Recomendações e práticas dos comportamentos saudáveis entre indivíduos com diagnóstico de hipertensão arterial e diabetes no Brasil: Pesquisa Nacional de Saúde (PNS), 2013 / Recommendations and practice of healthy behaviors among patients with diagnosis and diabetes in Brazil: National Health Survey (PNS), 2013

Resumo: Objetivo: Analisar as recomendações relacionadas aos comportamentos saudáveis e a adoção das práticas recomendadas entre indivíduos hipertensos e diabéticos. Métodos: Foram analisadas recomendações relacionadas aos comportamentos saudáveis segundo local do último atendimento (atenção básica; outros estabelecimentos públicos; estabelecimentos do setor privado). Os efeitos de ter um diagnóstico de hipertensão ou diabetes sobre a adoção das práticas recomendadas foram analisados por modelos de regressão logística multivariada, usando sexo, idade, e grau de escolaridade como variáveis de controle, e os seguintes desfechos: uso atual de produtos de tabaco; prática regular de atividade física no lazer; consumo recomendado de hortaliças e frutas; percepção de baixo consumo de sal; consumo frequente de doces; consumo excessivo de álcool. Resultados: Aproximadamente, 88% dos hipertensos receberam recomendações de ter uma alimentação saudável, 91% de ingerir menos sal, 83% de praticar atividade física regular, e 76% de não fumar. Entre os diabéticos, todas as recomendações relacionadas à alimentação foram muito frequentes, 95% para o hábito de ter uma alimentação com frutas e hortaliças. O efeito de ter um diagnóstico de hipertensão foi significativo para o não uso de produtos de tabaco e percepção de baixo consumo de sal. O diagnóstico de diabetes influenciou principalmente o hábito de não consumir doces frequentemente. Conclusão: Evidenciou-se que os hipertensos e diabéticos dão prioridade a não usar hábitos nocivos à saúde do que adotar práticas que lhe trarão benefícios. É preciso promover não só os efeitos adversos dos hábitos nocivos, mas também os benefícios dos comportamentos saudáveis para o envelhecimento com qualidade.

Abstract: Objective: To analyze healthy life style recommendations given in health care and the adoption of healthy behaviors among hypertension and diabetes patients. Methods: We analyzed the recommendations according to the place of the last health care visit (primary health care, other public facilities, and private health care facilities). The effects of having a diagnosis of hypertension or diabetes on the adoption of healthy practices were analyzed by multivariate logistic regression models, using sex, age, and educational level as control variables, and the following outcomes: current use of tobacco products; regular physical activity during leisure time; recommended intake of fruits and vegetables; perception of low salt intake; frequent consumption of sweets; and excessive alcohol consumption. Results: Approximately 88% of hypertension patients received recommendations to have a healthy diet, 91% to eat less salt, 83% to practice regular physical activity, and 76% to not to smoke. Among diabetic patients, all recommendations related to nutrition were very frequent, reaching 95% for the habit of having fruits and vegetables regularly. The effect of having a diagnosis of hypertension was significant for non-use of tobacco products and perception of low salt intake. The diagnosis of diabetes mainly influenced the habit of not consuming sweets often. Conclusion: Results evidenced that people with diagnosis of hypertension and diabetes give priority to not use (stop) harmful health behaviors than to adopt practices that will bring benefits to their health. It is necessary to promote not only the adverse effects of harmful habits, but also the benefits of healthy behaviors to aging well.

Sensorineural Hearing Loss: Causes and Hearing Rehabilitation / 한양의대학술지

Sensorineural hearing loss is one of the most common chronic clinical disorders that we can easily encounter. The etiology of sensorineural hearing loss is multifactorial: congenital, idiopathic, traumatic, noise-induced, head injury induced, infectious disease, drug induced, degenerative, immune disorder, vestibular schwannoma and Meniere's disease. Many people are living with the discomfort of hearing loss because fundamental treatment is has not yet been found. Also due to the progress of medical science, human life span has been extended. As the result, the number of patients suffering from hearing loss has increased. But the present situation does not measure up to the demand for recovery of hearing loss. Hearing loss has a great influence on the quality of life. To overcome this situation, neural prostheses such as the cochlear implant and auditory brainstem implant are helpful for the rehabilitation of total deaf patients. Recently, due to the advancement of studies related to hair cell regeneration and the field of gene therapy on the inner ear has made big progress during the last few years. The purpose of this study is to describe the latest known causes and rehabilitation of sensorineural hearing loss.

Fully Implantable Deep Brain Stimulation System with Wireless Power Transmission for Long-term Use in Rodent Models of Parkinson's Disease

OBJECTIVE: The purpose of this study to develop new deep-brain stimulation system for long-term use in animals, in order to develop a variety of neural prostheses. METHODS: Our system has two distinguished features, which are the fully implanted system having wearable wireless power transfer and ability to change the parameter of stimulus parameter. It is useful for obtaining a variety of data from a long-term experiment. RESULTS: To validate our system, we performed pre-clinical test in Parkinson's disease-rat models for 4 weeks. Through the in vivo test, we observed the possibility of not only long-term implantation and stability, but also free movement of animals. We confirmed that the electrical stimulation neither caused any side effect nor damaged the electrodes. CONCLUSION: We proved possibility of our system to conduct the long-term pre-clinical test in variety of parameter, which is available for development of neural prostheses.

Research progress on key technology of power and signal transmission in neuroprosthetic / 生物医学工程学杂志

The power and signal transmission technology is one of the key technologies in neuroprosthetic research. This paper proposes firstly the related theory of power and signal transmission technology in neuroprosthetic, then summarizes the three key aspects of the power and signal transmission technology in neuroprosthetic. After analyzed the development of the inductive wireless power harvesting technology, the wireless telemetry technology and the wireless power harvesting telemetry technology, the emphasis on research contents will be proposed and discussed, which will help accelerate the further research of prosthetic.

Accurate Representation of Light-intensity Information by the Neural Activities of Independently Firing Retinal Ganglion Cells

For successful restoration of visual function by a visual neural prosthesis such as retinal implant, electrical stimulation should evoke neural responses so that the information on visual input is properly represented. A stimulation strategy, which means a method for generating stimulation waveforms based on visual input, should be developed for this purpose. We proposed to use the decoding of visual input from retinal ganglion cell (RGC) responses for the evaluation of stimulus encoding strategy. This is based on the assumption that reliable encoding of visual information in RGC responses is required to enable successful visual perception. The main purpose of this study was to determine the influence of inter-dependence among stimulated RGCs activities on decoding accuracy. Light intensity variations were decoded from multiunit RGC spike trains using an optimal linear filter. More accurate decoding was possible when different types of RGCs were used together as input. Decoding accuracy was enhanced with independently firing RGCs compared to synchronously firing RGCs. This implies that stimulation of independently-firing RGCs and RGCs of different types may be beneficial for visual function restoration by retinal prosthesis.

Electrically-evoked Neural Activities of rd1 Mice Retinal Ganglion Cells by Repetitive Pulse Stimulation

For successful visual perception by visual prosthesis using electrical stimulation, it is essential to develop an effective stimulation strategy based on understanding of retinal ganglion cell (RGC) responses to electrical stimulation. We studied RGC responses to repetitive electrical stimulation pulses to develop a stimulation strategy using stimulation pulse frequency modulation. Retinal patches of photoreceptor-degenerated retinas from rd1 mice were attached to a planar multi-electrode array (MEA) and RGC spike trains responding to electrical stimulation pulse trains with various pulse frequencies were observed. RGC responses were strongly dependent on inter-pulse interval when it was varied from 500 to 10 ms. Although the evoked spikes were suppressed with increasing pulse rate, the number of evoked spikes were >60% of the maximal responses when the inter-pulse intervals exceeded 100 ms. Based on this, we investigated the modulation of evoked RGC firing rates while increasing the pulse frequency from 1 to 10 pulses per second (or Hz) to deduce the optimal pulse frequency range for modulation of RGC response strength. RGC response strength monotonically and linearly increased within the stimulation frequency of 1~9 Hz. The results suggest that the evoked neural activities of RGCs in degenerated retina can be reliably controlled by pulse frequency modulation, and may be used as a stimulation strategy for visual neural prosthesis.

In vivo Performance Evaluation of Implantable Wireless Neural Signal Transmission System for Brain Machine Interface

A brain-machine interface (BMI) has recently been introduced to research a reliable control of machine from the brain information processing through single neural spikes in motor brain areas for paralyzed individuals. Small, wireless, and implantable BMI system should be developed to decode movement information for classifications of neural activities in the brain. In this paper, we have developed a totally implantable wireless neural signal transmission system (TiWiNets) combined with advanced digital signal processing capable of implementing a high performance BMI system. It consisted of a preamplifier with only 2 operational amplifiers (op-amps) for each channel, wireless bluetooth module (BM), a Labview-based monitor program, and 16 bit-RISC microcontroller. Digital finite impulse response (FIR) band-pass filter based on windowed sinc method was designed to transmit neural signals corresponding to the frequency range of 400 Hz to 1.5 kHz via wireless BM, measuring over -48 dB attenuated in the other frequencies. Less than +/-2% error by inputting a sine wave at pass-band frequencies for FIR algorithm test was obtained between simulated and measured FIR results. Because of the powerful digital FIR design, the total dimension could be dramatically reduced to 23x27x4 mm including wireless BM except for battery. The power isolation was built to avoid the effect of radio-frequency interference on the system as well as to protect brain cells from system damage due to excessive power dissipation or external electric leakage. In vivo performance was evaluated in terms of long-term stability and FIR algorithm for 4 months after implantation. Four TiWiNets were implanted into experimental animals' brains, and single neural signals were recorded and analyzed in real time successfully except for one due to silicon- coated problem. They could control remote target machine by classify neural spike trains based on decoding technology. Thus, we concluded that our study could fulfill in vivo needs to study various single neuron-movement relationships in diverse fields of BMI.

Classification of BMI Control Commands Using Extreme Learning Machine from Spike Trains of Simultaneously Recorded 34 CA1 Single Neural Signals

A recently developed machine learning algorithm referred to as Extreme Learning Machine (ELM) was used to classify machine control commands out of time series of spike trains of ensembles of CA1 hippocampus neurons (n=34) of a rat, which was performing a target-to-goal task on a two-dimensional space through a brain-machine interface system. Performance of ELM was analyzed in terms of training time and classification accuracy. The results showed that some processes such as class code prefix, redundancy code suffix and smoothing effect of the classifiers' outputs could improve the accuracy of classification of robot control commands for a brain-machine interface system.