{"id":2042,"date":"2022-09-16T21:47:55","date_gmt":"2022-09-16T12:47:55","guid":{"rendered":"http:\/\/cinetjp-static3.nict.go.jp\/japanese\/?post_type=event&#038;p=2042"},"modified":"2022-09-16T21:47:57","modified_gmt":"2022-09-16T12:47:57","slug":"20181009_2915","status":"publish","type":"event","link":"http:\/\/cinetjp-static3.nict.go.jp\/japanese\/event\/20181009_2915\/","title":{"rendered":"Tim Mullen \u201cA Python-based Software Platform for Multi-Modal Signal Processing and BCI\u201d"},"content":{"rendered":"\n<p>2018\u5e7410\u670811\u65e5\uff08\u6728\uff09<br>13:30 ~ 14:15<br>\u4f1a\u5834 \uff1a CiNet\u30001F\u3000\u5927\u4f1a\u8b70\u5ba4<\/p>\n\n\n\n<p>Tim Mullen<br>Research Director &amp; CEO<br>Intheon, USA<\/p>\n\n\n\n<p>\u62c5\u5f53 :\u00a0Daniel Callan\u00a0\uff08CiNet PI\uff09<\/p>\n\n\n\n<p>Abstract:<br>In this talk I will present and demonstrate the NeuroPype Suite Academic Edition, a suite of desktop applications made available for free to the scientific community with the goal of accelerating and streamlining the creation, deployment, and sharing of pipelines for real-time or batch processing and decoding of unimodal and multi-modal sensor data (e.g. EEG, ExG, intracranial electrophysiology, actigraphy, eye tracking, audio and video signals, etc). The suite includes a version of NeuroPype, an extensible Python-based dataflow programming environment, containing 250+ modular data processing and visualization routines (\u201cnodes\u201d) that can be configured and linked together to create and run pipelines for signal processing and analysis, BCI and signal classification, neuroimaging, closed-loop feedback and control, and more. NeuroPype integrates seamlessly with the open-source Lab Streaming Layer (LSL) protocol for data acquisition, synchronization, and I\/O, and works out of the box with LSL-compatible hardware devices. An extensible framework enables users to add their own custom processing nodes in Python, while a RESTful API allows external applications to interface with NeuroPype to create, run and configure pipelines in real-time. While NeuroPype can be operated entirely programmatically, the suite also includes Pipeline Designer, an open-source visual programming application based on Orange which provides an intuitive drag-and-drop GUI for pipeline design and configuration through NeuroPype\u2019s API. I will illustrate both local deployment of NeuroPype pipelines, as well as deployment on the NeuroScale cloud platform for streaming access to\/from mobile and other internet-connected devices and for scalable batch processing.<\/p>\n","protected":false},"featured_media":0,"template":"","acf":[],"_links":{"self":[{"href":"http:\/\/cinetjp-static3.nict.go.jp\/japanese\/wp-json\/wp\/v2\/event\/2042"}],"collection":[{"href":"http:\/\/cinetjp-static3.nict.go.jp\/japanese\/wp-json\/wp\/v2\/event"}],"about":[{"href":"http:\/\/cinetjp-static3.nict.go.jp\/japanese\/wp-json\/wp\/v2\/types\/event"}],"wp:attachment":[{"href":"http:\/\/cinetjp-static3.nict.go.jp\/japanese\/wp-json\/wp\/v2\/media?parent=2042"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}