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What is brain-computer interfaces (BCIs)
What is brain-computer interfaces (BCIs)
In the beginning of the speech, professor Tzyy-Ping Jung explained what is brain computer interfaces? BCIs is a direct communication pathway between a brain and an external device. BCIs are often aimed at replacing, assisting, augmenting or repairing human cognitive or sensory-motor functions.
In the beginning of the speech, professor Tzyy-Ping Jung explained what is brain computer interfaces? BCIs is a direct communication pathway between a brain and an external device. BCIs are often aimed at replacing, assisting, augmenting or repairing human cognitive or sensory-motor functions.
Big and crucial issues in BCIs
Big and crucial issues in BCIs
The past thirty years have witness remarkable advances in fundamental neuroscience research and next generation neurotechnology. Among the major forerunners in these areas are brain-computer interfaces (BCIs). However, even with immense advancements. BCIs are still not in widespread and daily use, except for some exciting neuroprosthetic studies recovering lost functions of patients. We need to understand and more importantly overcome the obstacles or challenges that impede the widespread use of BCIs. Moreover, professor Tzyy-Ping Jung mentioned that we lack new sensors and technologies to measure high-quality neural, physiological, behavioral, and contextual data in real-world environments. In real life, we have to find our target. Professor Tzyy-Ping Jung mentioned that in education, whether you want to know how children learn is a very important issue.
The past thirty years have witness remarkable advances in fundamental neuroscience research and next generation neurotechnology. Among the major forerunners in these areas are brain-computer interfaces (BCIs). However, even with immense advancements. BCIs are still not in widespread and daily use, except for some exciting neuroprosthetic studies recovering lost functions of patients. We need to understand and more importantly overcome the obstacles or challenges that impede the widespread use of BCIs. Moreover, professor Tzyy-Ping Jung mentioned that we lack new sensors and technologies to measure high-quality neural, physiological, behavioral, and contextual data in real-world environments. In real life, we have to find our target. Professor Tzyy-Ping Jung mentioned that in education, whether you want to know how children learn is a very important issue.
Mobile Brain/Body Imaging (MoBI)
Mobile Brain/Body Imaging (MoBI)
There are a lot of challenges with the MoBI technology. It has gained increasing attention and made a lot of progress in recent years. However, there is still room for improvement. The technology is restricted to well- controlled laboratory environments. In summary, professor Tzyy-Ping Jung mentioned that we have developed and disseminated open-source software for the interpretation of neural, physiological, and behavioral data. Also, his study showed that the eye fixation duration and fixationrelated EEG can predict the likelihood of responding with correct answers. Finally, he developed a wearable and easily deployable system, based on VR HMD and mfSSVEP BCI, to assess visual field loss in patients with glaucoma.
There are a lot of challenges with the MoBI technology. It has gained increasing attention and made a lot of progress in recent years. However, there is still room for improvement. The technology is restricted to well- controlled laboratory environments. In summary, professor Tzyy-Ping Jung mentioned that we have developed and disseminated open-source software for the interpretation of neural, physiological, and behavioral data. Also, his study showed that the eye fixation duration and fixationrelated EEG can predict the likelihood of responding with correct answers. Finally, he developed a wearable and easily deployable system, based on VR HMD and mfSSVEP BCI, to assess visual field loss in patients with glaucoma.
學生優良心得(一)
學生優良心得(一)
Part 1. (概要)
Part 1. (概要)
- What is Brain-Computer Interfaces(BCIs)?
- Big and Crucial Issues in BCIs
- Recent progress in resolving BCIs in BCIs
- Sample BCI studies
We lack new sensors and technologies to measure high-quality neural, physiological, behavioral, and contextual data in real-world environments.
We lack new sensors and technologies to measure high-quality neural, physiological, behavioral, and contextual data in real-world environments.
Advanced signal-processing…
Advanced signal-processing…
All sensors are heavy except the EEG.
All sensors are heavy except the EEG.
Pros and cons on each methods
Pros and cons on each methods
Part 2. (心得)
Part 2. (心得)
As a teacher, not only should we know how to teach, but we also need to understand how the brain works. We may have the need to know the measurements of detecting one’s brainwave. It can be applied to show the shape form of our learning in different subjects. There are ways to do so. Advanced sensors and sensing technologies can do help. We should know briefly what is BCIs.
As a teacher, not only should we know how to teach, but we also need to understand how the brain works. We may have the need to know the measurements of detecting one’s brainwave. It can be applied to show the shape form of our learning in different subjects. There are ways to do so. Advanced sensors and sensing technologies can do help. We should know briefly what is BCIs.
Brain-computer interface(BCIs), is a direct communication pathway between an enhanced or wired brain and an external device. BCI differs from neuromodulation in that it allows for bidirectional information flow. BCIs are often directed at researching, mapping, assisting, augmenting, or repairing human cognitive or sensory-motor functions.
Brain-computer interface(BCIs), is a direct communication pathway between an enhanced or wired brain and an external device. BCI differs from neuromodulation in that it allows for bidirectional information flow. BCIs are often directed at researching, mapping, assisting, augmenting, or repairing human cognitive or sensory-motor functions.
For measurements, we have EEG, fMRI, and so forth. With these, we are able to detect signals from our brain, even the waveform when the interaction with person to person or the time the person is running can be recorded. Thus, we can comprehend how the students’ thoughts.
For measurements, we have EEG, fMRI, and so forth. With these, we are able to detect signals from our brain, even the waveform when the interaction with person to person or the time the person is running can be recorded. Thus, we can comprehend how the students’ thoughts.
Given an e-keyboard, with 1 shining at the frequency of 10 Hz, and 5 doing at 15 Hz, the student is looking at 1(the scientist doesn’t know). Then, we would get the graph of the wave from the student’s by EEG. Finally, we analyze the wave, get the frequency which should be 10(Hz), and know that he is looking at 1.
Given an e-keyboard, with 1 shining at the frequency of 10 Hz, and 5 doing at 15 Hz, the student is looking at 1(the scientist doesn’t know). Then, we would get the graph of the wave from the student’s by EEG. Finally, we analyze the wave, get the frequency which should be 10(Hz), and know that he is looking at 1.
I think it beneficial to helping students learning abstract concepts. For example, when the concept is difficult to learn, the amplitude of the wave should be rolling and falling heavily. Then, teachers can give more illustrations at that point. It also has the function of detecting how the students’ response.
I think it beneficial to helping students learning abstract concepts. For example, when the concept is difficult to learn, the amplitude of the wave should be rolling and falling heavily. Then, teachers can give more illustrations at that point. It also has the function of detecting how the students’ response.
學生優良心得(二)
學生優良心得(二)
Today we meet Professor Tzyy Ping Jung- Director of Neuroscience and Center for Advanced Neurological Engineering. He had a lot of achievement and scholarship when he was a university student. He graduated in National Chiao Tung University in Hsinchu Taiwan and also learnt Phd Department of Electronic. And this professor also explain to our faculty about BCIs. There are three plans that professor want to explain. Firstly, he want us to know what is the brain computer interfaces( BCIs). Brain computer interfaces sometimes called a brain machine interface, is a direct communication pathway between an enhanced or wired brain and an external device. It differs from neuromodulation in that it allows bidirectional information flow. And they are often directed in mapping, assisting, repairing human cognitive and sensory motor functions.
Today we meet Professor Tzyy Ping Jung- Director of Neuroscience and Center for Advanced Neurological Engineering. He had a lot of achievement and scholarship when he was a university student. He graduated in National Chiao Tung University in Hsinchu Taiwan and also learnt Phd Department of Electronic. And this professor also explain to our faculty about BCIs. There are three plans that professor want to explain. Firstly, he want us to know what is the brain computer interfaces( BCIs). Brain computer interfaces sometimes called a brain machine interface, is a direct communication pathway between an enhanced or wired brain and an external device. It differs from neuromodulation in that it allows bidirectional information flow. And they are often directed in mapping, assisting, repairing human cognitive and sensory motor functions.
Secondly, he want to explain the Big and Crucial Issues in BCIs. In the past thirty years have witnessed remarkable advances in fundamental neuroscience research and next generation neurotechnologies. Among the major forerunners in these areas are brain computer interfaces. However, even with immerse advancements, BCIs are still not in widespread and routine use, except for some exciting neuroprosthetic studies recovering lost functions of patients. We need to understand and more importantly overcome the obstacles or challenges that impede the widespread use of BCIs. Because we lack new sensors and technologies to measure high quality neural, physiological, behavioral, and contextual data in real world enviroments. And also, we need advanced signal- processing and machine learning algonrithms to jointly anylyze multi modal data.
Secondly, he want to explain the Big and Crucial Issues in BCIs. In the past thirty years have witnessed remarkable advances in fundamental neuroscience research and next generation neurotechnologies. Among the major forerunners in these areas are brain computer interfaces. However, even with immerse advancements, BCIs are still not in widespread and routine use, except for some exciting neuroprosthetic studies recovering lost functions of patients. We need to understand and more importantly overcome the obstacles or challenges that impede the widespread use of BCIs. Because we lack new sensors and technologies to measure high quality neural, physiological, behavioral, and contextual data in real world enviroments. And also, we need advanced signal- processing and machine learning algonrithms to jointly anylyze multi modal data.
Thirdly, professor also answers that there are some recent progress in resolving BCIS in BCIs. BCIs is a well-controlled laboratory, mobile brain and body imaging. They move technology to visual search in a VR environment. In 1995, he and his team had developed Independent Component Analysis. ICA is a method to recovery a version, of original sources by multiplying the data in a unmixing matrix. When PCA simply decorates the outputs using an orthogonal matrix, W1,ICA attempts to make the outputs statically independent, while placing no constraints on th matrix W. Finally, professor also shows us a lot of samples of BCIs studies. Like Neuroimaging modality for Real World BCIs- In all modalities but EEG, the sensors are heavy. EEG is the only modality that does not require the head body to be fixed. It also might enable the monitoring brain functions of unconstrained participants performing normal tasks in the workplace and home. The second sample is Mobi technology, which has gained increasing attention and made a lot of progress in recent years.
Thirdly, professor also answers that there are some recent progress in resolving BCIS in BCIs. BCIs is a well-controlled laboratory, mobile brain and body imaging. They move technology to visual search in a VR environment. In 1995, he and his team had developed Independent Component Analysis. ICA is a method to recovery a version, of original sources by multiplying the data in a unmixing matrix. When PCA simply decorates the outputs using an orthogonal matrix, W1,ICA attempts to make the outputs statically independent, while placing no constraints on th matrix W. Finally, professor also shows us a lot of samples of BCIs studies. Like Neuroimaging modality for Real World BCIs- In all modalities but EEG, the sensors are heavy. EEG is the only modality that does not require the head body to be fixed. It also might enable the monitoring brain functions of unconstrained participants performing normal tasks in the workplace and home. The second sample is Mobi technology, which has gained increasing attention and made a lot of progress in recent years.
However, there is still room for environment. The bio- sensing modalities are typically bulky, costly, inconvenient, and labor- intensive. Secondly, the technology is restricted to well- controlled laboratory environments. And existing systems lack a method to automatically tag cognitively meaningful events. Last but not least, there are 11 commercially available health monitoring devices like thermometer measure body temperature, blood pressure monitor, pregnancy tests, smart weight scale and so on. Until the end of the represent, professor also summarizes all the things that we have listened. First, we have development advanced sensors and sensing technologies for measuring neural, physiological, and behavioral data from unconstrained subjects in real world environments. Secondly, we have developed and disseminated open source software for the interpretation of neural physiological, and behavioral data. Thirdly, our pilot study showed that the eye fixation duration and fixation related EEG can predict the likelihood of responding with correct answers. Finally, we developed a wearable and easily deployable system, based on a VR HMD and mfS5VEP BCI, to assess visual field loss in patients with glaucomia.
However, there is still room for environment. The bio- sensing modalities are typically bulky, costly, inconvenient, and labor- intensive. Secondly, the technology is restricted to well- controlled laboratory environments. And existing systems lack a method to automatically tag cognitively meaningful events. Last but not least, there are 11 commercially available health monitoring devices like thermometer measure body temperature, blood pressure monitor, pregnancy tests, smart weight scale and so on. Until the end of the represent, professor also summarizes all the things that we have listened. First, we have development advanced sensors and sensing technologies for measuring neural, physiological, and behavioral data from unconstrained subjects in real world environments. Secondly, we have developed and disseminated open source software for the interpretation of neural physiological, and behavioral data. Thirdly, our pilot study showed that the eye fixation duration and fixation related EEG can predict the likelihood of responding with correct answers. Finally, we developed a wearable and easily deployable system, based on a VR HMD and mfS5VEP BCI, to assess visual field loss in patients with glaucomia.
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