Design of Emergency Communication and Alerting System for High Risk Workers

Emergency Management System (EMS) is a system that communicates and alert for emergency medical care. Once it is activated by an incident that causes serious illness or injury to human workers. High Risk workers emergency communication system is equipment which is used for response on any emergency, the worker can alert the Rescuing people, and it will continuously monitor the workers blood pressure and Heart beat rate .If any violation occurs it will be observed by the equipment and it will alert the responsible persons by alarm and Emergency Messages. Using GSM modem, pressure sensor and Heartbeat sensor the equipment can observe the real-time health monitoring of the high risk workers. According to the alerting system we can shoot the first aid and control the accident severity rate. Thus, the proposed system makes the human’s life at workplace easier and more comfortable

A comparative study to assess the awareness of antibiotic resistance amongst first and second year medical undergraduate students in a medical college

Background: With the rising instances of antibiotic resistance and decline in the discovery of newer antibiotics, it is high time to prevent the emergence of antibiotic resistance. One of the best measures regarding the above problem is education and creating awareness regarding antibiotic resistance, and that too primarily among healthcare professionals. The initiation should start at the basic level and that too in the early days of medical profession, so that there is greater awareness and strong foundation for antibiotic prescribing pattern. The present study is taken up to compare awareness among 1st year and 2nd year medical students in a private medical college with 2nd year medical students having prior education regarding antibiotics resistance and first year students representing general public without any education regarding antibiotics resistance.Methods: This study was a comparative, cross-sectional, questionnaire based study. The questionnaire was validated for face validity and content validity from subject experts. The two groups selected were 1st year and 2nd year medical undergraduates. Data was analysed using simple descriptive statistics.Results: 136 students from 1st year and 88 students from 2nd year participated in the study. In both the groups studied, majority of the respondents completed the full course of antibiotics. 77% of 1st year and all 2nd year students were aware of the antibiotic resistance. 99% of 2nd year students and only 49% of the 1st year students were aware of the reasons for it (p<0.01). Awareness regarding prophylactic usage of antibiotics, usage for simple common cold and usage of higher antibiotics for mid infection leading to Antibiotic Resistance was significantly less among first year students. 2nd year students were well aware of consequences of antibiotic resistance like ineffective treatment, prolongation of illness, emergence of bacterial resistance and additional cost burden than 1st year students. Awareness regarding other aspects of antibiotic resistance was not significant between two groups.Conclusions: Stressing upon awareness and education regarding antibiotic resistance in the early days of medical curriculum will help in change of behaviour and habits of antibiotic usage and rational prescribing of antibiotics by the future doctors.

FPGA based implementation of low complex adaptive speckle suppression filter for B-mode medical ultrasound images

Speckles are considered as noise, which masks the fine information present in B-mode ultrasound images. Speckles appears as small snakes and dense granular like structures which has serious impact on visual perception of an image. Adaptive filter based on local statistics of an image is used to enhance the image by suppressing the noise. Adaptive speckle suppression filter enhance the image by reducing the variance between intrapixel intensities in homogeneous regions and preserving variance across interpixel intensities across the nonhomogeneous regions. In this paper, we implemented low complex adaptive speckle suppression filter on FPGA based kintex7 board. The performance of the filter is evaluated by plotting the pixel variations of original image with filtered image of an ultrasound phantom. The results show that proposed algorithm can be implemented on mobile ultrasound platforms due to 50% less computations needed per pixel compared to traditional adaptive speckle suppression algorithms, which aids better diagnosis for healthcare

A comparative study of probiotic, prokinetic based triple therapy with USFDA regimen in the eradication of Helicobacter pylori in a tertiary care hospital

Background: Helicobacter pylori infection has been associated with peptic ulcer disease, gastric carcinoma and gastric mucosa associated lymphoid tissue (MALT) lymphoma. Its eradication is important and current regimens are associated with antibiotic resistance, side effects and poor patient compliance. Probiotics supplementation can overcome the above problem and additions of prokinetics improve dyspepsia symptoms and thereby improve patient compliance. So the aim of the study was to compare efficacy and safety of standard United States Food and Drug Administration (USFDA) regimen with probiotic, prokinetic based novel regimen.Methods: 100 patients diagnosed with H. pylori infection were randomly assigned into two eradication regimen groups viz., group A and group B. Group A received standard USFDA regimen, amoxicillin 1 gm, lansoprazole 30 mg and clarithromycin 500 mg twice a day for 2 weeks and group B received a probiotic and prokinetic itopride 50 mg thrice daily, pantoprazole 40 mg, amoxicillin 1 gm and clarithromycin 500 mg twice daily for 2 weeks. Patients with Rapid Urease Test (RUT) and histopathology reports negative for H. pylori were considered as eradicated and then the percentage of eradication rate in both groups was compared.Results: H. pylori eradication rates were more in group B compared to group A (84% vs 70%, p =0.096 at 95% CI). The occurrence of side effects was less in group B compared to group A (30% vs 46%, p= 0.099). Diarrhoea was statistically less in group B compared to group A (p< 0.05).Conclusions: Probiotics supplementation increases eradication rates of anti H. pylori therapy and improves tolerability by reducing side effects especially diarrhoea. Prokinetics and probiotic based novel regimen improved dyspepsia symptoms and patient compliance

Aerosol Infection Model of Tuberculosis in Wistar Rats

We explored suitability of a rat tuberculosis aerosol infection model for investigating the pharmacodynamics of new antimycobacterial agents. Infection of rats via the aerosol route led to a reproducible course of M. tuberculosis infection in the lungs. The pulmonary bacterial load increased logarithmically during the first six weeks, thereafter, the infection stabilized for the next 12 weeks. We observed macroscopically visible granulomas in the lungs with demonstrable acid-fast bacilli and associated histopathology. Rifampicin (RIF) at a dose range of 30 to 270 mg/kg exhibited a sharp dose response while isoniazid (INH) at a dose range of 10 to 90 mg/kg and ethambutol (EMB) at 100 to 1000 mg/kg showed shallow dose responses. Pyrazinamide (PZA) had no dose response between 300 and 1000 mg/kg dose range. In a separate time kill study at fixed drug doses (RIF 90 mg/kg, INH 30 mg/kg, EMB 300 mg/kg, and PZA 300 mg/kg) the bactericidal effect of all the four drugs increased with longer duration of treatment from two weeks to four weeks. The observed infection profile and therapeutic outcomes in this rat model suggest that it can be used as an additional, pharmacologically relevant efficacy model to develop novel antitubercular compounds at the interface of discovery and development

Evaluation of academic stress among medical students using graphology and machine learning algorithm in correlation with salivary cortisol

Background: Stress is a part of the academic life of graduates. Young adults are especially susceptible to academic stress based on their subjective commitment towards academic goals, and social pressure for superior academic performance. Recognizing academic stress is crucial for planning successful management, and to prevent mental illness. The aim of the study was to develop methods to identify stress using graphology, machine learning algorithm and salivary cortisol.Methods: The study included a mixed method research design and   enrolled 43 medical students (19 males and 24 females) between 18-23 years of age were taken in the present study. The Kessler psychological distress scale (K10) was used to ascertain distress among the study subjects.Results: Students written manuscript images were taken for artificial intelligence training and analysis. The written   manuscript was evaluated for positive and negative personality traits using graphology techniques. One of the negative traits identified by graphology, i.e.; dejection, it was used to train a machine learning tool to identify the negative trait of dejection.Conclusions: This study suggests that mental health professionals can train machine learning algorithms, using graphology tools, to function as a screening tool to determine stress levels. This may help to plan for management and recovery of stressed individuals and help them in future academic performance

Assessment on awareness of rational prescribing practices among medical interns in a tertiary care hospital: a questionnaire based study

Background: Awareness about rational use of Medicines is required to improve the quality of health care system. Attitude towards rational drug use is also an utmost importance as they constitute the future generation doctors.Methods: A set of 13 questionnaire is given to the interns through an online link to their e-mail which contains informed consent and questionnaires. Respondents has to select the best suitable option and after which the data will be compiled and statistically analyzed.Results: Age of the study participants range from 22-26yrs. Half of them have finished major postings. Almost 96.1 % of them were aware of the term essential drugs. Only 25% of them said that they have NLEMI at work place, 75% of them were aware of the term Rational use of Medicines. Only 32% of them were aware of the term P drugs. 44% of them were aware of STEP criteria for selection of drug and 47% of them were aware of the updated prescribing format. 8% knew the difference between old and new prescription format, 25% of them always prescribe. Almost 82% of them narrate regarding the disease and drug therapy, 31% of them prescribe only generic name.Conclusions: Educational intervention like CME and practical hands on training in Rational use of Medicines would help them in better understanding of the subject and its clinical implications thereby decreasing the prescribing errors

FPGA-Based Portable Ultrasound Scanning System with Automatic Kidney Detection

Bedsides diagnosis using portable ultrasound scanning (PUS) offering comfortable diagnosis with various clinical advantages, in general, ultrasound scanners suffer from a poor signal-to-noise ratio, and physicians who operate the device at point-of-care may not be adequately trained to perform high level diagnosis. Such scenarios can be eradicated by incorporating ambient intelligence in PUS. In this paper, we propose an architecture for a PUS system, whose abilities include automated kidney detection in real time. Automated kidney detection is performed by training the Viola–Jones algorithm with a good set of kidney data consisting of diversified shapes and sizes. It is observed that the kidney detection algorithm delivers very good performance in terms of detection accuracy. The proposed PUS with kidney detection algorithm is implemented on a single Xilinx Kintex-7 FPGA, integrated with a Raspberry Pi ARM processor running at 900 MHz