Spectral characteristics of subthalamic nucleus local field potentials in Parkinson's disease: Phenotype and movement matter.

Parkinson's disease (PD) is clinically heterogeneous across patients and may be classified in three motor phenotypes: tremor dominant (TD), postural instability and gait disorder (PIGD), and undetermined. Despite the significant clinical characterization of motor phenotypes, little is known about how electrophysiological data, particularly subthalamic nucleus local field potentials (STN-LFP), differ between TD and PIGD patients. This is relevant since increased STN-LFP bandpower at α-ß range (8-35 Hz) is considered a potential PD biomarker and, therefore, a critical setpoint to drive adaptive deep brain stimulation. Acknowledging STN-LFP differences between phenotypes, mainly in rest and movement states, would better fit DBS to clinical and motor demands. We studied this issue through spectral analyses on 35 STN-LFP in TD and PIGD patients during rest and movement. We demonstrated that higher ß2 activity (22-35 Hz) was observed in PIGD only during rest. Additionally, bandpower differences between rest and movement occurred at the α-ß range, but with different patterns as per phenotypes: movement-induced desynchronization concerned lower frequencies in TD (10-20 Hz) and higher frequencies in PIGD patients (21-28 Hz). Finally, when supervised learning algorithms were employed aiming to discriminate PD phenotypes based on STN-LFP bandpower features, movement information had improved the classification accuracy, achieving peak performances when TD and PIGD movement-induced desynchronization ranges were considered. These results suggest that STN-LFP ß-band encodes phenotype-movement dependent information in PD patients.

Unsupervised Classification of Atrial Electrograms for Electroanatomic Mapping of Human Persistent Atrial Fibrillation.

OBJECTIVE: Ablation treatment for persistent atrial fibrillation (persAF) remains challenging due to the absence of a 'ground truth' for atrial substrate characterization and the presence of multiple mechanisms driving the arrhythmia. We implemented an unsupervised classification to identify clusters of atrial electrograms (AEGs) with similar patterns, which were then validated by AEG-derived markers. METHODS: 956 bipolar AEGs were collected from 11 persAF patients. CARTO variables (Biosense Webster; ICL, ACI and SCI) were used to create a 3D space, and subsequently used to perform an unsupervised classification with k-means. The characteristics of the identified groups were investigated using nine AEG-derived markers: sample entropy (SampEn), dominant frequency, organization index (OI), determinism, laminarity, recurrence rate (RR), peak-to-peak (PP) amplitude, cycle length (CL), and wave similarity (WS). RESULTS: Five AEG classes with distinct characteristics were identified (F = 582, P<0.0001). The presence of fractionation increased from class 1 to 5, as reflected by the nine markers. Class 1 (25%) included organized AEGs with high WS, determinism, laminarity, and RR, and low SampEn. Class 5 (20%) comprised fractionated AEGs with in low WS, OI, determinism, laminarity, and RR, and in high SampEn. Classes 2 (12%), 3 (13%) and 4 (30%) suggested different degrees of AEG organization. CONCLUSIONS: Our results expand and reinterpret the criteria used for automated AEG classification. The nine markers highlighted electrophysiological differences among the five classes found by the k-means, which could provide a more complete characterization of persAF substrate during ablation target identification in future clinical studies.

Dynamic repair priority rule based on remaining useful life predictions.

In this paper, we propose a novel repair priority rule for spare parts in a repair station with limited repair capacity to minimize total inventory cost per time unit. Inventory cost is composed of holding costs and backorder costs. The proposed rule uses Remaining Useful Life (RUL) predictions of functioning machines obtained from a Prognostics and Health Monitoring (PHM) system. An inventory system comprising a finite number of machines, one warehouse, and one single-server repair station is considered. Numerical experiments were conducted to compare the performance of the proposed model with the performance of three existing priority rules: a first-come, first-served (FCFS) rule, a static priority rule, and a dynamic priority rule. A testbed with 20 instances of the problem was considered. The results showed that the proposed PHM-based rule consistently reduces the inventory system cost.

Recurrence Quantification Analysis for Investigating Atrial Fibrillation Dynamics in a Heterogeneous Simulation Setup.

The outcomes of ablation targeting either reentry activations or fractionated activity during persistent atrial fibrillation (AF) therapy remain suboptimal due to, among others, the intricate underlying AF dynamics. In the present work, we sought to investigate such AF dynamics in a heterogeneous simulation setup using recurrence quantification analysis (RQA). AF was simulated in a spherical model of the left atrium, from which 412 unipolar atrial electrograms (AEGs) were extracted (2 s duration; 5 mm spacing). The phase was calculated using the Hilbert transform, followed by the identification of points of singularity (PS). Three regions were defined according to the occurrence of PSs: 1) no rotors; 2) transient rotors and; 3) long-standing rotors. Bipolar AEGs (1114) were calculated from pairs of unipolar nodes and bandpass filtered (30-300 Hz). The CARTO criterion (Biosense Webster) was used for AEGs classification (normal vs. fractionated). RQA attributes were calculated from the filtered bipolar AEGs: determinism (DET); recurrence rate (RR); laminarity (LAM). Sample entropy (SampEn) and dominant frequency (DF) were also calculated from the AEGs. Regions with longstanding rotors have shown significantly lower RQA attributes and SampEn when compared to the other regions, suggesting a higher irregular behaviour (P≤0.01 for all cases). Normal and fractionated AEGs were found in all regions (respectively; Region 1: 387 vs. 15; Region 2: 221 vs. 13; Region 3: 415 vs. 63). Region 1 vs. Region 3 have shown significant differences in normal AEGs (P≤0.0001 for all RQA attributes and SampEn), and significant differences in fractionated AEGs for LAM, RR and SampEn (P=0.0071, P=0.0221 and P=0.0086, respectively). Our results suggest the co-existence of normal and fractionated AEGs within long-standing rotors. RQA has unveiled distinct dynamic patterns-irrespective of AEGs classification-related to regularity structures and their nonstationary behaviour in a rigorous deterministic context.

Parameter estimation of an artificial respiratory system under mechanical ventilation following a noisy regime

Abstract Introduction: This work concerns the assessment of a novel system for mechanical ventilation and a parameter estimation method in a bench test. The tested system was based on a commercial mechanical ventilator and a personal computer. A computational routine was developed do drive the mechanical ventilator and a parameter estimation method was utilized to estimate positive end-expiratory pressure, resistance and compliance of the artificial respiratory system. Methods The computational routine was responsible for establishing connections between devices and controlling them. Parameters such as tidal volume, respiratory rate and others can be set for standard and noisy ventilation regimes. Ventilation tests were performed directly varying parameters in the system. Readings from a calibrated measuring device were the basis for analysis. Adopting a first-order linear model, the parameters could be estimated and the outcomes statistically analysed. Results Data acquisition was effective in terms of sample frequency and low noise content. After filtering, cycle detection and estimation took place. Statistics of median, mean and standard deviation were calculated, showing consistent matching with adjusted values. Changes in positive end-expiratory pressure statistically imply changes in compliance, but not the opposite. Conclusion The developed system was satisfactory in terms of clinical parameters. Statistics exhibited consistent relations between adjusted and estimated values, besides precision of the measurements. The system is expected to be used in animals, with a view to better understand the benefits of noisy ventilation, by evaluating the estimated parameters and performing cross relations among blood gas, ultrasonography and electrical impedance tomography.

State estimation and optimal long period clinical treatment of HIV seropositive patients.

Optimal control theory provides a very interesting quantitative method that can be used to assist the decision making process in several areas of application, such as engineering, biology, economics and sociology. The main idea is to determine the values of the manipulated variables, such as drug doses, so that some cost function is minimized, subject to physical constraints. In this work, the cost function reflects the number of CD4+T cells, viral particles and the drug doses. It is worth noticing that high drug doses are related to more intense side-effects, apart from the impact on the actual cost of the treatment. In a previous paper by the authors, the LQR - Linear Quadratic Regulator approach was proposed for the computation of long period maintenance doses for the drugs, which turns out to be of state feedback form. However, it is not practical to determine all the components of the state vector, due to the fact that infected and uninfected CD4+T cells are not microscopically distinguishable. In order to overcome this difficulty, this work proposes the use of Extended Kalman Filter to estimate the state, even though, because of the nonlinear nature of the involved state equations, the separation principle may not be valid. Extensive simulations were then carried out to investigate numerically if the control strategy consisting of the feedback of estimated states yielded satisfactory clinical results.

State estimation and optimal long period clinical treatment of HIV seropositive patients

Optimal control theory provides a very interesting quantitative method that can be used to assist the decision making process in several areas of application, such as engineering, biology, economics and sociology. The main idea is to determine the values of the manipulated variables, such as drug doses, so that some cost function is minimized, subject to physical constraints. In this work, the cost function reflects the number of CD4+T cells, viral particles and the drug doses. It is worth noticing that high drug doses are related to more intense side-effects, apart from the impact on the actual cost of the treatment. In a previous paper by the authors, the LQR - Linear Quadratic Regulator approach was proposed for the computation of long period maintenance doses for the drugs, which turns out to be of state feedback form. However, it is not practical to determine all the components of the state vector, due to the fact that infected and uninfected CD4+T cells are not microscopically distinguishable. In order to overcome this difficulty, this work proposes the use of Extended Kalman Filter to estimate the state, even though, because of the nonlinear nature of the involved state equations, the separation principle may not be valid. Extensive simulations were then carried out to investigate numerically if the control strategy consisting of the feedback of estimated states yielded satisfactory clinical results.

A teoria de controle ótimo apresenta um método quantitativo muito interessante que pode ajudar no processo de tomada de decisão em algumas áreas de aplicação, tais como engenharia, biologia, economia e sociologia. A principal idéia é determinar os valores das variáveis controladas, tais como doses de medicamentos, onde alguma função-custo é minimizada, sujeito às restrições físicas. Neste trabalho, a função-custo reflete o número de células CD4+T, partículas virais e doses de medicamentos. É fato que altas dosagens de medicamentos estão relacionadas à maior intensidade de efeitos colaterais, além do impacto no custo real do tratamento. Num prévio trabalho nosso, foi proposta a abordagem LQR - Regulador Linear Quadrático para o cálculo das doses de manutenção para os medicamentos, as quais dependiam de ser realimentadas pelo estado. Entretanto, a determinação de todos os componentes do vetor de estado não seria prática, devido ao fato de que células infectadas e não infectadas são indistingüíveis no microscópio. Para contornar essa dificuldade, este trabalho propõe o uso do Filtro de Kalman Estendido para estimar o estado, ainda que, devido à natureza não linear das equações de estado envolvidas, o princípio da separação não seja válido. Simulações extensivas foram realizadas para investigar numericamente se a estratégia de controle consistindo da realimentação de estados estimados produz resultados clínicos satisfatórios.

Pro-oxidative effect of alpha-tocopherol in the oxidation of LDL isolated from co-antioxidant-depleted non-diabetic hemodialysis patients.

The association between the antioxidants in LDL and the oxidizability of LDL assessed by the oxidation lag time during copper ion-catalyzed oxidation was investigated in 69 non-diabetic hemodialysis patients and 23 healthy volunteers. The concentrations of co-antioxidants, including ubiquinol-10, lycopene and beta-carotene, in LDL were significantly lower in the hemodialysis patients than in the healthy volunteers, while there was no difference in the alpha-tocopherol concentration between the groups. The lag time showed a significantly positive correlation with the alpha-tocopherol level (r = 0.62, P < 0.01) in the healthy subjects, but a significantly negative correlation (r = -0.38, P < 0.05) in the hemodialysis patients. Furthermore, in vitro incubation of LDL with alpha-tocopherol prolonged the lag time in the healthy subjects, but shortened it in the hemodialysis patients. These results suggested that the alpha-tocopherol might exert the pro-oxidative effect in co-antioxidant-depleted LDL that was isolated from the hemodialysis patients. Despite such co-antioxidant depletion and the pro-oxidative effect of alpha-tocopherol, the lag time in the hemodialysis patients was not statistically different from that in the healthy volunteers. This might have been because the polyunsaturated fatty acids concentration, another determinant of the lag time, in LDL was less in the hemodialysis patients than in the healthy controls.

A competitive wavelet network for signal clustering.

This correspondence proposes a novel signal clustering method based on the unsupervised training of a wavelet network. The synaptic weights are parameterized by wavelet basis functions, which are adjusted by a competitive algorithm that makes use of the neighborhood concept proposed by Kohonen. The robustness of the wavelet network with respect to noise is illustrated in a simulated problem, in which dynamic systems are grouped on the basis of their step responses. An example involving clustering of electrocardiographic signals taken from the MIT-BIH database is also presented. In this case, the ability of the proposed network to perform clustering at successive resolution levels is illustrated. The possibility of interpreting the information encoded in the network at the end of training is also discussed.

Short and long period optimization of drug doses in the treatment of AIDS.

Numerical optimization techniques are useful in solving problems of computing the best inputs for systems described by mathematical models and when the objectives can be stated in a quantitative form. This work concerns the problem of optimizing the drug doses in the treatment of AIDS in terms of achieving a balance between the therapeutic response and the side effects. A mathematical model describing the dynamics of HIV viruses and CD4 cells is used to compute the short term optimal drug doses in the treatments of patients with AIDS by a direct method of optimization using a cost function of Bolza type. The model parameters were fitted to actual published clinical data. In order to simplify the numerical procedures, the control law is expressed as a series and the sub-optimal control is obtained by truncating the higher terms. When the patient reaches a clinically satisfactory state, the LQR - Linear Quadratic Regulator technique is used to determine the long period maintenance doses for the drugs. The doses computed using the LQR technique tend to be smaller than equivalent constant-dose therapy in terms of increase in the counts of CD4+T cells and reduction of the density of free viruses.

Short and long period optimization of drug doses in the treatment of AIDS

Numerical optimization techniques are useful in solving problems of computing the best inputs for systems described by mathematical models and when the objectives can be stated in a quantitative form. This work concerns the problem of optimizing the drug doses in the treatment of AIDS in terms of achieving a balance between the therapeutic response and the side effects. A mathematical model describing the dynamics of HIV viruses and CD4 cells is used to compute the short term optimal drug doses in the treatments of patients with AIDS by a direct method of optimization using a cost function of Bolza type. The model parameters were fitted to actual published clinical data. In order to simplify the numerical procedures, the control law is expressed as a series and the sub-optimal control is obtained by truncating the higher terms. When the patient reaches a clinically satisfactory state, the LQR - Linear Quadratic Regulator technique is used to determine the long period maintenance doses for the drugs. The doses computed using the LQR technique tend to be smaller than equivalent constant-dose therapy in terms of increase in the counts of CD4+T cells and reduction of the density of free viruses

a neural network with asymmetric basis functions for feature extraction of ecg waves

Efficient and economical feature extraction schemes are of paramount importance in many pattern clustering or classification tasks. In the present work a simple neural network with asymmetric basis functions is proposed as a feature extractor for waves in electrocardiographic signals (ECG). The neural network is trained using the classical backwarderror-propagation algorithm. The performance of the proposed network was tested using actual ECG signals and compared with other types of neural feature extractors.

A comparative evaluation of open loop and closed loop drug administration strategies in the treatment of AIDS

In recent years, many researchers in the field of biomedical sciences have made successful use of mathematical models to study, in a quatitative way, a multitude of phenomena such as those found in disease dynamics, control of physiological systems, optimization of drug therapy, economics of the preventive medicine and many other applications. The availability of good dynamic models have been providing means for simulation and design of novel control strategies in the context of biological events. This work concerns a particular model related to HIV infection dynamics which is used to allow a comparative evaluation of schemes for treatment of AIDS patients. The mathematical model adopted in this work was proposed by Nowak & Bangham, 1996 and describes the dynamics of viral concentration in terms of interaction with CD4 cells and the cytotoxic T lymphocytes, which are responsible for the defense of the organism. Two conceptually distinct techniques for drug therapy are analyzed: Open Loop Treatment, where a priori fixed dosage is prescribed and Closed Loop Treatment, where the doses are adjusted according to results obtained by laboratory analysis. Simulation results show that the Closed Loop Scheme can achieve improved quality of the treatment in terms of reduction in the viral load and quatity of administered drugs, but with the inconvenience related to the necessity of frequent and periodic laboratory analysis.