Detection of freezing of gait and gait initiation failure in people with Parkinson's disease using electroencephalogram signals

University of Technology Sydney. Faculty of Engineering and Information Technology.Parkinson’s disease (PD) is the second most common age related neurodegenerative disorder, affecting approximately 1-2% of the elderly population. Freezing of Gait (FOG) is a very disabling feature of PD that causes frequent falls. During FOG, patients are suddenly unable to take a step despite the intention to walk or continue moving forward. The neural mechanisms of FOG are unclear and treatments have only limited effectiveness. Based on contexts of behavioural measures in daily life, different types of FOG have been observed including: freezing when turning (TF); freezing when getting through narrow doorways; freezing when reaching a target; freezing when straight walking or freezing when initiating gait to start a movement (GIF). TF and GIF are recognized to be the most frequent triggers of FOG seen in PD patients. To detect FOG, using parameters extracted from the Electroencephalogram (EEG) is one of the most promising methods. In the comparison of using “body-worn” sensors technique, EEG measures the activity of the brain where the root of FOG is occurring. Therefore, EEG will be quicker to detect FOG than “body-worn” sensors because of the time the neural signal has to travel all the way to the legs to be measured, thus offering the most optimal time window for intervention to overcome FOG. The research in this thesis introduces advanced algorithms for FOG detection using EEG signals. These algorithms have been developed and applied successfully to detect FOG and its two common subtypes (GIF, TF) based on various features extractions and classifiers, providing high accuracy for detection. It was found that the combination of Independent Component Analysis Entropy Boundary Minimization (ICA-EBM), S-Transform (ST) and Bayesian Neural Networks (BNN) proved to be a very robust and effective method for freezing detection. In the first study, abnormal changes of EEG signal to detect FOG were investigated. By using Fast Fourier Transform as the feature extraction and Artificial Neural Networks (ANN) as a classifier, the EEG data of FOG could be detected effectively from seven PD patients with sensitivity, specificity and accuracy of 72.20%, 70.58% and 71.46%, respectively. Furthermore, FOG episodes were found to be associated with significant increases in the high beta band (21-38Hz) across the central, frontal, occipital and parietal EEG sites. In the second study, the dynamic brain changes underlying a GIF episode and its detection were investigated in four PD patients. This research studied the brain activity underlying GIF by analyzing Wavelet Transform (WT) of EEG signals. Using ICA-EBM for EEG source separation, WT for feature extraction and Support Vector Machine (SVM) for classification, the correct identification of GIF episodes was improved with sensitivity, specificity, and accuracy of 83.94%, 89.39% and 86.67%, respectively. The final classification results produced by this dissertation indicated that by applying source separation ICA-EBM for pre-processing EEG data, time-frequency ST techniques for feature extraction and BNN for classification, a freezing event can be successfully detected using EEG signals. The results for the TF detection were achieved with sensitivity, specificity, and accuracy of 83.00%, 87.60% and 85.40%, respectively. The results for the GIF detection were relatively similar with sensitivity, specificity, and accuracy of 88.96%, 90.26% and 89.50%, respectively. With the final performance (ICA-EBM, ST, BNN) achieved by this thesis, future work will be carried out to pursue the eventual aim of the current research, which is developing an EEG-based system for detecting FOG that can be applied in real-time

Detection of turning freeze in Parkinson's disease based on S-transform decomposition of EEG signals

© 2017 IEEE. Freezing of Gait (FOG) is a highly debilitating and poorly understood symptom of Parkinson's disease (PD), causing severe immobility and decreased quality of life. Turning Freezing (TF) is known as the most common sub-type of FOG, also causing the highest rate of falls in PD patients. During a TF, the feet of PD patients appear to become stuck whilst making a turn. This paper presents an electroencephalography (EEG) based classification method for detecting turning freezing episodes in six PD patients during Timed Up and Go Task experiments. Since EEG signals have a time-variant nature, time-frequency Stockwell Transform (S-Transform) techniques were used for feature extraction. The EEG sources were separated by means of independent component analysis using entropy bound minimization (ICA-EBM). The distinctive frequency-based features of selected independent components of EEG were extracted and classified using Bayesian Neural Networks. The classification demonstrated a high sensitivity of 84.2%, a specificity of 88.0% and an accuracy of 86.2% for detecting TF. These promising results pave the way for the development of a real-time device for detecting different sub-types of FOG during ambulation

Network Coding with Multimedia Transmission and Cognitive Networking: An Implementation based on Software-Defined Radio

Network coding (NC) is considered a breakthrough to improve throughput, robustness, and security of wireless networks. Although the theoretical aspects of NC have been extensively investigated, there have been only few experiments with pure NC schematics. This paper presents an implementation of NC under a two-way relay model and extends it to two\ua0non-straightforward scenarios: (i) multimedia transmission with layered coding and multiple-description coding, and (ii) cognitive radio with Vandermonde frequency division multiplexing (VFDM). The implementation is in real time and based on software-defined radio (SDR). The experimental results show that, by combining NC and source coding, we can control the quality of the received multimedia content in an on-demand manner. Whereas in the VFDM-based cognitive radio, the quality of the received content in the primary receiver is low (due to imperfect channel estimation) yet retrievable. Our implementation results serve as a proof for the practicability of network coding in relevant applications

Network Coding with Multimedia Transmission and Cognitive Networking: An Implementation based on Software-Defined Radio

Network coding (NC) is considered a breakthrough to improve throughput, robustness, and security of wireless networks. Although the theoretical aspects of NC have been extensively investigated, there have been only few experiments with pure NC schematics. This paper presents an implementation of NC under a two-way relay model and extends it to two non-straightforward scenarios: (i) multimedia transmission with layered coding and multiple-description coding, and (ii) cognitive radio with Vandermonde frequency division multiplexing (VFDM). The implementation is in real time and based on software-defined radio (SDR). The experimental results show that, by combining NC and source coding, we can control the quality of the received multimedia content in an on-demand manner. Whereas in the VFDM-based cognitive radio, the quality of the received content in the primary receiver is low (due to imperfect channel estimation) yet retrievable. Our implementation results serve as a proof for the practicability of network coding in relevant applications

Successful Psoriasis Treatment Using NB-UVB with Methotrexate: The Vietnamese Experience

AIM: To compare the effectiveness of narrowband ultraviolet B (NBUVB) and oral methotrexate (MTX) to oral MTX alone in Vietnamese psoriasis patients, from May 2016 to May 2018. METHODS: We conducted a non-randomized trial on 70 patients with plaque-type psoriasis of moderate to severe. Thirty-five patients apply NBUVB once/day in 5 days/week for 4 weeks plus oral MTX 7.5 mg/week and 35 patients oral MTX 7.5 mg/week and both two groups treatment for 3 months. The extent of the lesion was assessed by the Psoriasis Area and Severity Index (PASI). RESULTS: The proportion of decreasing PASI was comparable (68.49% in NBUVB and MTX versus 57.62% in MTX alone); p < 0.05. Inside, good 28.58%, moderate 68.57% and poor 2.85% in NBUVB and MTX better than good 2.85%, moderate 71.4% and poor 25.72% in MTX alone; p < 0.05. The recurrence rate after 24 months of the NBUVB and MTX group (42.9%) was lower than the MTX alone group (71.4%); p < 0.05. CONCLUSION: NBUVB and oral MTX have affected treatment with chronic plaque psoriasis better than oral MTX alone

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

Manure, biogas digestate and crop residue management affects methane gas emissions from rice paddy fields on Vietnamese smallholder livestock farms

Greenhouse gas (CH4 and N2O) emissions from rice paddy fields amended by differently treated manure and crop residue inputs [fresh manure (FM), composted manure (CM), liquid biogas digestate from manure (D), D mixed with biochar (D ? B) or D mixed with rice straw and composted before application (CD ? RS)], were compared in a field experiment, also including two mineral nitrogen fertiliser controls (N1, N2). The trial was performed on a degraded soil in Bac Giang Province in northern Vietnam with a three-crop per year rotation (summer rice–maize–spring rice). CH4 and N2O fluxes from the two rice crops were measured using static chambers. Fluxes of N2O were below or close to the detection limit at nearly all sampling times in both seasons and therefore considered negligible. However, the CH4 emissions were significant and their temporal pattern differed markedly between the rice seasons. In the summer rice season, the D ? B ? N1 and D ? N1 treatments had significantly lower cumulative CH4 emissions (156 and 162 kg CH4 ha-1 crop-1) than CM ? N1, CD ? RS ? N1 and FM ? N1 treatments (217, 283 and 288 kg CH4 ha-1 crop-1, respectively). In the spring rice season, CH4 emissions were generally much lower, and the D ? B ? N1 and D ? N1 treatments emitted significantly less CH4 (44 and 72 kg CH4 ha-1 crop-1) in comparison with treatments amended with FM ? N1, CD ? RS ? N1 and CM ? N1 (89, 124 and 137 kg CH4 ha-1 crop-1, respectively). Treatments amended with D ? B ? N1 or D ? N1 therefore had the lowest emissions of methane per unit of rice grain yield

Transformacja cyfrowa w sektorze wydobywczym w Wietnamie

Digital transformation is one of the inevitable trends in today’s world. Vietnam is one of the pioneer countries following this trend and has launched a national digital transformation program. Digital transformation has attracted great interest from both the community of scientists and managers in general and in the field of coal mining and other minerals. Currently, researchers have been focusing on issues, such as the theory of digital transformation in both state and the business sector, the relationships between digital transformation and the building of e-government or digital government, and between digital transformation and effective national administration. In this study, the method of document-based analysis (Desk review) was used to analyze and evaluate the current situation of digital transformation of the coal and mineral mining industry and identify achievements as well as limitations of the digital transformation process in the coal and mineral mining industry in Vietnam. The study presents the following issues: (1) Some general issues about digital transformation, in which the concept of digital transformation is clarified; Meaning of digital transformation in the field of coal and mineral mining; Requirements for digital transformation in the field of coal-mineral mining. (2) The current status of digital transformation in coal-mineral mining in Vietnam, including applying advanced technologies in exploration and mining, and application of advanced technologies in mining and environmental protection.Cyfrowa transformacja to jeden z nieuniknionych trendów w dzisiejszym świecie. Wietnam jest jednym z pionierskich krajów podążających za tym trendem i uruchomił krajowy program transformacji cyfrowej. Transformacja cyfrowa cieszy się dużym zainteresowaniem zarówno środowiska naukowców, jak i menedżerów w ogóle oraz w obszarze górnictwa węgla kamiennego i innych kopalin. Obecnie badacze koncentrują się na takich zagadnieniach, jak teoria transformacji cyfrowej zarówno w państwie, jak iw sektorze biznesowym, związki między transformacją cyfrową a budową e-government lub cyfrowego rządu oraz między transformacją cyfrową a efektywną administracją państwową. W niniejszym opracowaniu metoda analizy dokumentów (Desk review) została wykorzystana do analizy i oceny aktualnej sytuacji transformacji cyfrowej górnictwa węgla kamiennego i kopalin oraz identyfikacji osiągnięć i ograniczeń procesu transformacji cyfrowej w górnictwie węglowym i mineralnym. przemysł wydobywczy minerałów w Wietnamie. W opracowaniu przedstawiono następujące zagadnienia: (1) Niektóre ogólne zagadnienia dotyczące transformacji cyfrowej, w których doprecyzowano pojęcie transformacji cyfrowej; Znaczenie transformacji cyfrowej w obszarze górnictwa węglowego i mineralnego; Wymagania transformacji cyfrowej w obszarze górnictwa węglowo-mineralnego. (2) Aktualny stan transformacji cyfrowej w górnictwie węglowo-mineralnym w Wietnamie, w tym zastosowanie zaawansowanych technologii w eksploracji i wydobyciu oraz zastosowanie zaawansowanych technologii w górnictwie i ochronie środowisk

A cohort study to define the age-specific incidence and risk factors of Shigella diarrhoeal infections in Vietnamese children: a study protocol.

BACKGROUND: Shigella spp. are one of the most common causes of paediatric dysentery globally, responsible for a substantial proportion of diarrhoeal disease morbidity and mortality, particularly in industrialising regions. Alarming levels of antimicrobial resistance are now reported in S. flexneri and S. sonnei, hampering treatment options. Little is known, however, about the burden of infection and disease due to Shigella spp. in the community. METHODS/DESIGN: In order to estimate the incidence of this bacterial infection in the community in Ho Chi Minh City, Vietnam we have designed a longitudinal cohort to follow up approximately 700 children aged 12-60 months for two years with active and passive surveillance for diarrhoeal disease. Children will be seen at 6 month intervals for health checks where blood and stool samples will be collected. Families will also be contacted every two weeks for information on presence of diarrhoea in the child. Upon report of a diarrhoeal disease episode, study nurses will either travel to the family home to perform an evaluation or the family will attend a study hospital at a reduced cost, where a stool sample will also be collected. Case report forms collected at this time will detail information regarding disease history, risk factors and presence of disease in the household.Outcomes will include (i) age-specific incidence of Shigella spp. and other agents of diarrhoeal disease in the community, (ii) risk factors for identified aetiologies, (iii) rates of seroconversion to a host of gastrointestinal pathogens in the first few years of life. Further work regarding the longitudinal immune response to a variety of Shigella antigens, host genetics and candidate vaccine/diagnostic proteins will also be conducted. DISCUSSION: This is the largest longitudinal cohort with active surveillance designed specifically to investigate Shigella infection and disease. The study is strengthened by the active surveillance component, which will likely capture a substantial proportion of episodes not normally identified through passive or hospital-based surveillance. It is hoped that information from this study will aid in the design and implementation of Shigella vaccine trials in the future