{"id":4572,"date":"2020-06-24T10:29:06","date_gmt":"2020-06-24T02:29:06","guid":{"rendered":"http:\/\/pairlabs.ai.pro6.designworks.tw\/?post_type=portfolio&#038;p=4572"},"modified":"2021-12-21T17:29:39","modified_gmt":"2021-12-21T09:29:39","slug":"development-of-artificial-intelligence-based-brain-computer-interface-p-en","status":"publish","type":"portfolio","link":"https:\/\/pairlabs.ai\/en\/portfolio-item\/development-of-artificial-intelligence-based-brain-computer-interface-p-en\/","title":{"rendered":"Intelligent Interactive Platform with Applications to Healthcare and Home Care \u2013 Development of Artificial Intelligence \u2013 based Brain Computer Interface"},"content":{"rendered":"<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='av_section_1' class='avia-section main_color avia-section-large avia-no-border-styling avia-full-stretch av-section-color-overlay-active avia-bg-style-fixed    av-small-hide av-mini-hide container_wrap sidebar_right' style='background-repeat: no-repeat; background-image: url(https:\/\/pairlabs.ai\/wp-content\/uploads\/2020\/05\/wall005.jpg);background-attachment: fixed; background-position: bottom right;  '  data-section-bg-repeat='stretch' style='background-repeat: no-repeat; background-image: url(https:\/\/pairlabs.ai\/wp-content\/uploads\/2020\/05\/wall005.jpg);background-attachment: fixed; background-position: bottom right;  ' ><div class='av-section-color-overlay-wrap'><div class='av-section-color-overlay' style='opacity: 0.6; background-color: #ffffff; '><\/div><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4572'><div class='entry-content-wrapper clearfix'>\n<div class='flex_column_table av-equal-height-column-flextable -flextable' style='margin-top:0px; margin-bottom:-20px; '><div class=\"flex_column av_one_fourth  flex_column_table_cell av-equal-height-column av-align-top av-zero-column-padding first   \" style='border-radius:0px; '><\/div><\/div><!--close column table wrapper. Autoclose: 1 --><div class='flex_column_table av-equal-height-column-flextable -flextable' style='margin-top:0px; margin-bottom:-20px; '><div class='av-flex-placeholder'><\/div><div class=\"flex_column av_one_half  flex_column_table_cell av-equal-height-column av-align-top av-zero-column-padding   \" style='border-radius:0px; '><section class=\"av_textblock_section \"  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div class='avia_textblock  '  style='font-size:20px; '  itemprop=\"text\" ><p style=\"text-align: center;\">Pervasive Artificial Intelligence Research (PAIR) Labs<\/p>\n<\/div><\/section><br \/>\n<div style='height:20px' class='hr hr-invisible   '><span class='hr-inner ' ><span class='hr-inner-style'><\/span><\/span><\/div><\/p><\/div><\/div><!--close column table wrapper. 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Autoclose: 1 --><div class='flex_column_table av-equal-height-column-flextable -flextable' ><div class='av-flex-placeholder'><\/div><div class=\"flex_column av_one_half  flex_column_table_cell av-equal-height-column av-align-top    \" style='background-color:#00a0e9; background:linear-gradient(to bottom right,#00a0e9,#25a98f); padding:10px; border-radius:0px; '><p><div style=' margin-top:-21px; margin-bottom:0px;'  class='hr hr-custom hr-center hr-icon-yes   '><span class='hr-inner   inner-border-av-border-thin' style=' width:0px;' ><span class='hr-inner-style'><\/span><\/span><span class='av-seperator-icon' style='color:#ffffff;' aria-hidden='true' data-av_icon='\ue883' data-av_iconfont='entypo-fontello'><\/span><span class='hr-inner   inner-border-av-border-thin' style=' width:0px;' ><span class='hr-inner-style'><\/span><\/span><\/div><br \/>\n<section class=\"av_textblock_section \"  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div class='avia_textblock  av_inherit_color '  style='font-size:30px; color:#ffffff; '  itemprop=\"text\" ><h1 style=\"text-align: center;\">Home care Team<\/h1>\n<\/div><\/section><\/p><\/div><\/div><!--close column table wrapper. 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Autoclose: 1 -->\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><\/div><div id='after_section_1' class='main_color av_default_container_wrap container_wrap sidebar_right' style=' '   style=' ' ><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4572'><div class='entry-content-wrapper clearfix'>\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='av_section_2' class='avia-section main_color avia-section-large avia-no-border-styling avia-full-stretch av-section-color-overlay-active avia-bg-style-fixed    av-desktop-hide av-medium-hide container_wrap sidebar_right' style='background-repeat: no-repeat; background-image: url(https:\/\/pairlabs.ai\/wp-content\/uploads\/2020\/05\/wall005.jpg);background-attachment: fixed; background-position: bottom right;  '  data-section-bg-repeat='stretch' style='background-repeat: no-repeat; background-image: url(https:\/\/pairlabs.ai\/wp-content\/uploads\/2020\/05\/wall005.jpg);background-attachment: fixed; background-position: bottom right;  ' ><div class='av-section-color-overlay-wrap'><div class='av-section-color-overlay' style='opacity: 0.6; background-color: #ffffff; '><\/div><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4572'><div class='entry-content-wrapper clearfix'>\n<div class='flex_column_table av-equal-height-column-flextable -flextable' style='margin-top:0px; margin-bottom:-20px; '><div class=\"flex_column av_one_fourth  flex_column_table_cell av-equal-height-column av-align-top av-zero-column-padding first   \" style='border-radius:0px; '><\/div><\/div><!--close column table wrapper. Autoclose: 1 --><div class='flex_column_table av-equal-height-column-flextable -flextable' style='margin-top:0px; margin-bottom:-20px; '><div class='av-flex-placeholder'><\/div><div class=\"flex_column av_one_half  flex_column_table_cell av-equal-height-column av-align-top av-zero-column-padding   \" style='border-radius:0px; '><section class=\"av_textblock_section \"  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div class='avia_textblock  '  style='font-size:20px; '  itemprop=\"text\" ><p style=\"text-align: center;\">Pervasive Artificial Intelligence Research (PAIR) Labs<\/p>\n<\/div><\/section><br \/>\n<div style='height:1px' class='hr hr-invisible   '><span class='hr-inner ' ><span class='hr-inner-style'><\/span><\/span><\/div><\/p><\/div><\/div><!--close column table wrapper. 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Autoclose: 1 --><div class='flex_column_table av-equal-height-column-flextable -flextable' ><div class='av-flex-placeholder'><\/div><div class=\"flex_column av_one_half  flex_column_table_cell av-equal-height-column av-align-top    \" style='background-color:#00a0e9; background:linear-gradient(to bottom right,#00a0e9,#25a98f); padding:10px; border-radius:0px; '><p><div style=' margin-top:-21px; margin-bottom:0px;'  class='hr hr-custom hr-center hr-icon-yes   '><span class='hr-inner   inner-border-av-border-thin' style=' width:0px;' ><span class='hr-inner-style'><\/span><\/span><span class='av-seperator-icon' style='color:#ffffff;' aria-hidden='true' data-av_icon='\ue883' data-av_iconfont='entypo-fontello'><\/span><span class='hr-inner   inner-border-av-border-thin' style=' width:0px;' ><span class='hr-inner-style'><\/span><\/span><\/div><br \/>\n<section class=\"av_textblock_section \"  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div class='avia_textblock  av_inherit_color '  style='font-size:30px; color:#ffffff; '  itemprop=\"text\" ><h2 style=\"text-align: center;\">Home care Team<\/h2>\n<\/div><\/section><\/p><\/div><\/div><!--close column table wrapper. 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Autoclose: 1 -->\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><\/div><div id='after_section_2' class='main_color av_default_container_wrap container_wrap sidebar_right' style=' '   style=' ' ><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4572'><div class='entry-content-wrapper clearfix'>\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='av_section_3' class='avia-section socket_color avia-section-default avia-no-border-styling avia-bg-style-scroll    av-arrow-down-section container_wrap sidebar_right' style=' '   style=' ' ><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4572'><div class='entry-content-wrapper clearfix'>\n<div style='padding-bottom:0px; margin:0 0 0 0; font-size:30px;' class='av-special-heading av-special-heading-h3  blockquote modern-quote modern-centered   av-inherit-size '><h3 class='av-special-heading-tag '  itemprop=\"headline\"  >Intelligent Interactive Platform with Applications to Healthcare and Home Care \u2013 Development of Artificial Intelligence \u2013 based Brain Computer Interface<\/h3><div class='special-heading-border'><div class='special-heading-inner-border' ><\/div><\/div><\/div>\n<\/div><\/div><\/div><!-- close content main div --><\/div><div class='av-extra-border-element border-extra-arrow-down'><div class='av-extra-border-outer'><div class='av-extra-border-inner'  style='background-color:#333333;' ><\/div><\/div><\/div><\/div><div id='after_section_3' class='main_color av_default_container_wrap container_wrap sidebar_right' style=' '   style=' ' ><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4572'><div class='entry-content-wrapper clearfix'><\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='av_section_4' class='avia-section main_color avia-section-default avia-no-border-styling avia-bg-style-scroll   container_wrap sidebar_right' style=' '   style=' ' ><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4572'><div class='entry-content-wrapper clearfix'>\n<div class=\"flex_column av_three_fifth  flex_column_div av-zero-column-padding first  \" style='border-radius:0px; '><section class=\"av_textblock_section \"  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div class='avia_textblock  '   itemprop=\"text\" ><p><b>Principal Investigator:<\/b><a href=\"https:\/\/pairlabs.ai\/en\/portfolio-item\/professor-kuo-kai-shyu-pi-en\/\">Professor Kuo-Kai Shyu<\/a><\/p>\n<p>&#8212;<\/p>\n<blockquote>\n<h5><b>Summary<\/b><\/h5>\n<\/blockquote>\n<p>This project aims to develop an artificial intelligence (AI)\u2013based brain computer interface (BCI) system to decode brain functions on Electroencephalography (EEG) data. The developed AI-based EEG techniques will be applied to three main research fields, including medical care, home care, and scientific education. From the medical care aspect, we will design a closed-loop BCI system for rehabilitation treatments in stroke and cognitive impairment patients. By detecting patients\u2019 brain statuses using AI, transcranial electric stimulation (tES) will be utilized as a biofeedback to restore patient\u2019s brain functions. From the home care aspect, an AI-based BCI device for severely paralyzed patients will be designed to help them to communicate with external environments. Patients\u2019 vital signs (e.g., heart rate, respiration, blood pressure, etc.) will also be detected to manage a patient\u2019s physiological status. In the third part, a real-time BCI system with a biofeedback system in an education environment will be developed. Students\u2019 cognitive loads and emotional statues will be detected using deep learning networks. The research outcomes of this project are expected to establish a closed-loop BCI system to help the rehabilitation of stroke and dementia patients, to improve the communications of paralyzed patients, and to design better learning strategies for students.<\/p>\n<blockquote>\n<h5><b>Keywords<\/b><\/h5>\n<\/blockquote>\n<p>Closed-loop brain computer interface and electroencephalography (EEG)<\/p>\n<blockquote>\n<h5><b>Innovations<\/b><\/h5>\n<\/blockquote>\n<p>Our key achievements include the hardware design of close-loop EEG-based BCI system and the development of deep learning neural network for EEG applications. Hardware achievements:<\/p>\n<ul>\n<li>Multi-channel wireless EEG with 4, 8, 20, and 40 channels.<\/li>\n<li>High-sensitivity EEG dry electrode with high-performance impedance matching circuit.<\/li>\n<li>Wearable vital-sign monitoring watch for real-time monitoring of heart-rate, heart-rate variability, cuffless blood pressure, exercise ECG.<\/li>\n<li>3D posture recorder using eleven inertial measurement units (IMU) with 100 Hz digitization rate.<\/li>\n<\/ul>\n<p>AI for EEG applications:<\/p>\n<ul>\n<li>Real-time emotion recognition in EEG data using Long-short term memory network.<\/li>\n<li>Implementation of a Dry-Electrode EEG BCI system using Convolutional Neural Network.<\/li>\n<li>Application of deep learning to classifier sleep EEG waves.<\/li>\n<li>Bilateral motor cortices modulation by task-concurrent dual transcranial direct current stimulation in subacute stroke patients.<\/li>\n<li>Prediction of post-stroke epilepsy (PSE) using artificial intelligence on EEG data.<\/li>\n<li>Use of artificial intelligence to detect emotion and cognitive load during learning in classroom environments.<\/li>\n<\/ul>\n<blockquote>\n<h5><b>Benefits<\/b><\/h5>\n<\/blockquote>\n<ul>\n<li>EEG data measured by wearable devices are wirelessly transmitted to cloud servers.<\/li>\n<li>Deep learning neural networks are constructed on our cloud computation server in order to target different EEG applications.<\/li>\n<li>The established closed-loop BCI and the EEG cloud computing architecture will be applied to the following applications:\n<ol>\n<li>Using AI to detect user\u2019s emotion statuses can help people to manage their mental stress and emotions (Fig. 2a).<\/li>\n<li>Using AI to recognize user\u2019s movement intention. The EEG feedbacks from stroke or paralyzed patients provide biomarkers for clinical physicians to design better rehabilitation programs for patients.<\/li>\n<li>Using AI to detect user\u2019s sleep statuses can alleviate physicians\u2019 workload in examining huge amount of sleep EEG data (Fig. 2b).<\/li>\n<li>Using AI to improve the performance of EEG-based BCI will allow paralyzed patients (lock-in syndrome) to achieve communication with external environments.<\/li>\n<li>Using AI to find out good biomarkers for epilepsy in EEG data. Detection of biomarkers for epilepsy patients could help us understand the mechanism of epileptogenesis in patients and develop suitable preventive treatments.<\/li>\n<\/ol>\n<\/li>\n<\/ul>\n<\/div><\/section><\/div><div class=\"flex_column av_two_fifth  flex_column_div av-zero-column-padding   \" style='border-radius:0px; '><p><div class='avia-progress-bar-container  av-desktop-hide av-medium-hide av-small-hide av-mini-hide avia_animate_when_almost_visible   av-striped-bar av-animated-bar '><div class='avia-progress-bar theme-color-bar icon-bar-no'><div class='progressbar-title-wrap'><div class='progressbar-icon'><span class='progressbar-char' aria-hidden='true' data-av_icon='\ue856' data-av_iconfont='entypo-fontello'><\/span><\/div><div class='progressbar-title'>Type 1<\/div><\/div><div class='progress' ><div class='bar-outer'><div class='bar' style='width: 91%' data-progress='91'><\/div><\/div><\/div><\/div><div class='avia-progress-bar theme-color-bar icon-bar-no'><div class='progressbar-title-wrap'><div class='progressbar-icon'><span class='progressbar-char' aria-hidden='true' data-av_icon='\ue856' data-av_iconfont='entypo-fontello'><\/span><\/div><div class='progressbar-title'>Type 2<\/div><\/div><div class='progress' ><div class='bar-outer'><div class='bar' style='width: 86%' data-progress='86'><\/div><\/div><\/div><\/div><div class='avia-progress-bar theme-color-bar icon-bar-no'><div class='progressbar-title-wrap'><div class='progressbar-icon'><span class='progressbar-char' aria-hidden='true' data-av_icon='\ue856' data-av_iconfont='entypo-fontello'><\/span><\/div><div class='progressbar-title'>Type 3<\/div><\/div><div class='progress' ><div class='bar-outer'><div class='bar' style='width: 97%' data-progress='97'><\/div><\/div><\/div><\/div><div class='avia-progress-bar theme-color-bar icon-bar-no'><div class='progressbar-title-wrap'><div class='progressbar-icon'><span class='progressbar-char' aria-hidden='true' data-av_icon='\ue856' data-av_iconfont='entypo-fontello'><\/span><\/div><div class='progressbar-title'>Type 4<\/div><\/div><div class='progress' ><div class='bar-outer'><div class='bar' style='width: 85%' data-progress='85'><\/div><\/div><\/div><\/div><\/div><br \/>\n<div style='height:20px' class='hr hr-invisible   '><span class='hr-inner ' ><span class='hr-inner-style'><\/span><\/span><\/div><br \/>\n<div id='av-masonry-1' class='av-masonry  noHover av-fixed-size av-no-gap av-hover-overlay- av-masonry-animation-active av-masonry-col-2 av-caption-always av-caption-style- av-masonry-gallery   av-orientation-portrait   av-medium-columns-overwrite av-medium-columns-2 av-small-columns-overwrite av-small-columns-2 av-mini-columns-overwrite av-mini-columns-2'  ><div class='av-masonry-container isotope av-js-disabled ' ><div class='av-masonry-entry isotope-item av-masonry-item-no-image '><\/div><a href=\"https:\/\/pairlabs.ai\/wp-content\/uploads\/2020\/06\/\u5f90\u570b\u93a7-1-773x1030.jpg\" id='av-masonry-1-item-5168' data-av-masonry-item='5168' class='av-masonry-entry isotope-item post-5168 attachment type-attachment status-inherit hentry  av-masonry-item-with-image' title=\"\u5f90\u570b\u93a7\"  itemprop=\"thumbnailUrl\" ><div class='av-inner-masonry-sizer'><\/div><figure class='av-inner-masonry main_color'><div class=\"av-masonry-outerimage-container\"><div class=\"av-masonry-image-container\" style=\"background-image: url(https:\/\/pairlabs.ai\/wp-content\/uploads\/2020\/06\/\u5f90\u570b\u93a7-1-529x705.jpg);\" title=\"\u5f90\u570b\u93a7\" ><\/div><\/div><\/figure><\/a><!--end av-masonry entry--><\/div><\/div><\/p><\/div><\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='after_section_4' class='main_color av_default_container_wrap container_wrap sidebar_right' style=' '   style=' ' ><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4572'><div class='entry-content-wrapper clearfix'><\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='av_section_5' class='avia-section alternate_color avia-section-default avia-no-border-styling avia-bg-style-scroll    container_wrap sidebar_right' style=' '   style=' ' ><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4572'><div class='entry-content-wrapper clearfix'>\n<div class='flex_column_table av-equal-height-column-flextable -flextable' ><div class=\"flex_column av_two_fifth  flex_column_table_cell av-equal-height-column av-align-middle av-zero-column-padding first   \" style='border-radius:0px; 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