Higuchi Fractal Properties of Onset Epilepsy Electroencephalogram

Epilepsy is a medical term which indicates a common neurological disorder characterized by seizures, because of abnormal neuronal activity. This leads to unconsciousness or even a convulsion. The possible etiologies should be evaluated and treated. Therefore, it is necessary to concentrate not only on finding out efficient treatment methods, but also on developing algorithm to support diagnosis. Currently, there are a number of algorithms, especially nonlinear algorithms. However, those algorithms have some difficulties one of which is the impact of noise on the results. In this paper, in addition to the use of fractal dimension as a principal tool to diagnose epilepsy, the combination between ICA algorithm and averaging filter at the preprocessing step leads to some positive results. The combination which improved the fractal algorithm become robust with noise on EEG signals. As a result, we can see clearly fractal properties in preictal and ictal period so as to epileptic diagnosis

Synchronization controller for a 3-RRR parallel manipulator

A 3-RRR parallel manipulator has been well-known as a closed-loop kinematic chain mechanism in which the end-effector generally a moving platform is connected to the base by several independent actuators. Performance of the robot is decided by performances of the component actuators which are independently driven by tracking controllers without acknowledging information from each other. The platform performance is degraded if any actuator could not be driven well. Therefore, this paper aims to develop an advanced synchronization (SYNC) controller for position tracking of a 3-RRR parallel robot using three DC motor-driven actuators. The proposed control scheme consists of three sliding mode controllers (SMC) to drive the actuators and a supervisory controller named PID-neural network controller (PIDNNC) to compensate the synchronization errors due to system nonlinearities, uncertainties and external disturbances. A Lyapunov stability condition is added to the PIDNNC training mechanism to ensure the robust tracking performance of the manipulator. Numerical simulations have been performed under different working conditions to demonstrate the effectiveness of the suggested control approach

Extracting Fetal Electrocardiogram from Being Pregnancy Based on Nonlinear Projection

Fetal heart rate extraction from the abdominal ECG is of great importance due to the information that carries in assessing appropriately the fetus well-being during pregnancy. In this paper, we describe a method to suppress the maternal signal and noise contamination to discover the fetal signal in a single-lead fetal ECG recordings. We use a locally linear phase space projection technique which has been used for noise reduction in deterministically chaotic signals. Henceforth, this method is capable of extracting fetal signal even when noise and fetal component are of comparable amplitude. The result is much better if the noise is much smaller (P wave and T wave can be discovered)

Identify aerodynamic derivatives of the airplane attitude channel using a spiking neural network

The paper proposes a method for identifying aerodynamic coefficient derivatives of aircraft attitude channel using spiking neural network (SNN) and Gauss-Newton algorithm based on data obtained from actual flights. Using SNN combination with Gauss-Newton iterative calculation algorithm allows the identification of aerodynamic coefficient derivatives in a nonlinear model for aerodynamic parameters with higher accuracy and faster calculation time. The paper proposes an algorithm to train the SNN multi-layer network by Normalized Spiking Error Back Propagation (NSEBP), in which, in the forward propagation period, the time of output spikes is calculating by solving quadratic equations instead of detection by traditional methods. The phase of propagation of errors backward uses the step-by-step calculation instead of the conventional gradient calculation method. The identification results are compared with the results when using the RBN network to prove the algorithm efficienc

Analyzing surface EMG signals to determine relationship between jaw imbalance and arm strength loss

BACKGROUND: This study investigated the relationship between dental occlusion and arm strength; in particular, the imbalance in the jaw can cause loss in arm strength phenomenon. One of the goals of this study was to record the maximum forces that the subjects can resist against the pull-down force on their hands while biting a spacer of adjustable height on the right or left side of the jaw. Then EMG measurement was used to determine the EMG-Force relationship of the jaw, neck and arms muscles. This gave us useful insights on the arms strength loss due to the biomechanical effects of the imbalance in the jaw mechanism. METHODS: In this study to determine the effects of the imbalance in the jaw to the strength of the arms, we conducted experiments with a pool of 20 healthy subjects of both genders. The subjects were asked to resist a pull down force applied on the contralateral arm while biting on a firm spacer using one side of the jaw. Four different muscles – masseter muscles, deltoid muscles, bicep muscles and trapezoid muscles – were involved. Integrated EMG (iEMG) and Higuchi fractal dimension (HFD) were used to analyze the EMG signals. RESULTS: The results showed that (1) Imbalance in the jaw causes loss of arm strength contra-laterally; (2) The loss is approximately a linear function of the height of the spacers. Moreover, the iEMG showed the intensity of muscle activities decreased when the degrees of jaw imbalance increased (spacer thickness increased). In addition, the tendency of Higuchi fractal dimension decreased for all muscles. CONCLUSIONS: This finding indicates that muscle fatigue and the decrease in muscle contraction level leads to the loss of arm strength

Optimising diagnosis and treatment of tuberculosis infection in community and primary care settings in two urban provinces of Viet Nam: a cohort study

Objectives: To end tuberculosis (TB), the vast reservoir of 1.7–2.3 billion TB infections (TBIs) must be addressed, but achieving global TB preventive therapy (TPT) targets seems unlikely. This study assessed the feasibility of using interferon-γ release assays (IGRAs) at lower healthcare levels and the comparative performance of 3-month and 9-month daily TPT regimens (3HR/9H). Design, setting, participants and intervention: This cohort study was implemented in two provinces of Viet Nam from May 2019 to September 2020. Participants included household contacts (HHCs), vulnerable community members and healthcare workers (HCWs) recruited at community-based TB screening events or HHC investigations at primary care centres, who were followed up throughout TPT. Primary and secondary outcomes: We constructed TBI care cascades describing indeterminate and positivity rates to assess feasibility, and initiation and completion rates to assess performance. We fitted mixed-effects logistic and stratified Cox models to identify factors associated with IGRA positivity and loss to follow-up (LTFU). Results: Among 5837 participants, the indeterminate rate was 0.8%, and 30.7% were IGRA positive. TPT initiation and completion rates were 63.3% (3HR=61.2% vs 9H=63.6%; p=0.147) and 80.6% (3HR=85.7% vs 9H=80.0%; p=0.522), respectively. Being male (adjusted OR=1.51; 95% CI: 1.28 to 1.78; p<0.001), aged 45–59 years (1.30; 1.05 to 1.60; p=0.018) and exhibiting TB-related abnormalities on X-ray (2.23; 1.38 to 3.61; p=0.001) were associated with positive IGRA results. Risk of IGRA positivity was lower in periurban districts (0.55; 0.36 to 0.85; p=0.007), aged <15 years (0.18; 0.13 to 0.26; p<0.001), aged 15–29 years (0.56; 0.42 to 0.75; p<0.001) and HCWs (0.34; 0.24 to 0.48; p<0.001). The 3HR regimen (adjusted HR=3.83; 1.49 to 9.84; p=0.005) and HCWs (1.38; 1.25 to 1.53; p<0.001) showed higher hazards of LTFU. Conclusion: Providing IGRAs at lower healthcare levels is feasible and along with shorter regimens may expand access and uptake towards meeting TPT targets, but scale-up may require complementary advocacy and education for beneficiaries and providers

Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke