A estimulação elétrica periférica (PES), que abrange diversas técnicas com respostas fisiológicas diversas, tem apresentado em alguns casos resultados clínicos promissores para o tratamento da dor e reabilitação clínica. No entanto, as respostas encontradas são heterogêneas, principalmente porque há uma falta de compreensão em relação ao seu mecanismo de ação. Neste estudo, buscamos avaliar os efeitos da PES através da medição da ativação cortical cerebral utilizando a espectroscopia funcional por infravermelho (fNIRS). A fNIRS é um método de imagem óptica funcional que avalia mudanças hemodinâmicas nas concentrações de hemoglobina oxigenada (HbO) e desoxigenada (HbR), relacionadas à atividade cortical. Nós hipotetizamos que a PES do nervo acessório espinal (ASN) pode promover a ativação do córtex motor (MC) e do córtex pré-frontal dorsolateral (DLPFC), relacionados ao processamento da dor. Quinze voluntários saudáveis receberam estimulação elétrica ativa e sham em um ensaio clínico randomizado cruzado. A resposta hemodinâmica à estimulação elétrica unilateral direita do nervo acessório com 10 Hz foi medida pela espectroscopia funcional por um sistema de 40 canais. A variação de HbO nas áreas corticais de interesse mostrou ativação do DLPFC direito (p=0,025) e do MOTOR esquerdo (p=0,042) no grupo ativo comparado com sham. Em relação ao DLPFC esquerdo (p=0,610) e ao MOTOR direito (p=0,154), não houve diferença estatística entre os grupos. Como na modulação top-down, a estimulação bottom-up do nervo acessório parece ativar as mesmas áreas corticais, relacionadas às dimensões sensório-discriminativas e afetivo-motivacionais da dor. Esses resultados fornecem evidência adicional para desenvolver e otimizar o uso clínico da estimulação elétrica periférica. / Peripheral electrical stimulation (PES), which encompasses several techniques with heterogeneous physiological responses, has shown in some cases remarkable outcomes for pain treatment and clinical rehabilitation. However, results are still mixed, mainly because there is a lack of understanding regarding its neural mechanisms of action. In this study, we aimed to assess its effects by measuring cortical activation as indexed by functional near infrared spectroscopy (fNIRS). fNIRS is a functional optical imaging method to evaluate hemodynamic changes in oxygenated (HbO) and de-oxygenated (HbR) blood hemoglobin concentrations in cortical capillary networks that can be related to cortical activity. We hypothesized that PES of accessory spinal nerve (ASN) can promote cortical activation of motor cortex (MC) and dorsolateral prefrontal cortex (DLPFC) pain processing cortical areas. Fifteen healthy volunteers received both active and sham ASN electrical stimulation in a crossover design. The hemodynamic response to unilateral right ASN burst electrical stimulation with 10 Hz was measured by a 40- channel fNIRS system. The effect of ASN electrical stimulation over HbO concentration in cortical areas of interest was observed through the activation of right- DLPFC (p=0.025) and left-MOTOR (p=0.042) in the active group but not in sham group. Regarding left-DLPFC (p=0.610) and right-MOTOR (p=0.174) there was no statistical difference between groups. As in non-invasive brain stimulation (NIBS) topdown modulation, bottom-up electrical stimulation to the accessory spinal nerve seems to activate the same critical cortical areas on pain pathways related to sensorydiscriminative and affective-motivational pain dimensions. These results provide additional mechanistic evidence to develop and optimize the effects of peripheral neural electrical stimulation.

<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>