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In this paper, aiming to estimate force/torque information from brain activity to help and support the daily lives of human beings, we estimate the human muscular activity from EEG (Electroencephalogram) by PCA (Principal Component Analysis) and RLS (Recursive Least Squares). EEG and EMG (Electromyogram) are measured when a subject is flexing and extending his arm, and their linear model is established by PCA. Then, this linear model between EEG and EMG is updated by the angle, the angular velocity and the angular acceleration of the robot arm. Finally, EMG is estimated from EEG using the updated model. The results show that the estimation of EMG from EEG is possible, and using EEG support human's activities has a great potential.

In view of the existing verification methods of electric meters, there are problems such as high maintenance cost, poor accuracy, and difficulty in full coverage, etc. Starting from the perspective of analyzing the large-scale measured data collected by user-side electric meters, an online estimation method for the operating error of electric meters was proposed, which uses the recursive least squares (RLS) and introduces a double-parameter method with dynamic forgetting factors λa and λb to track the meter parameters changes in real time. Firstly, the obtained measured data are preprocessed, and the abnormal data such as null data and light load data are eliminated by an appropriate clustering method, so as to screen out the measured data of the similar operational states of each user. Then equations relating the head electric meter in the substation and each users’ electric meter and line loss based on the law of conservation of electric energy are established. Afterwards, the recursive least squares algorithm with double-parameter is used to estimate the parameters of line loss and the electric meter error. Finally, the effects of double dynamic forgetting factors, double constant forgetting factors and single forgetting factor on the accuracy of estimated error of electric meter are discussed. Through the program-controlled load simulation system, the proposed method is verified with higher accuracy and practicality.

Insomnia and excessive sleepiness are among the most commonly reported sleep problems related to shift work. Sleep-related movement disorders have, however, received far less attention in relation to such work schedules. The objective of this study was to investigate the association between different shift work schedules and the prevalence of Restless legs syndrome/Willis-Ekbom disease (RLS/WED) in a large sample of Norwegian nurses. Our hypothesis was that shift working nurses would report higher prevalence of RLS/WED compared to day workers. A total of 1,788 nurses with different work schedules (day work, two-shift rotation, night work, three shift rotation) participated in a cohort study, started in 2008/2009. Four questions about RLS/WED based on the diagnostic criteria were included in wave 4 (2012). RLS/WED prevalence rates across different shift schedules were explored by the Pearson chi-square test. Logistic regression analysis was used to assess the association between RLS/WED and work schedules and shift work disorder (SWD) with adjustment for sex, age, marital status, smoking, and caffeine use. In total, 90.0% of the nurses were females, mean age 36.5 years (SD = 8.6, range 25-67). The overall prevalence of RLS/WED was 26.8%. We found no significant differences between the prevalence of RLS/WED across the different shift schedules, ranging from 23.3% (day work) to 29.4% (night work). There was a significant difference (p < 0.001) in the prevalence of RLS/WED between nurses having SWD (33.5%) compared to nurses not having SWD (23.8%). SWD remained significantly associated with RLS/WED in the adjusted logistic regression analysis (1.56, CI: 1.24-1.97). This study did not support the hypothesis. RLS/WED was associated with SWD, which might indicate that nurses vulnerable to shift work also are sensitive to other complaints related to a misalignment of the biological clock. [ABSTRACT FROM AUTHOR]

The recursive least squares algorithm (RLS) using dichotomous coordinate descent (DCD) iterations, namely, RLS-DCD, is regarded to be well suited for hardware implementation because of its small computational complexity compared to the classical RLS algorithm. While this is true, yet another important aspect that ultimately determines its applicability for real-time applications with high sample rates, is its iteration bound. In this brief, we discuss this issue and propose a modified RLS-DCD algorithm based on delay relaxation whose iteration bound can be reduced arbitrarily. The degradation in convergence speed is shown to be tolerable, which results in still much faster convergence compared to the normalized least mean square algorithm. [ABSTRACT FROM PUBLISHER]

A quadrature rule based on Legendre polynomial functions is proposed to find approximate values of denite integrals in this paper. This method uses recursive least squares (RLS) algorithm to compute coefficients of Legendre polynomial fitting functions, and then approximately computes values of definite integrals by using obtained the coefficients. The main advantage of this approach is its efficiency and simple applicability. Finally some examples are given to test the convergence and accuracy of the method. [ABSTRACT FROM AUTHOR]

In this paper, we have experimentally demonstrated faster-than-Nyquist carrierless amplitude and phase modulation quadrature phase-shift keying visible light communication system over 1.5-m free space transmission. Weighted look-up table is used to mitigate nonlinear impairment caused by amplifiers and electro-optical components. At the receiver side, recursive least square is employed to improve the decision precision. By combining these techniques, a data rate of 1.01 Gb/s is experimentally achieved with a bit error rate less than 7% forward error correction limit of 3.8 x 10-3. To the best of our knowledge, this is the first time that weighted look-up table is proposed and used in visible light communication system. [ABSTRACT FROM AUTHOR]

In this paper, we present versatile nonlinear equalizer based on support vector machine for a standard downlink LTE link. The nonlinear effects are introduced through a solid state power amplifier. The equalizer is compared with a linear RLS and nonlinear Wiener-Hammerstein (W-H) for 16QAM-MIMO-OFDM transmission, revealing improved performance at 1 Mb/s, by 3 and 2 dB in SNR, respectively, when targeting a EVM (dB) of −60 dB. SVM equalization also outperforms the Wiener-Hammerstein by 1 dB in SNR. [ABSTRACT FROM AUTHOR]

This work aims to enhance the filtering performance of the recursive least-squares adaptive algorithm in the ultrasonic testing of materials by processing the primary input of the filter to improve the correlation properties of the signal and noise and enhance the adaptation and filtering process. The preprocessing is carried out using the SURE and universal threshold methods, which were originally used in wavelet denoising. The standard and proposed realisations of the recursive least-squares filter were applied to process simulated ultrasonic grain noise signals and the echo signals of experimental defects. Preprocessing using the SURE method did not offer good results in the simulation study. The results of the simulation and experimental studies showed that the proposed configuration of the recursive least-squares filter using the universal method performs better than the standard recursive least-squares filter. [ABSTRACT FROM AUTHOR]

Techniques for hypothesis testing can be used to solve a broad class of nonstationarity detection problems, which is a key issue in a variety of applications. To achieve lower complexity and to deal with real-time detection in practical applications, we develop a new adaptive nonstationarity detector by exploiting a parametric model. A weighted maximum a posteriori (MAP) estimator is developed to estimate the parameters associated with the parametric model. We then derive a regularized Wald test from the weighted MAP estimate, which is adaptively implemented by a regularized recursive least squares (RLS) algorithm. Several important issues are discussed, including model order selection, forgetting factor and regularization parameter selection for RLS, and numerically stable implementation using QR decomposition, which are intrinsic parts of the proposed parametric adaptive detector. Simulation results are presented to illustrate the efficiency of the proposed nonstationarity detector, with adaptive estimation and automatic model selection, especially for “slowly varying” type of nonstationarity such as time-varying spectrums and speeches. [ABSTRACT FROM PUBLISHER]

This paper reviews the past and the recent research on Adaptive Filter algorithms based on adaptive noise cancellation systems. In many applications of noise cancellation, the change in signal characteristics could be quite fast which requires the utilization of adaptive algorithms that converge rapidly. Algorithms such as LMS and RLS proves to be vital in the noise cancellation are reviewed including principle and recent modifications to increase the convergence rate and reduce the computational complexity for future implementation. The purpose of this paper is not only to discuss various noise cancellation LMS algorithms but also to provide the reader with an overview of the research conducted. [ABSTRACT FROM AUTHOR]

While inter-symbol interference is not of concern, inter-carrier interference that is caused by carrier frequency offset (CFO) is more concerned in orthogonal frequency division multiplexing (OFDM) systems. The estimation of channel impulse response (CIR) is another important parameter of interest in the system. Recently, a number of approaches for the joint estimation of CFO and CIR in OFDM systems have been proposed in the literature, and most of them are traditional maximum-likelihood-based approaches. In this paper, we propose a number of mixture cost-reference particle filtering (CRPF) approaches for joint estimation of CIR and CFO, and a couple of them can be applied without the knowledge of both state and measurement noise statistics. Conventional least mean squares algorithm or recursive least squares algorithm is jointly employed with recently developed CRPF for nonlinear and multiple parameters estimation in OFDM systems. The computer simulation results show that mixture CRPFs are more robust against particle impoverishment (PI) problem than standard mixture particle filtering (PF) and mixture regularized PF (RPF) approaches although RPF was particularly developed to tackle the PI problem. In this paper, we investigate a number of mixture PF approaches including ones that do not need the information of noise statistics for the joint estimation of CFO and channel in OFDM systems. [ABSTRACT FROM PUBLISHER]

In this paper, the fault detection of a latent fault in a sensor for a Markov jump system is studied. It is equivalent to detecting a change point in a coefficient vector of a measurement equation in the state space representation of a system. Indeed, the fault detection procedure is evaluated as detecting this change point and the time that the change point has occurred. To this end, first, the recursive least square (RLS) filter is proposed and under Yao's Prior setting, the Bayesian fault detection algorithm is proposed. The Smith-Gelfand re-sampling method is applied to approximate the posterior distribution. The performance of the Bayesian method is studied under the null and alternative hypotheses. The delay in diagnosis of the fault is measured. To study the effect of the fault time point in the performance of the Bayesian method, the sensitivity analysis is studied. The probability of the fault is studied and the Martingale approach is used to obtain the lower and upper bounds for this probability. The fault detection in integrated systems is studied and a Kalman filter, as a parallel filter, is considered to estimate the state and the effect of the unknown coefficient jump on state estimation is also studied. [ABSTRACT FROM AUTHOR]

Objectives: Perampanel is a selective, noncompetitive α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPA) antagonist that has been approved for the treatment of partial seizures. Here we report on the first open study evaluating its efficacy in idiopathic restless legs syndrome (RLS).Methods: The study was designed as a prospective two-month open trial. Twenty-two previously untreated patients diagnosed with idiopathic RLS began treatment with 2 mg perampanel, which was increased to 4 mg at week four if clinically necessary. Multiple Suggested Immobilization Tests (mSITs) followed by polysomnography were performed at baseline and at week eight. Severity ratings were performed every two weeks by means of the IRLS scale, and Clinical Global Index (CGI) subscale. The main endpoint was therapeutic response, defined as a 50% improvement in IRLS total score.Results: Twenty patients completed the study. During the 8-week treatment period, the IRLS score improved from a mean (±standard deviation (SD)) 23.7 ± 4.2 to 11.5 ± 5.3. Twelve of 20 patients were full responders (improvement 50% in IRLS total score), and four responded partially. The mean effective dose of perampanel at the end of treatment was 3.8 mg/day. Treatment with perampanel also resulted in an improvement in the mean (±SD) periodic leg movement index from 27.8 ± 6.9 to 4.36 ± 2.0. Perampanel was well tolerated. The main side effects were dizziness, somnolence, headache, and irritability.Conclusion: These preliminary results suggest that perampanel has significant therapeutic effects on both sensory and motor symptoms. If confirmed by future controlled studies, perampanel might become a promising alternative to existing dopaminergic treatments due to its glutamatergic mechanism of action. The study provides class IV evidence supporting the therapeutic effects of perampanel in RLS/WED. [ABSTRACT FROM AUTHOR]

Restless legs syndrome is a frequent neurological disorder with potentially serious and highly distressing treatment complications. The role and potential implications of periodic leg movements during sleep range from being a genetic risk marker for restless legs syndrome to being a cardiovascular risk factor. The diagnosis of restless legs syndrome in patients with daytime movement disorders is challenging and restless legs syndrome needs to be differentiated from other sleep-related movement disorders. This article provides an update on the diagnosis of restless legs syndrome as an independent disorder and the role of periodic leg movements and reviews the association of restless legs syndrome with Parkinson's disease and other movement disorders. © 2017 International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

At the outset of genetic studies in restless legs syndrome (RLS), the disorder was assumed to be a classical monogenic disorder that runs in families. However, years of family studies did not reveal any causally-related genes or genetic variants. The advent of high-throughput genotyping technology led to a change; genome-wide association studies in large case-control samples became feasible, which led to the identification of first genetic risk variants for RLS. Variants detected by this approach are common ones, which that individually confer only a minor increase in risk of disease. Overall, the currently known risk variants in six genomic loci account for only a small proportion of the genetically determined susceptibility to RLS. Additional risk loci and individual variants remain to be discovered. First studies indicate that rare genetic variants are also important contributors in RLS. These are expected to have a larger impact on the phenotype and may thus prove to be excellent candidates for functional studies and, in the long-term, targets for developing therapeutics or preventive measures. To enable their discovery, large-scale studies including tens of thousands of affected individuals may be needed. Next-generation sequencing technologies such as whole exome or whole genome sequencing will be essential for this endeavor. Even though the number of known risk variants is still limited, they have been indispensable in terms of deciphering the underlying pathophysiology of RLS, providing the molecular starting points for animal models and in vitro studies to understand disease mechanisms. In addition, genetic risk variants can be valuable tools for disentangling the phenotypic complexity observed in RLS. Testing RLS risk variants for associations with periodic limb movements (PLMs) identified a significant role of some of the variants and suggested PLMs as an endophenotype in RLS. Further advances in genetics research in RLS will be driven by large-scale sequencing projects and the identification of additional common, but also rarer risk variants with larger effects on disease risk. Another uncharted territory in RLS research epigenetic effect on gene activity. Overall, genetic studies continue to hold great potential for understanding biology of the disease. [ABSTRACT FROM AUTHOR]

In this article, we review the original findings from MRI and autopsy studies that demonstrated brain iron status is insufficient in individuals with restless legs syndrome (RLS). The concept of deficient brain iron status is supported by proteomic studies from cerebrospinal fluid (CSF) and from the clinical findings where intervention with iron, either dietary or intravenous, can improve RLS symptoms. Therefore, we include a section on peripheral iron status and how peripheral status may influence both the RLS symptoms and treatment strategy. Given the impact of iron in RLS, we have evaluated genetic data to determine if genes are directly involved in iron regulatory pathways. The result was negative. In fact, even the HFE mutation C282Y could not be shown to have a protective effect. Lastly, a consistent finding in conditions of low iron is increased expression of proteins in the hypoxia pathway. Although there is lack of clinical data that RLS patients are hypoxic, there are intriguing observations that environmental hypoxic conditions worsen RLS symptoms; in this chapter we review very compelling data for activation of hypoxic pathways in the brain in RLS patients. In general, the data in RLS point to a pathophysiology that involves decreased acquisition of iron by cells in the brain. Whether the decreased ability is genetically driven, activation of pathways (eg, hypoxia) that are designed to limit cellular uptake is unknown at this time; however, the data strongly support a functional rather than structural defect in RLS, suggesting that an effective treatment is possible. [ABSTRACT FROM AUTHOR]

Objectives:  The current study aimed to search the prevalence and severity of restless legs syndrome (RLS) in pregnancy according to the three trimesters and predictive factors of RLS in pregnancy based on validated diagnostic tools and a thorough literature review., Methods: The cross-sectional descriptive study included 500 pregnant women without comorbidities who were interviewed face-to-face. Age, height, weight, week of pregnancy, smoking, alcohol, caffeine use, regular exercise, and lab test results from the last visit were all included in the data. Only women satisfying the RLS diagnostic criteria were given the Restless Legs Syndrome Rating Scale., Results: The prevalence of RLS was found to be 29.2% with the highest rate in the third trimester (64.4%). In all trimesters, low ferritin (first trimester: p = 0.004; second trimester: p < 0.001; third trimester: p < 0.001), folic acid (first trimester: p = 0.001; second trimester: p < 0.001; third trimester: p < 0.001), vitamin B12 (first trimester: p = 0.003; second trimester: p < 0.001; third trimester: p < 0.001), and hemoglobin (first trimester: p < 0.001; second trimester: p < 0.001; third trimester: p < 0.001) levels were associated with RLS. In the second and third trimesters, low magnesium (p < 0.001 and p < 0.001, respectively) and high creatinine (p = 0.027 and p < 0.001, respectively) levels were associated with RLS. Higher thyroid-stimulating hormone and free T4 levels were associated with RLS in the third trimester but not in the first and second trimesters (median: 2.4 vs. 2.1, p < 0.001; median: 1.5 vs. 1.2, p < 0.001). In the multivariate regression analysis, age (p = 0.034, OR: 1.060, 95% CI: 1.005-1.119), present BMI (p < 0.001, OR: 1.8884, 95% CI: 1.597-2.222), BMI before conception (p < 0.001, OR: 0.607, 95% CI: 0.513-0.718), gravida (p < 0.001, OR: 2.172, 95% CI: 1.547-3.049), low ferritin level (p < 0.001, OR: 6.396, 95% CI: 0.00744-0.010405), low vitamin B12 (p < 0.001, OR: 10.347, 95% CI: 0.00120-0.00176), low folate (p < 0.001, OR: 5.841, 95% CI: 0.00616-0.01240), RLS history before conception (p = 0.013, OR: 4.963, 95% CI: 1.402-17.57), and RLS family history (p < 0.001, OR: 7.914, 95% CI: 0.18760-0.31151) were found to be predictive factors for RLS in pregnancy., Conclusion: More attention is needed to RLS during pregnancy to prevent or treat this syndrome., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2023, Turan et al.)

The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust at high speed mobility.

In this paper, a variable step size based least mean squares (LMS) channel estimation (CE) algorithm is presented for a single carrier frequency division multiple access(SC-FDMA) system under the umbrella of the long term evolution (LTE). This unbiased CE method can automatically adapts the weighting coefficients on the channel condition. Therefore, it does not require knowledge of channel,and noise statistics. Furthermore, it uses a phase weighting scheme to eliminate the signal fluctuations due to noise and decision errors. Such approaches can guarantee the convergence towards the true channel coefficient. The mean and mean square behaviors of the proposed CE algorithm are also analyzed. With the help of theoretical analysis and simulation results, we prove that the proposed algorithm outperforms the existing algorithms in terms of mean square error (MSE) and bit error rate (BER) by more than around 2.5dB.

Data collected from medical literature indicate that dopaminergic agonists alleviate Restless Legs Syndrome symptoms while dopaminergic agonists antagonists aggravate them. Dopaminergic agonists is a physiological regulator of thyroid-stimulating hormone. Dopaminergic agonists infusion diminishes the levels of thyroid hormones, which have the ability to provoke restlessness, hyperkinetic states, tremors, and insomnia. Conditions associated with higher levels of thyroid hormones, such as pregnancy or hyperthyroidism, have a higher prevalence of Restless Legs Syndrome symptoms. Low iron levels can cause secondary Restless Legs Syndrome or aggravate symptoms of primary disease as well as diminish enzymatic activities that are involved in dopaminergic agonists production and the degradation of thyroid hormones. Moreover, as a result of low iron levels, dopaminergic agonists diminishes and thyroid hormones increase. Iron therapy improves Restless Legs Syndrome symptoms in iron deprived patients. Medical hypothesis. To discuss the theory that thyroid hormones, when not counterbalanced by dopaminergic agonists, may precipitate the signs and symptoms underpinning Restless Legs Syndrome. The main cause of Restless Legs Syndrome might be an imbalance between the dopaminergic agonists system and thyroid hormones.

Background: Restless leg syndrome (RLS) is a sensory-motor disorder that affects 6-83% of dialysis patients. Increased Urea and creatinine, and Iron deficiency anemia resulting from renal failure are some causes of restless leg syndrome. This study was aimed to evaluate this issue. Methods: A cross sectional study was done on 130 dialysis patients in 5 dialysis centers of Bushehr Province. The diagnosis of RLS was made using the criteria of the International Restless Leg syndrome. The length of renal failure, number of weekly dialysis, erythropoietin dose per week, dose of mineral Iron per day, other co morbidities and medications, ferritin level, and predialysis BUN were determined. Results: In this study 43 (33.1%) patients had restless leg syndrome who consisted of 18 (41.9%) women and 25 (58.1%) men. Positive family history was significantly associated with restless leg syndrome (p

Restless legs syndrome (RLS) affects 2% of children presenting with symptoms of insomnia, restless sleep, decreased quality of life, and effects on cognition and behavior. The International RLS Study Group and the American Academy of Sleep Medicine have published guidelines for the diagnosis and treatment of RLS in children. Restless sleep disorder has been recently identified in children and presents with frequent movements during sleep and daytime symptoms with polysomnography findings of at least 5 large muscle movements at night. Treatment options for both disorders include iron supplementation, either oral or intravenous with improvement in nighttime and daytime symptoms., (Copyright © 2023. Published by Elsevier Inc.)

Restless Legs Syndrome (RLS) is a common sensorimotor and a sleep disorder that affects 2.5-10% of the European and North American populations. RLS is also often associated with periodic leg movements during sleep (PLMS). Despite ample evidence of genetic contributions, the underlying mechanisms that elicit the sensory and motor symptoms remain unidentified. Clinically, RLS has been correlated with an altered central iron metabolism, particularly in the brain. While several animal models have been developed to determine the outcome of an altered iron homeostasis on brain function, the potential role of an altered iron homeostasis on sleep and sensorimotor circuits has not yet been investigated. Here, we utilize a mouse model to assess the effects of an iron-deficient (ID) but non-anemic state on sleep time and episodes, and sensorimotor reflexes in male and female mice. We found that animals on the ID diet displayed an increased expression of the transferrin receptor in the spinal cord, confirming the results of previous studies that focused only on the impact of ID in the brain. We also demonstrate that the ID diet reduced hematocrit levels compared to controls but not into the anemic range, and that animals on the ID diet exhibited RLS-like symptoms with regard to sleep onset and spinal cord reflex excitability. Interestingly, the effects on the spinal cord were stronger in females than in males, and the ID diet-induced behaviors were rescued by the return of the animals to the control diet. Taken together, these results demonstrate that diet-induced ID changes to CNS function are both inducible and reversible, and that they mimic the sleep and sensorimotor RLS symptoms experienced in the clinic. We therefore propose replacing the commonly used phrase "brain iron deficiency" (BID) hypothesis in the RLS research field with the term "iron deficiency in the central nervous system" (ID-CNS), to include possible effects of altered iron levels on spinal cord function., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Woods, Basco and Clemens.)

En este trabajo se describen brevemente los sistemas de antenas inteligentes. Se presentan algunos algoritmos adaptativos que hacen que el sistema sea inteligente. Los algoritmos que se presentan son LMS y el RLS y serán sometidos a un análisis matemático para su posterior simulación vía MatLab. Éstos se escogen por su relación con un algoritmo híbrido desarrollado. Cada algoritmo será evaluado respecto a diferentes parámetros tales como convergencia, rapidez, estabilidad, etcThis paper briefly describes intelligent antenna systems. Some adaptive algorithms that render the system intelligent are presented. LMS and RLS algorithms are introduced and subject to mathematical analysis in order to allow simulation by using MatLab. The algorithms are chosen according to their relationship with the hybrid algorithm developed by the authors. Each algorithm is evaluated with reference to parameters such as convergence, speed, stability, etc

This paper considers the application of the linear constraints and RLS inverse QR decomposition in adaptive arrays based on constant modulus criterion. The computational procedures of adaptive algorithms are presented. Linearly constrained least squares adaptive arrays, constant modulus adaptive arrays and linearly constrained constant modulus adaptive arrays are compared via simulation. It is demonstrated, that a constant phase shift in the array output signal, caused by desired signal orientation and array weights, is compensated in a simple way in linearly constrained constant modulus adaptive arrays.

BACKGROUND & PURPOSE: The association of obstructive sleep apnea syndrome (OSAS) and restless legs syndrome (RLS) has been reported in the literature for many years. Both conditions may be responsible for fatigue and somnolence complaints secondary to nocturnal sleep disruption. The primary concern of this study is to evaluate the outcome of fatigue and daytime sleepiness symptoms at baseline and after continuous positive air pressure (CPAP) treatment in OSAS patients with and without RLS. METHOD: A prospective and comparative study between a group of 13 patients with OSAS and a group of 17 patients with OSAS+RLS. Laboratory blood tests and polysomnography were performed at baseline. The Epworth Sleepiness Scale (ESS) and the Pichot’s questionnaire of fatigue/depression (PIC) were applied before and after 3 months of CPAP treatment. Results were compared. RESULTS: No significant differences were found on PSG and laboratory results at baseline. Both groups had similar ESS and PIC scores at baseline (p=0.73 and 0.08, respectively). After n-CPAP, OSAS+RLS patients showed higher ESS and PIC scores (p=0.017 and 0.03, respectively). CONCLUSIONS: Despite a favorable general response, n-CPAP seemed less effective in treating fatigue and sleepiness in the OSAS+RLS group.OBJETIVO: A associação síndrome de apnéia obstrutiva do sono / síndrome de pernas inquietas (SAOS-SPI) tem sido mencionada na literatura há muito. Ambas podem ser responsáveis por queixas de fadiga e sonolência secundárias à fragmentação do sono noturno. O objetivo deste estudo é avaliar a evolução dos sintomas de fadiga e sonolência diurna excessiva antes e após o tratamento com pressão aérea positiva contínua (CPAP) em pacientes portadores de SAOS, com e sem SPI. MÉTODO: Estudo prospectivo e comparativo entre um grupo de 13 pacientes com SAOS e um grupo de 17 com SAOS +SPI. Exames laboratoriais e polissonografia (PSG) foram realizados no início do estudo. A escala de sonolência de Epworth (ESE) e o questionário de fadiga/depressão de Pichot (PIC) foram aplicados antes do tratamento com CPAP e 3 meses após. Os resultados foram comparados. RESULTADOS: No início do estudo não foram encontradas diferenças significativas na avaliação laboratorial e PSG. Ambos os grupos apresentavam inicialmente pontuação semelhante na avaliação da ESE e PIC (p=0,73 e 0,08, respectivamente). Após CPAP, os pacientes SAOS+SPI apresentaram maiores ESE e PIC (p=0,017 e 0,03, respectivamente). CONCLUSÃO: Apesar de resposta inicial favorável em ambos os grupos, o CPAP foi aparentemente menos eficaz na redução das queixas de fadiga e sonolência nos pacientes apnéicos com associação a SPI.

In order to improve the reconnaissance efficiency of unmanned aerial vehicle (UAV) electro-optical stabilized imaging systems, a real-time multi-target localization scheme based on an UAV electro-optical stabilized imaging system is proposed. First, a target location model is studied. Then, the geodetic coordinates of multi-targets are calculated using the homogeneous coordinate transformation. On the basis of this, two methods which can improve the accuracy of the multi-target localization are proposed: (1) the real-time zoom lens distortion correction method; (2) a recursive least squares (RLS) filtering method based on UAV dead reckoning. The multi-target localization error model is established using Monte Carlo theory. In an actual flight, the UAV flight altitude is 1140 m. The multi-target localization results are within the range of allowable error. After we use a lens distortion correction method in a single image, the circular error probability (CEP) of the multi-target localization is reduced by 7%, and 50 targets can be located at the same time. The RLS algorithm can adaptively estimate the location data based on multiple images. Compared with multi-target localization based on a single image, CEP of the multi-target localization using RLS is reduced by 25%. The proposed method can be implemented on a small circuit board to operate in real time. This research is expected to significantly benefit small UAVs which need multi-target geo-location functions. [ABSTRACT FROM AUTHOR]