This slide is about the basic theories of Neurotechnology.
It shows
1. An overview of this area
- Market value, etc
2. Basic knowledge
- Types of neurotechnologies
- Basics of neuroscience
- software engineering.
3. Use cases with neurotechnologies.
Exploring ICP, Tissue Oxygenation and RSNA with Implantable TelemetryInsideScientific
This webinar offers insight into unique applications of Millar implantable telemetry, including the measurement of intra-cranial pressure (ICP), concurrent sympathetic nerve activity (SNA) and arterial pressure recordings, and tissue oxygen.
Experts share experimental methods and highlight distinctive capabilities of this technology that have helped each of them uncover scientific findings in the areas of renal sympathetic nerve activity (RSNA) and cerebral perfusion in rats, respectively.
Dr. Fiona McBryde discusses her recent experience working with rats where she has successfully instrumented subjects with two telemeters, permitting continuous recording of arterial blood pressure, intracranial pressure and brain oxygenation. Importantly, she shares tips and prescribed best-practices for both single and dual telemeter implantation, and discusses experimental design for more complex multi-parameter research studies.
Professor Jacqueline Phillips discusses highlights from her recent publication, “Direct conscious telemetry recordings demonstrate increased renal sympathetic nerve activity (RSNA) in rats with chronic kidney disease”, specifically focusing on HOW scientists can successfully acquire continuous RSNA data and should approach data analysis.
BRAIN GATE TECHNOLOGY is a boon for ppl met with accidents leading to spinal cord failure,,,,, THIS technology brings ray of hope and sunshine in their life
Report consist of the literature survey of Spinal Cord Injuries. Design and implantation of the electrode with MEMS technology to implantable pulse generator with a rechargeable battery to cure the pain.
FRACTIONAL ORDER BUTTERWORTH FILTER FOR FETAL ELECTROCARDIOGRAPHIC SIGNAL FEA...sipij
The non-invasive Fetal Electrocardiogram (FECG) signal has become a significant method for monitoring the fetus's physiological conditions, extracted from the Abdominal Electrocardiogram (AECG) during pregnancy. The current techniques are limited during delivery for detecting and analyzing fECG. The non - intrusive fECG recorded from the mother's abdomen is contaminated by a variety of noise sources, can be a more challenging task for removing the maternal ECG. These contaminated noises have become a major challenge during the extraction of fetal ECG is managed by uni-modal technique. In this research, a new method based on the combination of Wavelet Transform (WT) and Fast Independent Component Analysis (FICA) algorithm approach to extract fECG from AECG recordings of the pregnant woman is proposed. Initially, preprocessing of a signal is done by applying a Fractional Order Butterworth Filter (FBWF). To select the Direct ECG signal which is characterized as a reference signal and the abdominal signal which is characterized as an input signal to the WT, the cross-correlation technique is used to find the signal with greater similarity among the available four abdominal signals. The model performance of the proposed method shows the most frequent similarity of fetal heartbeat rate present in the database can be evaluated through MAE and MAPE is 0.6 and 0.041209 respectively. Thus the proposed methodology of de-noising and separation of fECG signals will act as the predominant one and assist in understanding the nature of the delivery on further analysis.
Microneurography: Recording Nerve Traffic Via Intraneural Microelectrodes in ...InsideScientific
In this webinar sponsored by ADInstruments, Professor Vaughan Macefield, one of the world’s leading neurophysiologists in the field of microneurography, speaks about the current trends in this field, and specifically shares methodology, tips and best-practices that he uses in his lab to answer complex questions about physiological processes and associated stimuli.
Key topics covered during this webinar included…
- What is Microneurography and what sort of scientific questions can it answer?
- What are the current trends in the field?
- What equipment is needed to do this type of work?
- Tips, tricks and best-practices for the Microneurography technique
- Important data acquisition and analysis processes
Background:
While many neurophysiologists use invasive techniques to record from the brain or peripheral nerves in anaesthesed animals, such approaches have – of necessity – been rather limited in human subjects. However, 50 years ago the first direct recordings of nerve activity from peripheral nerves in awake human subjects were published. In Uppsala, Sweden, Karl–Erik Hagbarth and Åke Vallbo developed the technique of “microneurography”, in which an insulated tungsten microelectrode is inserted through the skin and into a muscle or cutaneous fascicle of a peripheral (or cranial) nerve. Their original aim was to understand the population behavior of muscle spindles during voluntary contractions, but they soon discovered that they could record from individual myelinated sensory axons supplying muscle or skin. Moreover, they confirmed that the same microelectrodes could record spontaneous and evoked activity generated by the unmyelinated sympathetic axons.
Poster Presentation on "Artifact Reduction from Scalp EEG for Epilepsy Seizur...Md Kafiul Islam
This research presents a method to reduce artifacts from scalp EEG recordings to facilitate seizure diagnosis/detection for epilepsy patients. The proposed method is primarily based on stationary wavelet transform and takes the spectral band of seizure activities (i.e. 0.5 - 30 Hz) into account to separate artifacts from seizures. It requires a reference seizure epoch of N-sec which can either be generated from a patient-specific
seizure database (if available) or can be simulated by a simple mathematical model of seizure. The purpose of the algorithm is to reduce as much artifacts as possible without distorting the desired seizure events to be detected/diagnosed. Different artifact templates have been simulated to mimic the most commonly appeared artifacts in real EEG recordings. The algorithm is applied on three sets of synthesized data:
fully simulated, semi-simulated and real data to evaluate both the artifact removal performance and seizure detection performance. The EEG features responsible for detection of seizures from non-seizure epochs have been found to be easily distinguishable after artifacts are removed and consequently reduces the false alarms in seizure detection. Results from an extensive experiment with these datasets prove the efficacy of
the proposed algorithm and hence this algorithm (with some modifications) is expected to be a future candidate for artifact removal not only in epilepsy diagnosis applications but also in other applications (e.g. BCI or other neuroscience studies).
Noninvasive, Automated Measurement of Sleep, Wake and Breathing in RodentsInsideScientific
In this exclusive webinar sponsored by Signal Solutions LLC, Dr. Bruce O’Hara discusses methodology, best-practices and use studies of the PiezoSleep system. Discussion focuses on how these techniques can answer questions about animal behavior, phenotyping and relationships between sleep and disease. Dr. O’Hara also highlights the benefits of the PiezoSleep system that can assess sleep, wake and breathing variables.
Braingate is an electrode chip which can be implemented in the brain. When it is implemented in brain, the electrical signal exchanged by neurons within the brain. Those signals are sent to the brain and it executes body movement. All the signalling process is handled by special software. The signal sends to the computer and then the computer is controlled by patient.
Effective electroencephalogram based epileptic seizure detection using suppo...IJECEIAES
Epilepsy is one of the widespread disorders. It is a noncommunicable disease that affects the human nerve system. Seizures are abnormal patterns of behavior in the electricity of the brain which produce symptoms like losing consciousness, attention or convulsions in the whole body. This paper demonstrates an effective electroencephalogram (EEG) based seizure detection method using discrete wavelet transformation (DWT) for signal decomposition to extract features. An automatic channel selection method was proposed by the researcher to select the best channel from 23 channels based on maximum variance value. The records were segmented into a nonoverlapping segment with long 1-S. The support vector machine (SVM) model was used to automatically detect segments that contain seizures, using both frequency and time domain statistical moment features. The experimental result was obtained from 24 patients in CHB-MIT database. The average accuracy is 94.1, sensitivity is 93.5, specificity is 94.6 and the false positive rate average is 0.054.
This slide is about the basic theories of Neurotechnology.
It shows
1. An overview of this area
- Market value, etc
2. Basic knowledge
- Types of neurotechnologies
- Basics of neuroscience
- software engineering.
3. Use cases with neurotechnologies.
Exploring ICP, Tissue Oxygenation and RSNA with Implantable TelemetryInsideScientific
This webinar offers insight into unique applications of Millar implantable telemetry, including the measurement of intra-cranial pressure (ICP), concurrent sympathetic nerve activity (SNA) and arterial pressure recordings, and tissue oxygen.
Experts share experimental methods and highlight distinctive capabilities of this technology that have helped each of them uncover scientific findings in the areas of renal sympathetic nerve activity (RSNA) and cerebral perfusion in rats, respectively.
Dr. Fiona McBryde discusses her recent experience working with rats where she has successfully instrumented subjects with two telemeters, permitting continuous recording of arterial blood pressure, intracranial pressure and brain oxygenation. Importantly, she shares tips and prescribed best-practices for both single and dual telemeter implantation, and discusses experimental design for more complex multi-parameter research studies.
Professor Jacqueline Phillips discusses highlights from her recent publication, “Direct conscious telemetry recordings demonstrate increased renal sympathetic nerve activity (RSNA) in rats with chronic kidney disease”, specifically focusing on HOW scientists can successfully acquire continuous RSNA data and should approach data analysis.
BRAIN GATE TECHNOLOGY is a boon for ppl met with accidents leading to spinal cord failure,,,,, THIS technology brings ray of hope and sunshine in their life
Report consist of the literature survey of Spinal Cord Injuries. Design and implantation of the electrode with MEMS technology to implantable pulse generator with a rechargeable battery to cure the pain.
FRACTIONAL ORDER BUTTERWORTH FILTER FOR FETAL ELECTROCARDIOGRAPHIC SIGNAL FEA...sipij
The non-invasive Fetal Electrocardiogram (FECG) signal has become a significant method for monitoring the fetus's physiological conditions, extracted from the Abdominal Electrocardiogram (AECG) during pregnancy. The current techniques are limited during delivery for detecting and analyzing fECG. The non - intrusive fECG recorded from the mother's abdomen is contaminated by a variety of noise sources, can be a more challenging task for removing the maternal ECG. These contaminated noises have become a major challenge during the extraction of fetal ECG is managed by uni-modal technique. In this research, a new method based on the combination of Wavelet Transform (WT) and Fast Independent Component Analysis (FICA) algorithm approach to extract fECG from AECG recordings of the pregnant woman is proposed. Initially, preprocessing of a signal is done by applying a Fractional Order Butterworth Filter (FBWF). To select the Direct ECG signal which is characterized as a reference signal and the abdominal signal which is characterized as an input signal to the WT, the cross-correlation technique is used to find the signal with greater similarity among the available four abdominal signals. The model performance of the proposed method shows the most frequent similarity of fetal heartbeat rate present in the database can be evaluated through MAE and MAPE is 0.6 and 0.041209 respectively. Thus the proposed methodology of de-noising and separation of fECG signals will act as the predominant one and assist in understanding the nature of the delivery on further analysis.
Microneurography: Recording Nerve Traffic Via Intraneural Microelectrodes in ...InsideScientific
In this webinar sponsored by ADInstruments, Professor Vaughan Macefield, one of the world’s leading neurophysiologists in the field of microneurography, speaks about the current trends in this field, and specifically shares methodology, tips and best-practices that he uses in his lab to answer complex questions about physiological processes and associated stimuli.
Key topics covered during this webinar included…
- What is Microneurography and what sort of scientific questions can it answer?
- What are the current trends in the field?
- What equipment is needed to do this type of work?
- Tips, tricks and best-practices for the Microneurography technique
- Important data acquisition and analysis processes
Background:
While many neurophysiologists use invasive techniques to record from the brain or peripheral nerves in anaesthesed animals, such approaches have – of necessity – been rather limited in human subjects. However, 50 years ago the first direct recordings of nerve activity from peripheral nerves in awake human subjects were published. In Uppsala, Sweden, Karl–Erik Hagbarth and Åke Vallbo developed the technique of “microneurography”, in which an insulated tungsten microelectrode is inserted through the skin and into a muscle or cutaneous fascicle of a peripheral (or cranial) nerve. Their original aim was to understand the population behavior of muscle spindles during voluntary contractions, but they soon discovered that they could record from individual myelinated sensory axons supplying muscle or skin. Moreover, they confirmed that the same microelectrodes could record spontaneous and evoked activity generated by the unmyelinated sympathetic axons.
Poster Presentation on "Artifact Reduction from Scalp EEG for Epilepsy Seizur...Md Kafiul Islam
This research presents a method to reduce artifacts from scalp EEG recordings to facilitate seizure diagnosis/detection for epilepsy patients. The proposed method is primarily based on stationary wavelet transform and takes the spectral band of seizure activities (i.e. 0.5 - 30 Hz) into account to separate artifacts from seizures. It requires a reference seizure epoch of N-sec which can either be generated from a patient-specific
seizure database (if available) or can be simulated by a simple mathematical model of seizure. The purpose of the algorithm is to reduce as much artifacts as possible without distorting the desired seizure events to be detected/diagnosed. Different artifact templates have been simulated to mimic the most commonly appeared artifacts in real EEG recordings. The algorithm is applied on three sets of synthesized data:
fully simulated, semi-simulated and real data to evaluate both the artifact removal performance and seizure detection performance. The EEG features responsible for detection of seizures from non-seizure epochs have been found to be easily distinguishable after artifacts are removed and consequently reduces the false alarms in seizure detection. Results from an extensive experiment with these datasets prove the efficacy of
the proposed algorithm and hence this algorithm (with some modifications) is expected to be a future candidate for artifact removal not only in epilepsy diagnosis applications but also in other applications (e.g. BCI or other neuroscience studies).
Noninvasive, Automated Measurement of Sleep, Wake and Breathing in RodentsInsideScientific
In this exclusive webinar sponsored by Signal Solutions LLC, Dr. Bruce O’Hara discusses methodology, best-practices and use studies of the PiezoSleep system. Discussion focuses on how these techniques can answer questions about animal behavior, phenotyping and relationships between sleep and disease. Dr. O’Hara also highlights the benefits of the PiezoSleep system that can assess sleep, wake and breathing variables.
Braingate is an electrode chip which can be implemented in the brain. When it is implemented in brain, the electrical signal exchanged by neurons within the brain. Those signals are sent to the brain and it executes body movement. All the signalling process is handled by special software. The signal sends to the computer and then the computer is controlled by patient.
Effective electroencephalogram based epileptic seizure detection using suppo...IJECEIAES
Epilepsy is one of the widespread disorders. It is a noncommunicable disease that affects the human nerve system. Seizures are abnormal patterns of behavior in the electricity of the brain which produce symptoms like losing consciousness, attention or convulsions in the whole body. This paper demonstrates an effective electroencephalogram (EEG) based seizure detection method using discrete wavelet transformation (DWT) for signal decomposition to extract features. An automatic channel selection method was proposed by the researcher to select the best channel from 23 channels based on maximum variance value. The records were segmented into a nonoverlapping segment with long 1-S. The support vector machine (SVM) model was used to automatically detect segments that contain seizures, using both frequency and time domain statistical moment features. The experimental result was obtained from 24 patients in CHB-MIT database. The average accuracy is 94.1, sensitivity is 93.5, specificity is 94.6 and the false positive rate average is 0.054.
Computer Aided Detection of Obstructive Sleep Apnea from EEG Signalssipij
Sleep Apnea is an anomaly in sleeping characterized by short pause in breathing. Failure to treat sleep
apnea leads to fatal complications in both psychological and physiological being of human.
Electroencephalogram (EEG) performs an important task in probing for sleep apnea through identifying
and recording the brain’s activities while sleeping. In this study, computer aided detection of sleep apnea
from EEG signals is developed to optimize and increase the prompt recognition and diagnosis of sleep
apnea in patients. The time domain, wavelets, and frequency domain of the EEG signals were computed,
and features were extracted from these domains. These features are inputted into two machine learning
algorithms: Support Vector Machine and K-Nearest Neighbors of different kernel functions and orders.
Evaluation metrics such as specificity, accuracy, and sensitivity are computed and analyzed for the
classifiers. The KNN classifier outperforms the SVM in classifying apnea from non-apnea events in
patients. The KNN order 3 shows the highest performance sensitivity of 85.92%, specificity of 80% and
accuracy of 82.69%.
Computer Aided Detection of Obstructive Sleep Apnea from EEG Signalssipij
Sleep Apnea is an anomaly in sleeping characterized by short pause in breathing. Failure to treat sleep
apnea leads to fatal complications in both psychological and physiological being of human.
Electroencephalogram (EEG) performs an important task in probing for sleep apnea through identifying
and recording the brain’s activities while sleeping. In this study, computer aided detection of sleep apnea
from EEG signals is developed to optimize and increase the prompt recognition and diagnosis of sleep
apnea in patients. The time domain, wavelets, and frequency domain of the EEG signals were computed,
and features were extracted from these domains. These features are inputted into two machine learning
algorithms: Support Vector Machine and K-Nearest Neighbors of different kernel functions and orders.
Evaluation metrics such as specificity, accuracy, and sensitivity are computed and analyzed for the
classifiers. The KNN classifier outperforms the SVM in classifying apnea from non-apnea events in
patients. The KNN order 3 shows the highest performance sensitivity of 85.92%, specificity of 80% and
accuracy of 82.69%.
Computer Aided Detection of Obstructive Sleep Apnea from EEG Signalssipij
Sleep Apnea is an anomaly in sleeping characterized by short pause in breathing. Failure to treat sleep
apnea leads to fatal complications in both psychological and physiological being of human.
Electroencephalogram (EEG) performs an important task in probing for sleep apnea through identifying
and recording the brain’s activities while sleeping. In this study, computer aided detection of sleep apnea
from EEG signals is developed to optimize and increase the prompt recognition and diagnosis of sleep
apnea in patients. The time domain, wavelets, and frequency domain of the EEG signals were computed,
and features were extracted from these domains. These features are inputted into two machine learning
algorithms: Support Vector Machine and K-Nearest Neighbors of different kernel functions and orders.
Evaluation metrics such as specificity, accuracy, and sensitivity are computed and analyzed for the
classifiers. The KNN classifier outperforms the SVM in classifying apnea from non-apnea events in
patients. The KNN order 3 shows the highest performance sensitivity of 85.92%, specificity of 80% and
accuracy of 82.69%.
Design and Implementation of wireless heart monitor for expectant mothers in ...IJMER
A low cost Maternal & Fetal Heart Rate (MFHR) monitor is introduced in an attempt to reduce or eliminate hypoxic episodes well before the development of fetal asphyxia. MFHR monitoring is sensitive and detects fetal hypoxia early in the evolution to acidosis. The abdominal electrocardiogram (AECG) is the recording of the cardiac activity of both the mother and the fetus. The main challenge is to extract the fetal ECG, which is strongly distorted by maternal component of dominating energy and artifacts like baseline wander and power-line interference which were effectively preprocessed and filtered by using a Kaiser FIR filter having a SNR ratio of 13.68 , filter order of 298 and a Notch filter (fc = 50 Hz) with a bandwidth of 2 Hz respectively. Our endeavor has been to design this MFHR monitoring device using a smartphone. This system continuously monitors the patient’s AECG data especially in the 3rd trimester. For the ongoing research work the maternal AECG signals were taken from the Physionet non-invasive ECG database. The AECG file is transferred from the PC to a microcontroller ATMEGA32A which is interfaced to a Bluetooth module. Data is then transferred wirelessly via Bluetooth to the phone. The smartphone contains an application that displays data received from the Bluetooth module interfaced with a plotter application. This Bluetooth Plotter application plots the ECG waveforms of the content on the phone. Various inferences were effectively made based upon the ECG graphs produced on the phone, thus giving the doctors an alert about the patient’s and Fetal ECG information. Further research will examine the real time patient’s data from the hospital assigned to us.
Seizure stage detection of epileptic seizure using convolutional neural networksIJECEIAES
According to the World Health Organization (WHO), seventy million individuals worldwide suffer from epilepsy, a neurological disorder. While electroencephalography (EEG) is crucial for diagnosing epilepsy and monitoring the brain activity of epilepsy patients, it requires a specialist to examine all EEG recordings to find epileptic behavior. This procedure needs an experienced doctor, and a precise epilepsy diagnosis is crucial for appropriate treatment. To identify epileptic seizures, this study employed a convolutional neural network (CNN) based on raw scalp EEG signals to discriminate between preictal, ictal, postictal, and interictal segments. The possibility of these characteristics is explored by examining how well timedomain signals work in the detection of epileptic signals using intracranial Freiburg Hospital (FH), scalp Children's Hospital Boston-Massachusetts Institute of Technology (CHB-MIT) databases, and Temple University Hospital (TUH) EEG. To test the viability of this approach, two types of experiments were carried out. Firstly, binary class classification (preictal, ictal, postictal each versus interictal) and four-class classification (interictal versus preictal versus ictal versus postictal). The average accuracy for stage detection using CHB-MIT database was 84.4%, while the Freiburg database's time-domain signals had an accuracy of 79.7% and the highest accuracy of 94.02% for classification in the TUH EEG database when comparing interictal stage to preictal stage.
SRGE Workshop on Intelligent system and Application, 27 Dec. 2017 in the framework of the int. conf of computer science, information systems, and operation research, ISSR, Cairo University
Similar to 011272 f cfm_obm_datasheet_en_us_lo-res (20)
India Clinical Trials Market: Industry Size and Growth Trends [2030] Analyzed...Kumar Satyam
According to TechSci Research report, "India Clinical Trials Market- By Region, Competition, Forecast & Opportunities, 2030F," the India Clinical Trials Market was valued at USD 2.05 billion in 2024 and is projected to grow at a compound annual growth rate (CAGR) of 8.64% through 2030. The market is driven by a variety of factors, making India an attractive destination for pharmaceutical companies and researchers. India's vast and diverse patient population, cost-effective operational environment, and a large pool of skilled medical professionals contribute significantly to the market's growth. Additionally, increasing government support in streamlining regulations and the growing prevalence of lifestyle diseases further propel the clinical trials market.
Growing Prevalence of Lifestyle Diseases
The rising incidence of lifestyle diseases such as diabetes, cardiovascular diseases, and cancer is a major trend driving the clinical trials market in India. These conditions necessitate the development and testing of new treatment methods, creating a robust demand for clinical trials. The increasing burden of these diseases highlights the need for innovative therapies and underscores the importance of India as a key player in global clinical research.
Medical Technology Tackles New Health Care Demand - Research Report - March 2...pchutichetpong
M Capital Group (“MCG”) predicts that with, against, despite, and even without the global pandemic, the medical technology (MedTech) industry shows signs of continuous healthy growth, driven by smaller, faster, and cheaper devices, growing demand for home-based applications, technological innovation, strategic acquisitions, investments, and SPAC listings. MCG predicts that this should reflects itself in annual growth of over 6%, well beyond 2028.
According to Chris Mouchabhani, Managing Partner at M Capital Group, “Despite all economic scenarios that one may consider, beyond overall economic shocks, medical technology should remain one of the most promising and robust sectors over the short to medium term and well beyond 2028.”
There is a movement towards home-based care for the elderly, next generation scanning and MRI devices, wearable technology, artificial intelligence incorporation, and online connectivity. Experts also see a focus on predictive, preventive, personalized, participatory, and precision medicine, with rising levels of integration of home care and technological innovation.
The average cost of treatment has been rising across the board, creating additional financial burdens to governments, healthcare providers and insurance companies. According to MCG, cost-per-inpatient-stay in the United States alone rose on average annually by over 13% between 2014 to 2021, leading MedTech to focus research efforts on optimized medical equipment at lower price points, whilst emphasizing portability and ease of use. Namely, 46% of the 1,008 medical technology companies in the 2021 MedTech Innovator (“MTI”) database are focusing on prevention, wellness, detection, or diagnosis, signaling a clear push for preventive care to also tackle costs.
In addition, there has also been a lasting impact on consumer and medical demand for home care, supported by the pandemic. Lockdowns, closure of care facilities, and healthcare systems subjected to capacity pressure, accelerated demand away from traditional inpatient care. Now, outpatient care solutions are driving industry production, with nearly 70% of recent diagnostics start-up companies producing products in areas such as ambulatory clinics, at-home care, and self-administered diagnostics.
Navigating Challenges: Mental Health, Legislation, and the Prison System in B...Guillermo Rivera
This conference will delve into the intricate intersections between mental health, legal frameworks, and the prison system in Bolivia. It aims to provide a comprehensive overview of the current challenges faced by mental health professionals working within the legislative and correctional landscapes. Topics of discussion will include the prevalence and impact of mental health issues among the incarcerated population, the effectiveness of existing mental health policies and legislation, and potential reforms to enhance the mental health support system within prisons.
We understand the unique challenges pickleball players face and are committed to helping you stay healthy and active. In this presentation, we’ll explore the three most common pickleball injuries and provide strategies for prevention and treatment.
CHAPTER 1 SEMESTER V - ROLE OF PEADIATRIC NURSE.pdfSachin Sharma
Pediatric nurses play a vital role in the health and well-being of children. Their responsibilities are wide-ranging, and their objectives can be categorized into several key areas:
1. Direct Patient Care:
Objective: Provide comprehensive and compassionate care to infants, children, and adolescents in various healthcare settings (hospitals, clinics, etc.).
This includes tasks like:
Monitoring vital signs and physical condition.
Administering medications and treatments.
Performing procedures as directed by doctors.
Assisting with daily living activities (bathing, feeding).
Providing emotional support and pain management.
2. Health Promotion and Education:
Objective: Promote healthy behaviors and educate children, families, and communities about preventive healthcare.
This includes tasks like:
Administering vaccinations.
Providing education on nutrition, hygiene, and development.
Offering breastfeeding and childbirth support.
Counseling families on safety and injury prevention.
3. Collaboration and Advocacy:
Objective: Collaborate effectively with doctors, social workers, therapists, and other healthcare professionals to ensure coordinated care for children.
Objective: Advocate for the rights and best interests of their patients, especially when children cannot speak for themselves.
This includes tasks like:
Communicating effectively with healthcare teams.
Identifying and addressing potential risks to child welfare.
Educating families about their child's condition and treatment options.
4. Professional Development and Research:
Objective: Stay up-to-date on the latest advancements in pediatric healthcare through continuing education and research.
Objective: Contribute to improving the quality of care for children by participating in research initiatives.
This includes tasks like:
Attending workshops and conferences on pediatric nursing.
Participating in clinical trials related to child health.
Implementing evidence-based practices into their daily routines.
By fulfilling these objectives, pediatric nurses play a crucial role in ensuring the optimal health and well-being of children throughout all stages of their development.
Welcome to Secret Tantric, London’s finest VIP Massage agency. Since we first opened our doors, we have provided the ultimate erotic massage experience to innumerable clients, each one searching for the very best sensual massage in London. We come by this reputation honestly with a dynamic team of the city’s most beautiful masseuses.
Global launch of the Healthy Ageing and Prevention Index 2nd wave – alongside...ILC- UK
The Healthy Ageing and Prevention Index is an online tool created by ILC that ranks countries on six metrics including, life span, health span, work span, income, environmental performance, and happiness. The Index helps us understand how well countries have adapted to longevity and inform decision makers on what must be done to maximise the economic benefits that comes with living well for longer.
Alongside the 77th World Health Assembly in Geneva on 28 May 2024, we launched the second version of our Index, allowing us to track progress and give new insights into what needs to be done to keep populations healthier for longer.
The speakers included:
Professor Orazio Schillaci, Minister of Health, Italy
Dr Hans Groth, Chairman of the Board, World Demographic & Ageing Forum
Professor Ilona Kickbusch, Founder and Chair, Global Health Centre, Geneva Graduate Institute and co-chair, World Health Summit Council
Dr Natasha Azzopardi Muscat, Director, Country Health Policies and Systems Division, World Health Organisation EURO
Dr Marta Lomazzi, Executive Manager, World Federation of Public Health Associations
Dr Shyam Bishen, Head, Centre for Health and Healthcare and Member of the Executive Committee, World Economic Forum
Dr Karin Tegmark Wisell, Director General, Public Health Agency of Sweden
Antibiotic Stewardship by Anushri Srivastava.pptxAnushriSrivastav
Stewardship is the act of taking good care of something.
Antimicrobial stewardship is a coordinated program that promotes the appropriate use of antimicrobials (including antibiotics), improves patient outcomes, reduces microbial resistance, and decreases the spread of infections caused by multidrug-resistant organisms.
WHO launched the Global Antimicrobial Resistance and Use Surveillance System (GLASS) in 2015 to fill knowledge gaps and inform strategies at all levels.
ACCORDING TO apic.org,
Antimicrobial stewardship is a coordinated program that promotes the appropriate use of antimicrobials (including antibiotics), improves patient outcomes, reduces microbial resistance, and decreases the spread of infections caused by multidrug-resistant organisms.
ACCORDING TO pewtrusts.org,
Antibiotic stewardship refers to efforts in doctors’ offices, hospitals, long term care facilities, and other health care settings to ensure that antibiotics are used only when necessary and appropriate
According to WHO,
Antimicrobial stewardship is a systematic approach to educate and support health care professionals to follow evidence-based guidelines for prescribing and administering antimicrobials
In 1996, John McGowan and Dale Gerding first applied the term antimicrobial stewardship, where they suggested a causal association between antimicrobial agent use and resistance. They also focused on the urgency of large-scale controlled trials of antimicrobial-use regulation employing sophisticated epidemiologic methods, molecular typing, and precise resistance mechanism analysis.
Antimicrobial Stewardship(AMS) refers to the optimal selection, dosing, and duration of antimicrobial treatment resulting in the best clinical outcome with minimal side effects to the patients and minimal impact on subsequent resistance.
According to the 2019 report, in the US, more than 2.8 million antibiotic-resistant infections occur each year, and more than 35000 people die. In addition to this, it also mentioned that 223,900 cases of Clostridoides difficile occurred in 2017, of which 12800 people died. The report did not include viruses or parasites
VISION
Being proactive
Supporting optimal animal and human health
Exploring ways to reduce overall use of antimicrobials
Using the drugs that prevent and treat disease by killing microscopic organisms in a responsible way
GOAL
to prevent the generation and spread of antimicrobial resistance (AMR). Doing so will preserve the effectiveness of these drugs in animals and humans for years to come.
being to preserve human and animal health and the effectiveness of antimicrobial medications.
to implement a multidisciplinary approach in assembling a stewardship team to include an infectious disease physician, a clinical pharmacist with infectious diseases training, infection preventionist, and a close collaboration with the staff in the clinical microbiology laboratory
to prevent antimicrobial overuse, misuse and abuse.
to minimize the developme
1. Continuous bedside cerebral function
monitoring – providing actionable
information when you
need it most…
newborn care
www.natus.com
Amplitude-integrated EEG is the most commonly used digital trend for
newborns and it’s use has been integrated as a customary practice for
assessment of EEG background in many intensive care nurseries.1
The Olympic Brainz Monitor is the latest technology
in cerebral function monitoring (CFM), allowing you to
begin monitoring in 3 easy steps: Plug in unit, apply
electrodes and start recording.
CFM
Olympic Brainz Monitor
2. Understanding an infant’s brain health is a critical part of your treatment decisions. Use of continuous Cerebral
Function Monitoring provides vital information to clinicians to assist with earlier diagnosis and treatment2
–
the Olympic Brainz Monitor is the optimal CFM solution for fast & simple routine bedside monitoring.
The Olympic Brainz Monitor provides aEEG, real time EEG and continuous measurement of impedance in up to
3 channels.The NICU friendly interface allows real time monitoring of brain function, providing vital data that
may assist in predicting outcomes.
Clinical Usage of aEEG Monitoring
Medical literature reports that aEEG monitoring can be used to:
• Monitor general neurological status
• Monitor and record seizures3
• Monitor during hypothermic treatment to measure the effectiveness
of treatment4
-- The time to normal trace (TTNT) has prognostic value and is a good
predictor of neurodevelopment outcome in term infants with Hypoxic-
Ischemic Encephalopathy (HIE) undergoing hypothermic treatment5
• Monitor aEEG patterns to indicate the presence of sleep wake cycling
(cyclicity) in term and preterm infants, which is associated with better
outcomes in HIE patients6
and may add value in developmental care
Ease of Operation
• System-based online help feature provides a step-by-step guide for
setting up both the system and patient prep – allowing staff to start
monitoring in minutes
• Intuitive navigation allows access to information fast when you need
it most
• Versatile patient settings
-- Easily add a channel to an existing single channel setup
-- Cross cerebral, right and left hemisphere with up to 3-channel
monitoring simplifies patient hook up and provides additional data
when needed
CFMsight
• Provides enhanced signal display for easier trace interpretation
Trace appears CNV based on margins
(however SWC is absent)
• The same trace with CFMsight enabled displays a narrow dark band in
the lower margin, suggesting the possibility of a falsely elevated lower
margin due to EKG artifact
• With the confirmation of EKG artifact in the raw EEG, the actual lower
margin would be interpreted as being close to zero, which would be
more consistent with severe injury and a burst suppression pattern
Without CFMsight: With CFMsight:
3. Monitor neurological status sooner
– help the newborn faster
www.natus.com
Ease of interpretation and collaboration
CFM Viewer
• CFM Viewer software implements similar functionality to the bedside
unit, permitting review and analysis of recorded CFM data away from
the bedside
• Remote review and consultation – offers remote viewing of active or
stored recordings from any location
-- Simplifies consultation
-- Provides remote review and annotation of patient recordings with
marked events appearing at bedside
• Web-based
Event markers
• User-customizable, time-stamped markers keep track of when
medications are administered, making the review process more efficient
and easier for cross collaboration
• Different colors designate whether markers were placed at bedside or using
Viewer from a remote location
File management and printing options
• Network archiving feature allows transfer of sessions and facilitates file
management by increasing speed of transfer
• Network printer connectivity simplifies charting and record keeping,
saving cost by allowing printing onto standard paper
• Archive, restore and review patient files via USB, allowing data
management even when not connected to the hospital network
Consumables
Electrodes
• Both hydrogel and needle electrodes are supported through standard
touch-proof connectors located on the amplifier housing
