No description available.

Os potenciais evocados têm uma consagrada utilização em clínica. Sua obtenção é dificultada pela presença de outros sinais biológicos, de artefatos de movimento, de ruído eletrônico, de interferência da rede elétrica e de artefatos de estímulo. A média síncrona ou promediação é um método que elimina os sinais que não estejam sincronizados com a estimulação, incluindo os outros sinais biológicos, os artefatos de movimento, o ruído e a interferência. No entanto, esse método não consegue eliminar os artefatos de estímulo. Outros métodos devem ser usados para essa tarefa. Para esses métodos, a eliminação do artefato de estímulo é bem sucedida quando o artefato não se sobrepõe ao potencial evocado. Porém, para uma captação próxima ao local de estimulação, a sobreposição ocorre e dificulta a eliminação do artefato de estímulo. O objetivo deste trabalho foi o de estudar a variação da amplitude e latência do pico do potencial evocado e sua influência nas estimativas da amplitude, da latência e do erro quadrático médio. Para potenciais evocados em que houve sobreposição com o artefato, o erro médio quadrático sempre foi reduzido com a remoção do artefato de estímulo. O erro de medição da latência foi reduzido a praticamente zero, independentemente da amplitude do potencial evocado. Por outro lado, o método inseriu erro na medição da amplitude de potenciais evocados grandes. Por isso, nesse caso específico de atraso pequeno e amplitude grande, a medição da amplitude deve ser feita diretamente no sinal antes da remoção do artefato de estímulo. Comparando a ocorrência de sobreposição com os locais de captação do potencial evocado, pode-se afirmar que, para o modelo de artefato de estímulo usado neste trabalho, a necessidade de se aplicar o procedimento de remoção de artefato se restringiu aos potenciais evocados captados no cotovelo, para estimulação do nervo mediano tanto no punho quanto na mão. / Evoked potentials have been used in clinics. Their measurement is hindered by the presence of other biological signals, movement artifacts, electronic noise, power-line interference, and stimulus artifacts. Synchronous averaging is a method that eliminates the signals that are not synchronized with the stimulation, including other biological signals, movement artifacts, noise and interference. However, this method fails to eliminate stimulus artifacts. Other methods must be used in this task. Using these methods, one can obtain success in the stimulus artifact elimination, whenever the artifact does not superimpose with the evoked potential. Nevertheless, for a measurement close to the stimulation site, the superimposition is a fact that hinders the elimination of the stimulus artifact. The objective of this Masters thesis was to study the variation of the amplitude and latency of an evoked potential and verify their influence on the amplitude and latency estimates, as well as on the mean square error. For evoked potentials in which there was superposition, the mean square error was always reduced by the removal of the stimulus artifact. Latency measurement errors were reduced to zero, regardless of the evoked potential amplitude. However, this method inserted amplitude measurement errors for large evoked potentials. So, in the case of short delays and large amplitudes, amplitude measurements should be performed directly on the signal, before stimulus artifact removal. By comparing the presence of superposition with the evoked potential recording sites, one may state that, for the stimulus artifact model used in this work, the need to apply the artifact removal procedure was restricted to the evoked potentials recorded on the elbow, for median nerve stimulation both on wrist and hand.

Os potenciais evocados têm uma consagrada utilização em clínica. Sua obtenção é dificultada pela presença de outros sinais biológicos, de artefatos de movimento, de ruído eletrônico, de interferência da rede elétrica e de artefatos de estímulo. A média síncrona ou promediação é um método que elimina os sinais que não estejam sincronizados com a estimulação, incluindo os outros sinais biológicos, os artefatos de movimento, o ruído e a interferência. No entanto, esse método não consegue eliminar os artefatos de estímulo. Outros métodos devem ser usados para essa tarefa. Para esses métodos, a eliminação do artefato de estímulo é bem sucedida quando o artefato não se sobrepõe ao potencial evocado. Porém, para uma captação próxima ao local de estimulação, a sobreposição ocorre e dificulta a eliminação do artefato de estímulo. O objetivo deste trabalho foi o de estudar a variação da amplitude e latência do pico do potencial evocado e sua influência nas estimativas da amplitude, da latência e do erro quadrático médio. Para potenciais evocados em que houve sobreposição com o artefato, o erro médio quadrático sempre foi reduzido com a remoção do artefato de estímulo. O erro de medição da latência foi reduzido a praticamente zero, independentemente da amplitude do potencial evocado. Por outro lado, o método inseriu erro na medição da amplitude de potenciais evocados grandes. Por isso, nesse caso específico de atraso pequeno e amplitude grande, a medição da amplitude deve ser feita diretamente no sinal antes da remoção do artefato de estímulo. Comparando a ocorrência de sobreposição com os locais de captação do potencial evocado, pode-se afirmar que, para o modelo de artefato de estímulo usado neste trabalho, a necessidade de se aplicar o procedimento de remoção de artefato se restringiu aos potenciais evocados captados no cotovelo, para estimulação do nervo mediano tanto no punho quanto na mão. / Evoked potentials have been used in clinics. Their measurement is hindered by the presence of other biological signals, movement artifacts, electronic noise, power-line interference, and stimulus artifacts. Synchronous averaging is a method that eliminates the signals that are not synchronized with the stimulation, including other biological signals, movement artifacts, noise and interference. However, this method fails to eliminate stimulus artifacts. Other methods must be used in this task. Using these methods, one can obtain success in the stimulus artifact elimination, whenever the artifact does not superimpose with the evoked potential. Nevertheless, for a measurement close to the stimulation site, the superimposition is a fact that hinders the elimination of the stimulus artifact. The objective of this Masters thesis was to study the variation of the amplitude and latency of an evoked potential and verify their influence on the amplitude and latency estimates, as well as on the mean square error. For evoked potentials in which there was superposition, the mean square error was always reduced by the removal of the stimulus artifact. Latency measurement errors were reduced to zero, regardless of the evoked potential amplitude. However, this method inserted amplitude measurement errors for large evoked potentials. So, in the case of short delays and large amplitudes, amplitude measurements should be performed directly on the signal, before stimulus artifact removal. By comparing the presence of superposition with the evoked potential recording sites, one may state that, for the stimulus artifact model used in this work, the need to apply the artifact removal procedure was restricted to the evoked potentials recorded on the elbow, for median nerve stimulation both on wrist and hand.

<p>Deep brain stimulation (DBS) is an established surgical therapy for movement disorders. The mechanisms of action of DBS remain unclear, and selection of stimulation parameters is a clinical challenge and can result in sub-optimal outcomes. Closed-loop DBS systems would use a feedback control signal for automatic adjustment of DBS parameters and improved therapeutic effectiveness. We hypothesized that evoked compound action potentials (ECAPs), generated by activated neurons in the vicinity of the stimulating electrode, would reveal the type and spatial extent of neural activation, as well as provide signatures of clinical effectiveness. The objective of this dissertation was to record and characterize the ECAP during DBS to determine its suitability as a feedback signal in closed-loop systems. The ECAP was investigated using computer simulation and <italic>in vivo</italic> experiments, including the first preclinical and clinical ECAP recordings made from the same DBS electrode implanted for stimulation. </p><p>First, we developed DBS-ECAP recording instrumentation to reduce the stimulus artifact and enable high fidelity measurements of the ECAP at short latency. <italic>In vitro</italic> and <italic>in vivo</italic> validation experiments demonstrated the capability of the instrumentation to suppress the stimulus artifact, increase amplifier gain, and reduce distortion of short latency ECAP signals.</p><p>Second, we characterized ECAPs measured during thalamic DBS across stimulation parameters in anesthetized cats, and determined the neural origin of the ECAP using pharmacological interventions and a computer-based biophysical model of a thalamic network. This model simulated the ECAP response generated by a population of thalamic neurons, calculated ECAPs similar to experimental recordings, and indicated the relative contribution from different types of neural elements to the composite ECAP. Signal energy of the ECAP increased with DBS amplitude or pulse width, reflecting an increased extent of activation. Shorter latency, primary ECAP phases were generated by direct excitation of neural elements, whereas longer latency, secondary phases were generated by post-synaptic activation.</p><p>Third, intraoperative studies were conducted in human subjects with thalamic DBS for tremor, and the ECAP and tremor responses were measured across stimulation parameters. ECAP recording was technically challenging due to the presence of a wide range of stimulus artifact magnitudes across subjects, and an electrical circuit equivalent model and finite element method model both suggested that glial encapsulation around the DBS electrode increased the artifact size. Nevertheless, high fidelity ECAPs were recorded from acutely and chronically implanted DBS electrodes, and the energy of ECAP phases was correlated with changes in tremor. </p><p>Fourth, we used a computational model to understand how electrode design parameters influenced neural recording. Reducing the diameter or length of recording contacts increased the magnitude of single-unit responses, led to greater spatial sensitivity, and changed the relative contribution from local cells or passing axons. The effect of diameter or contact length varied across phases of population ECAPs, but ECAP signal energy increased with greater contact spacing, due to changes in the spatial sensitivity of the contacts. In addition, the signal increased with glial encapsulation in the peri-electrode space, decreased with local edema, and was unaffected by the physical presence of the highly conductive recording contacts.</p><p>It is feasible to record ECAP signals during DBS, and the correlation between ECAP characteristics and tremor suggests that this signal could be used in closed-loop DBS. This was demonstrated by implementation in simulation of a closed-loop system, in which a proportional-integral-derivative (PID) controller automatically adjusted DBS parameters to obtain a target ECAP energy value, and modified parameters in response to disturbances. The ECAP also provided insight into neural activation during DBS, with the dominant contribution to clinical ECAPs derived from excited cerebellothalamic fibers, suggesting that activation of these fibers is critical for DBS therapy.</p> / Dissertation

No description available.

<div>Electrical nerve stimulation (ENS) is an emerging therapy for many neurological disorders. Compared with conventional one-way stimulations, closed-loop ENS approaches increase the stimulation efficacy and minimize patient's discomfort by constantly adjusting the stimulation parameters according to the feedback biomarkers from patients. Wireless neurostimulation devices capable of both stimulation and telemetry of recorded physiological signals are welcome for closed-loop ENS systems to improve the quality and reduce the costs of treatments, and real-time digital signal processing (DSP) engines processing and extracting features from recorded signals can reduce the data transmission rate and the resulting power consumption of wireless devices. Electrically-evoked compound action potential (ECAP) is an objective measure of nerve activity and has been used as the feedback biomarker in closed-loop ENS systems including neural response telemetry (NRT) systems and a newly proposed autonomous nerve control (ANC) platform. It's desirable to design a DSP engine for real-time processing of ECAP in closed-loop ENS systems. </div><div><br></div><div>This thesis focuses on developing the DSP architecture for real-time processing of ECAP, including stimulus artifact rejection (SAR), denoising, and extraction of nerve fiber responses as biomedical features, and its VLSI implementation for optimal hardware costs. The first part presents the DSP architecture for real-time SAR and denoising of ECAP in NRT systems. A bidirectional-filtered coherent averaging (BFCA) method is proposed, which enables the configurable linear-phase filter to be realized hardware efficiently for distortion-free filtering of ECAPs and can be easily combined with the alternating-polarity (AP) stimulation method for SAR. Design techniques including folded-IIR filter and division-free averaging are incorporated to reduce the computation cost. The second part presents the fiber-response extraction engine (FREE), a dedicated DSP engine for nerve activation control in the ANC platform. FREE employs the DSP architecture of the BFCA method combined with the AP stimulation, and the architecture of computationally efficient peak detection and classification algorithms for fiber response extraction from ECAP. FREE is mapped onto a custom-made and battery-powered wearable wireless device incorporating a low-power FPGA, a Bluetooth transceiver, a stimulation and recording analog front-end and a power-management unit. In comparison with previous software-based signal processing, FREE not only reduces the data rate of wireless devices but also improves the precision of fiber response classification in noisy environments, which contributes to the construction of high-accuracy nerve activation profile in the ANC platform. An application-specific integrated circuit (ASIC) version of FREE is implemented in 180-nm CMOS technology, with total chip area and core power consumption of 19.98 mm² and 1.95 mW, respectively. </div><div><br></div>