400.00 EUR
QEEG-040523-EN
ONLINE
Start Date: May 4, 2023, 10:00
Finish date: May 6, 2023, 18:00
2020
Quantitative EEG (QEEG) with Swingle Clinical Q
Quantitative Electroencephalography (QEEG) is an advanced technique that involves the computerized analysis of EEG data, enabling a more comprehensive understanding of brain activity.
The utilization of Quantitative EEG (QEEG) offers significant advantages in the realm of mental disorder diagnosis and analysis. By employing state-of-the-art data processing and EEG database matching, QEEG reveals disorders through a series of brain maps that display biomarkers associated with a wide range of mental conditions. This approach substantially broadens diagnostic capabilities, enabling the identification of the biological underpinnings of numerous mental disorders such as ADHD, depression, anxiety, autism, and learning disabilities.
Incorporating QEEG into the diagnosis and evaluation of mental disorders is essential for practitioners striving to stay current in their field. With its capacity to deliver enhanced accuracy, objectivity, and sensitivity, QEEG enables the creation of tailored treatment strategies and continuous monitoring, ultimately leading to improved therapeutic results.
The four main reasons why to use QEEG
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1. Enhanced precision: QEEG quantifies brainwave patterns, offering a higher level of detail and accuracy compared to conventional visual inspection of EEG data. This increased precision facilitates better identification of abnormalities and a more accurate diagnosis.
2. Objective assessment: QEEG relies on statistical analysis, removing subjectivity from the diagnostic process. This objectivity ensures consistent and reliable results, promoting more accurate diagnoses and treatment recommendations.
3. Sensitivity to subtle abnormalities: QEEG is capable of detecting subtle deviations in brainwave patterns that may be indicative of mental disorders. These nuances might be overlooked during standard EEG evaluations, making QEEG a valuable tool for identifying a broader range of conditions.
4. Personalized treatment planning: The detailed information obtained from QEEG assessments enables healthcare professionals to develop tailored treatment plans for individual patients. This customization leads to more effective interventions and better therapeutic outcomes.
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What can I learn in the QEEG course offered by IFEN?
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Recognizing typical patterns of neuropathological and psychophysiological dysregulation: The ability to discern distinct EEG patterns correlated with particular neurological or psychophysiological imbalances plays a vital role in ensuring accurate diagnoses and devising effective treatment plans. By understanding these characteristic patterns, clinicians can better identify underlying issues and develop targeted interventions for patients suffering from mental disorders.
- Connecting data with the client's individual clinical profile: Combining the quantitative information gathered from QEEG with the client's specific clinical presentation enables a holistic understanding of their condition. This integrated approach facilitates the development of personalized treatment plans tailored to the unique needs of each patient.
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Reliable creation of protocols: Developing consistent and reproducible protocols for EEG data acquisition, analysis, and interpretation ensures that results are accurate, reliable, and comparable across different sessions and clients.
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Recording of clean data: Ensuring high-quality data acquisition is vital for reliable analysis.
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Use of different EEG caps: Utilizing various types of EEG caps, such as those with wet or dry electrodes and caps with different electrode configurations or densities, allows for flexibility and adaptability in recording EEG data based on the specific needs of the assessment and the client's individual characteristic neuropathology.
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- Different methods of artifact correction
- Detecting Peak Frequency
- Managing difficult recording situations
- EEG Patterns and Biomarkers
- Using different programs for QEEG-Analysis
Swingle Clinical Q
Dr. Paul G. Swingle's quantitative EEG assessment is an exceptionally potent evaluation instrument for any neurofeedback practice. With a high degree of accuracy and efficiency, it can rapidly identify EEG abnormalities that are frequently linked to conditions such as ADHD, anxiety, burnout, depression, and developmental disorders. The Clinical Q method gathers amplitude data from five sequential single-channel EEG leads in just six minutes.
Curriculum
Day 1
- Electroencephalography in the clinic
- EEG technique and basic understanding of normal and abnormal EEG patterns
- Recognition and removal of artefacts
- Learning to use brain mapping software
- Finding and training clinically abnormal locations in the 10/20 system
- Characteristics of typical brain maps for depression, ADHD, anxiety, trauma, traumatic brain injury, post-traumatic stress disorder, autism, Asperger's, etc.
- Introduction to the use of the NeuroGuide software
Day 2
- Recording technique of the QEEG
- Acquisition of data, editing with Neuroguide and Brain Avatar
- Data acquisition (program execution)
- Normative EEG patterns using database comparisons
- Effects of drugs on the EEG
- Networks, hubs, and correlation of symptoms with protocol selection
- Neurofeedback in learning disorders, traumatic brain injury
- Multi-channel neurofeedback with symptom check-list technique
- 3-D Loreta training and ROI training with and without Z-scores
- Comparison of Z-scores to symptoms with neurology
Day 3
- T/B ratio
- Total amplitude
- Ratio to task and resting EEG
- Ratio EO to EC measurement
- Stress level indicators
- IQ indicators
- Biomarkers for anxiety and depression
- Difference to 19-channel QEEG
Required hardware/ software
QEEG is indeed based on the conventional 19-channel EEG setup. If you have any specific inquiries about your existing equipment or are considering purchasing new equipment, please feel free to ask, and we would be happy to assist you with your questions.
Workshop language
The workshop is in English Language
Subject to change
