developed an approach to optimize sensory stimulation to maximally assist human walking after incomplete SCI. To do so, I had to develop and validate a novel optimization algorithm for globally-optimizing noisy, time-variant, black-box systems, while maximizing the information gained from each test (experiment). I optimized sensory stimulation across a range of SCI subjects, across multiple sensory stimulation sites, and with different stimulation parameterizations. In all subjects and stimulation sites, the optimal stimulation protocol produced better walking (i.e. less external force assistance was required) than three alternative stimulation protocols: an industry-standard stimulation protocol, a no-stimulation protocol, and a random-stimulation protocol. The optimization approach minimized the total force required from an assistive orthosis, and post-hoc analysis of the optimization sessions produced a better understanding of how stimulation parameters affected specific gait features (e.g. hip forces during swing). Transcutaneous spinal cord stimulation (TSCS) frequency had divergent effects on the stance and swing phases – high frequencies tended to assist with swing, but low frequencies tended to assist with stance. For the two peripheral nerve stimulation sites (posterior tibial and common peroneal nerves), the optimal gait-phase for stimulation was generally after mid-stance and before early swing. There was some variability within this time-range depending on the specific feature under study. Experimental history (i.e. time spent walking/time spent being stimulated) proved to be as important a predictor as any of the stimulation parameters.Ph.D

Trauma, Tumors, Spine, Functional Neurosurgery

This book is written for graduate students, researchers, and practitioners who are interested in learning how the knowledge from research can be implemented in clinical competences. The first section is dedicated to deep brain stimulation, a surgical procedure which is the paramount example of how clinical practice can take advantage from fundamental research. The second section gathers four chapters on four different topics and illustrates how significant is the challenge to translate scientific advances into clinical practice because the route from evidence to action is not always obvious. It is hoped that this book will stimulate the interest in the process of translating research into practice for a broader range of neurosurgical topics than the one covered by this book, which could result in a forthcoming more comprehensive publication

EEG and ECoG features for Brain Computer Interface in Stroke Rehabilitation

The ability of non-invasive Brain-Computer Interface (BCI) to control an exoskeleton was used for motor rehabilitation in stroke patients or as an assistive device for the paralyzed. However, there is still a need to create a more reliable BCI that could be used to control several degrees of Freedom (DoFs) that could improve rehabilitation results. Decoding different movements from the same limb, high accuracy and reliability are some of the main difficulties when using conventional EEG-based BCIs and the challenges we tackled in this thesis. In this PhD thesis, we investigated that the classification of several functional hand reaching movements from the same limb using EEG is possible with acceptable accuracy. Moreover, we investigated how the recalibration could affect the classification results. For this reason, we tested the recalibration in each multi-class decoding for within session, recalibrated between-sessions, and between sessions. It was shown the great influence of recalibrating the generated classifier with data from the current session to improve stability and reliability of the decoding. Moreover, we used a multiclass extension of the Filter Bank Common Spatial Patterns (FBCSP) to improve the decoding accuracy based on features and compared it to our previous study using CSP. Sensorimotor-rhythm-based BCI systems have been used within the same frequency ranges as a way to influence brain plasticity or controlling external devices. However, neural oscillations have shown to synchronize activity according to motor and cognitive functions. For this reason, the existence of cross-frequency interactions produces oscillations with different frequencies in neural networks. In this PhD, we investigated for the first time the existence of cross-frequency coupling during rest and movement using ECoG in chronic stroke patients. We found that there is an exaggerated phase-amplitude coupling between the phase of alpha frequency and the amplitude of gamma frequency, which can be used as feature or target for neurofeedback interventions using BCIs. This coupling has been also reported in another neurological disorder affecting motor function (Parkinson and dystonia) but, to date, it has not been investigated in stroke patients. This finding might change the future design of assistive or therapeuthic BCI systems for motor restoration in stroke patients

Spine Surgery

We are very excited to introduce this new book on spinal surgery, which follows the curriculum of the EUROSPINE basic and advanced diploma courses. The approach we take is a purely case-based one, in which each case illustrates the concepts surrounding the treatment of a given pathology, including the uncertainties and problems in decision-making. The readers will notice that in many instances a lack of evidence for a given treatment exists. So decisions taken are usually not a clearcut matter of black or white, but merely different shades of gray. Probably in a lot of cases, there is often more than one option to treat the patient. The authors were asked to convey this message to the reader, giving him a guidance as what would be accepted within the mainstream. In addition, the reader is provided with the most updated literature and evidence on the topic. Most of the authors are teachers in the courses of EUROSPINE or other national societies with often vast clinical experience and have given their own perspective and reasoning. We believe that the readers will profit very much from this variety and bandwidth of knowledge provided for them in the individual chapters. We have given the authors extensive liberty as to what they consider the best solution for their case. It is thus a representative picture of what is considered standard of care for spine pathologies in Europe. We hope that this book will be an ideal complement for trainees to the courses they take. Munich, Germany Bernhard Meyer Offenbach, Germany Michael Rauschman

Source reconstruction of the neural correlates of ongoing pain using magnetoencephalography

Pain is a pervasive, complex, and subjective phenomenon that can be described by many features and researched using many paradigms; chronic pain has a significant impact on the quality of life of patients experiencing it and constitutes a large burden on the National Health Service. Discovering neural biomarkers for ongoing pain and pain sensitivity has the potential to elucidate underlying mechanisms, evaluate therapy effectiveness, and identify regions of interest within the brain for further study or intervention; something that is possible with functional imaging of brain activity. Magnetoencephalography (MEG) is a non-invasive technique that records brain activity through magnetic fields unobstructed by tissue of the head. This thesis utilises modern source reconstruction of MEG data to explore brain activity that characterises tonic pain conditions, and explores the future of tonic pain research by evaluating the utility of the PATHWAY Contact Heat Evoked Potentials Stimulator (CHEPS) – a tool used both as an experimental pain stimulus, and a clinical evaluation method in chronic pain – in current and future MEG research. A systematic review of studies exploring the CHEPS and MEG, which highlights the paucity of the literature combining the two despite the potential benefits of each, is presented within. Study one investigates the brain activity changes resulting from paraesthesia-based Spinal Cord Stimulation for chronic pain: significant enhancements in synchrony for theta and delta frequency bands during SCS-on resting-state are demonstrated, and a significant reduction in Somatosensory Evoked Potential (SSEP) power spectra in the SCS-on condition – providing evidence that conventional SCS influences resting and ascending processing in the brain, but does not necessarily suppress the field strength of SSEPs. Study two compared the neural activity of participants with high and low pain sensitivity during the Cold Pressor Test, and identifies regions of interest for future study. Study three is a methodological chapter which attempts to mitigate the methodological challenges involved in utilising the PATHWAY CHEPS in MEG research: The thorough exploration of independent component analysis, signal space separation and beamforming parameters demonstrates that it is possible to suppress the artefacts generated by the non-fMRI compatible CHEPS’ thermode with the application of signal attenuation techniques, but only in an empty room dataset; the implications of this for future research are discussed

Infrared Thermography for the Assessment of Lumbar Sympathetic Blocks in Patients with Complex Regional Pain Syndrome

[ES] El síndrome de dolor regional complejo (SDRC) es un trastorno de dolor crónico debilitante que suele afectar a una extremidad, y se caracteriza por su compleja e incomprendida fisiopatología subyacente, lo que supone un reto para su diagnóstico y tratamiento. Para evitar el deterioro de la calidad de vida de los pacientes, la consecución de un diagnóstico y tratamiento tempranos marca un punto de inflexión. Entre los diferentes tratamientos, los bloqueos simpáticos lumbares (BSLs) tienen como objetivo aliviar el dolor y reducir algunos signos simpáticos de la afección. Este procedimiento intervencionista se lleva a cabo inyectando anestesia local alrededor de los ganglios simpáticos y, hasta ahora, se realiza frecuentemente bajo el control de diferentes técnicas de imagen, como los ultrasonidos o la fluoroscopia. Dado que la termografía infrarroja (TIR) ha demostrado ser una herramienta eficaz para evaluar la temperatura de la piel, y teniendo en cuenta el efecto vasodilatador que presentan los anestésicos locales inyectados, se ha considerado el uso de la IRT para la evaluación de los BSLs. El objetivo de esta tesis es, estudiar la capacidad de la TIR como una técnica complementaria para la evaluación de la eficacia en la ejecución de los BSLs. Para cumplir este objetivo, se han realizado tres estudios implementando la TIR en pacientes diagnosticados de SDRC de miembros inferiores sometidos a BSLs. El primer estudio se centra en la viabilidad de la TIR como herramienta complementaria para la evaluación de la eficacia ejecución de los BSLs. Cuando se realizan los BSLs, la colocación correcta de la aguja es crítica para llevar realizar el procedimiento técnicamente correcto y, en consecuencia, para lograr los resultados clínicos deseados. Para verificar la posición de la aguja, tradicionalmente se han utilizado técnicas de imagen, sin embargo, los BSLs bajo control fluoroscópico no siempre aseguran su exacta ejecución. Por este motivo, se han aprovechado las alteraciones térmicas inducidas por los anestésicos locales y se han evaluado mediante la TIR. Así, cuando en las imágenes infrarrojas se observaron cambios térmicos en la planta del pie afectado tras la inyección de lidocaína, se consideró que el BSL era exitoso. El segundo estudio trata del análisis cuantitativo de los datos térmicos recogidos en el entorno clínico a partir de diferentes parámetros basados en las temperaturas extraídas de ambos pies. Según los resultados, para predecir adecuadamente los BSLs exitosos, se deberían analizar las temperaturas de las plantas de los pies durante los primeros cuatro minutos tras la inyección del anestésico local. Así, la aplicación de la TIR en el entorno clínico podría ser de gran ayuda para evaluar la eficacia de ejecución de los BSLs mediante la evaluación de las temperaturas de los pies en tiempo real. Por último, el tercer estudio aborda el análisis cuantitativo mediante la implementación de herramientas de machine learning (ML) para evaluar su capacidad de clasificar automáticamente los BSLs. En este estudio se han utilizado una serie de características térmicas extraídas de las imágenes infrarrojas para evaluar cuatro algoritmos de ML para tres momentos diferentes después del instante de referencia (inyección de lidocaína). Los resultados indican que los cuatro modelos evaluados presentan buenos rendimientos para clasificar automáticamente los BSLs entre exitosos y fallidos. Por lo tanto, la combinación de parámetros térmicos junto con de clasificación ML muestra ser eficaz para la clasificación automática de los procedimientos de BSLs. En conclusión, el uso de la TIR como técnica complementaria en la práctica clínica diaria para la evaluación de los BSLs ha demostrado ser totalmente eficaz. Dado que es un método objetivo y relativamente sencillo de implementar, puede permitir que los médicos especialistas en dolor identifiquen los bloqueos realizados fallidos y, en consecuencia, puedan revertir esta situación.[CA] La síndrome de dolor regional complex (SDRC) és un trastorn de dolor crònic debilitant que sol afectar una extremitat, i es caracteritza per la seua complexa i incompresa fisiopatologia subjacent, la qual cosa suposa un repte per al seu diagnòstic i tractament. Per a evitar la deterioració de la qualitat de vida dels pacients, la consecució d'un diagnòstic i tractament primerencs marca un punt d'inflexió. Entre els diferents tractaments , els bloquejos simpàtics lumbars (BSLs) tenen com a objectiu alleujar el dolor i reduir alguns signes simpàtics de l'afecció. Aquest procediment intervencionista es duu a terme injectant anestèsia local al voltant dels ganglis simpàtics i, fins ara, es realitza freqüentment sota el control de diferents tècniques d'imatge, com els ultrasons o la fluoroscopia. Atés que la termografia infraroja (TIR) ha demostrat ser una eina eficaç per a avaluar la temperatura de la pell, i tenint en compte l'efecte vasodilatador que presenten els anestèsics locals injectats, s'ha considerat l'ús de la TIR per a l'avaluació dels BSLs. L'objectiu d'aquesta tesi és, estudiar la capacitat de la TIR com una tècnica complementària per a l'avaluació de l'eficàcia en l'execució dels BSLs. Per a complir aquest objectiu, s'han realitzat tres estudis implementant la TIR en pacients diagnosticats de SDRC de membres inferiors sotmesos a BSLs. El primer estudi avalua la viabilitat de la TIR com a eina complementària per a l'analisi de l'eficàcia en l'execució dels BSLs. Quan es realitzen els BSLs, la col·locació correcta de l'agulla és crítica per a dur a terme el procediment tècnicament correcte i, en conseqüència, per a aconseguir els resultats clínics desitjats. Per a verificar la posició de l'agulla, tradicionalment s'han utilitzat tècniques d'imatge, no obstant això, els BSLs baix control fluoroscòpic no sempre asseguren la seua exacta execució. Per aquest motiu, s'han aprofitat les alteracions tèrmiques induïdes pels anestèsics locals i s'han avaluat mitjançant la TIR. Així, quan en les imatges infraroges es van observar canvis tèrmics en la planta del peu afectat després de la injecció de lidocaIna, es va considerar que el BSL era exitós. El segon estudi tracta de l'anàlisi quantitativa de les dades tèrmiques recollides en l'entorn clínic a partir de diferents paràmetres basats en les temperatures extretes d'ambdós peus. Segons els resultats, per a predir adequadament l'execució exitosa d'un BSL, s'haurien d'analitzar les temperatures de les plantes dels peus durant els primers quatre minuts després de la injecció de l'anestèsic local. Així, l'implementació de la TIR en l'entorn clínic podria ser de gran ajuda per a avaluar l'eficàcia d'execució dels BSLs mitjançant l'avaluació de les temperatures dels peus en temps real. El tercer estudi aborda l'anàlisi quantitativa mitjançant la implementació d'eines machine learning (ML) per a avaluar la seua capacitat de classificar automàticament els BSLs. En aquest estudi s'han utilitzat una sèrie de característiques tèrmiques extretes de les imatges infraroges per a avaluar quatre algorismes de ML per a tres moments diferents després de l'instant de referència (injecció de lidocaïna). Els resultats indiquen que els quatre models avaluats presenten bons rendiments per a classificar automàticament els BSLs en exitosos i fallits. Per tant, la combinació de paràmetres tèrmics juntament amb models de classificació ML mostra ser eficaç per a la classificació automàtica dels procediments de BSLs. En conclusió, l'ús de la TIR com a tècnica complementària en la pràctica clínica diària per a l'avaluació dels BSLs ha demostrat ser totalment eficaç. Atés que és un mètode objectiu i relativament senzill d'implementar, pot ajudar els metges especialistes en dolor a identificar els bloquejos realitzats fallits i, en conseqüència, puguen revertir aquesta situació.[EN] Complex regional pain syndrome (CRPS) is a debilitating chronic pain condition that usually affects one limb, and it is characterized by its misunderstood underlying pathophysiology, resulting in both challenging diagnosis and treatment. To avoid the patients' impairment quality of life, the achievement of both an early diagnosis and treatment marks a turning point. Among the different treatment approaches, lumbar sympathetic blocks (LSBs) are addressed to alleviate the pain and reduce some sympathetic signs of the condition. This interventional procedure is performed by injecting local anaesthetic around the sympathetic ganglia and, until now, it has been performed under different imaging techniques, including the ultrasound or the fluoroscopy approaches. Since infrared thermography (IRT) has proven to be a powerful tool to evaluate skin temperatures and taking into account the vasodilatory effects of the local anaesthetics injected in the LSB, the use of IRT has been considered for the LSBs assessment. Therefore, the purpose of this thesis is to evaluate the capability of IRT as a complementary assessment technique for the LSBs procedures performance. To fulfil this aim, three studies have been conducted implementing the IRT in patients diagnosed with lower limbs CRPS undergoing LSBs. The first study focuses on the feasibility of IRT as a complementary assessment tool for LSBs performance, that is, for the confirmation of the proper needle position. When LSBs are performed, the correct needle placement is critical to carry out the procedure technically correct and, consequently, to achieve the desired clinical outcomes. To verify the needle placement position, imaging techniques have traditionally been used, however, LSBs under radioscopic guidance do not always ensure an exact performance. For this reason, the thermal alterations induced by the local anaesthetics, have been exploited and assessed by means of IRT. Thus, the LSB procedure was considered successfully performed when thermal changes within the affected plantar foot were observed in the infrared images after the lidocaine injection. The second study deals with the quantitative analysis of the thermal data collected in the clinical setting through the evaluation of different temperature-based parameters extracted from both feet. According to the results, the proper LSB success prediction could be achieved in the first four minutes after the block through the evaluation of the feet skin temperatures. Therefore, the implementation of IRT in the clinical setting might be of great help in assessing the LSBs performance by evaluating the plantar feet temperatures in real time. Finally, the third study addresses the quantitative analysis by implementing machine learning (ML) tools to assess their capability to automatically classify LSBs. In this study, a set of thermal features retrieved from the infrared images have been used to evaluate four ML algorithms for three different moments after the baseline time (lidocaine injection). The results indicate that all four models evaluated present good performance metrics to automatically classify LSBs into successful and failed. Therefore, combining infrared features with ML classification models shows to be effective for the LSBs procedures automatic classification. In conclusion, the use of IRT as a complementary technique in daily clinical practice for LSBs assessment has been evidenced entirely effective. Since IRT is an objective method and it is not very demanding to perform, it is of great help for pain physicians to identify failed procedures, and consequently, it allow them to reverse this situation.Cañada Soriano, M. (2022). Infrared Thermography for the Assessment of Lumbar Sympathetic Blocks in Patients with Complex Regional Pain Syndrome [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/181699TESI