| dc.contributor.advisor | Sanjay E Sarma. | en_US |
| dc.contributor.author | Armengol Urpi, Alexandre | en_US |
| dc.contributor.other | Massachusetts Institute of Technology. Department of Mechanical Engineering. | en_US |
| dc.date.accessioned | 2018-10-22T18:47:01Z | |
| dc.date.available | 2018-10-22T18:47:01Z | |
| dc.date.copyright | 2018 | en_US |
| dc.date.issued | 2018 | en_US |
| dc.identifier.uri | http://hdl.handle.net/1721.1/118736 | |
| dc.description | Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018. | en_US |
| dc.description | Cataloged from PDF version of thesis. | en_US |
| dc.description | Includes bibliographical references (pages 67-72). | en_US |
| dc.description.abstract | The growing Internet of Things (JoT) ecosystem being built today is already affecting a great many daily objects, which may share information about their state, location and sensed data among others. Today, humans communicate with IoT devices through visual, voice or tactile interfaces. More natural and organic interaction requires more sophisticated communication methods. This thesis explores seamless interfaces between human and IoT devices. In particular, I focus on using biological signals as the interface to directly connect with the smart surroundings. The work is partitioned in two parts. First, I present a wearable sensing system to estimate the thermal comfort level of the user by monitoring skin temperature, blood volume pressure and skin conductivity. This effort is a first step towards connecting room occupants and smart A/C devices, which can enable real-time adjustments of indoor conditions. In the second part of the thesis, brain signals are used as the interface to navigate in a Virtual Reality (VR) environment. We develop Sublime, a new concept of Steady-State Visually Evoked Potentials (SSVEP) based Brain-Computer Interface (BCI). In this technology, brain-computer communication is triggered by imperceptible visual stimuli integrated in the virtual scene and subliminal information is seamlessly conveyed to a computer. By monitoring the elicited SSVEPs, the system is able to identify the gaze target of the user, thus enabling a hands-free menu navigation tool. | en_US |
| dc.description.statementofresponsibility | by Alexandre Armengol Urpi. | en_US |
| dc.format.extent | 72 pages | en_US |
| dc.language.iso | eng | en_US |
| dc.publisher | Massachusetts Institute of Technology | en_US |
| dc.rights | MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. | en_US |
| dc.rights.uri | http://dspace.mit.edu/handle/1721.1/7582 | en_US |
| dc.subject | Mechanical Engineering. | en_US |
| dc.title | Responsive IoT : using biosignals to connect humans and smart devices | en_US |
| dc.title.alternative | Responsive Internet of Things | en_US |
| dc.title.alternative | Using biosignals to connect humans and smart devices | en_US |
| dc.type | Thesis | en_US |
| dc.description.degree | S.M. | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Mechanical Engineering | |
| dc.identifier.oclc | 1057270096 | en_US |