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dc.contributor.advisorSanjay E Sarma.en_US
dc.contributor.authorArmengol Urpi, Alexandreen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Mechanical Engineering.en_US
dc.date.accessioned2018-10-22T18:47:01Z
dc.date.available2018-10-22T18:47:01Z
dc.date.copyright2018en_US
dc.date.issued2018en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/118736
dc.descriptionThesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 67-72).en_US
dc.description.abstractThe 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.statementofresponsibilityby Alexandre Armengol Urpi.en_US
dc.format.extent72 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT 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.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectMechanical Engineering.en_US
dc.titleResponsive IoT : using biosignals to connect humans and smart devicesen_US
dc.title.alternativeResponsive Internet of Thingsen_US
dc.title.alternativeUsing biosignals to connect humans and smart devicesen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineering
dc.identifier.oclc1057270096en_US


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