WISEglass: Smart eyeglasses recognising context

We investigated how regular eyeglasses could be extended with multi-modal sensing and processing functions to support context-awareness applications. Our aim was to leverage eyeglasses as a platform for acquiring and processing context information according to the wearer’s needs. The WISEglass archi...

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Main Authors: Florian Wahl, Martin Freund, Oliver Amft
Format: Article
Language:English
Published: European Alliance for Innovation (EAI) 2016-11-01
Series:EAI Endorsed Transactions on Pervasive Health and Technology
Subjects:
Online Access:http://eudl.eu/doi/10.4108/eai.28-9-2015.2261470
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spelling doaj-f86f9110250f48078fd2e283092423732020-11-25T01:54:57ZengEuropean Alliance for Innovation (EAI)EAI Endorsed Transactions on Pervasive Health and Technology2411-71452016-11-01251710.4108/eai.28-9-2015.2261470WISEglass: Smart eyeglasses recognising contextFlorian Wahl0Martin Freund1Oliver Amft2University of Passau; wahl@fim.uni-passau.deUniversity of PassauUniversity of PassauWe investigated how regular eyeglasses could be extended with multi-modal sensing and processing functions to support context-awareness applications. Our aim was to leverage eyeglasses as a platform for acquiring and processing context information according to the wearer’s needs. The WISEglass architecture consists of inertial motion, environmental light, and pulse sensors, processing and wireless data transmission functionality, besides a rechargeable battery. We implemented prototypes of WISEglass and evaluated them in three application scenarios: daily activity recognition, screen-use detection, and heart rate estimation. We conducted a daily activity study with nine participants, each wearing WISEglass and recording for one day. When evaluating daily activity recognition, we obtained 77 % average accuracy for continuous recognition using Gaussian Mixture Models and classifier reject to ignore null class data. Using the light sensor for detecting screen-use, yielded 80 % accuracy. Against a chest-worn ECG reference, our heart rate estimation showed an difference below 10 beats for stationary activities across the full recording day. We concluded that smart eyeglasses provide information from a single measurement spot that is relevant in various context recognition applications.http://eudl.eu/doi/10.4108/eai.28-9-2015.2261470context inferencemobile sensingsmart glassesactivity recognitioneyewear
collection DOAJ
language English
format Article
sources DOAJ
author Florian Wahl
Martin Freund
Oliver Amft
spellingShingle Florian Wahl
Martin Freund
Oliver Amft
WISEglass: Smart eyeglasses recognising context
EAI Endorsed Transactions on Pervasive Health and Technology
context inference
mobile sensing
smart glasses
activity recognition
eyewear
author_facet Florian Wahl
Martin Freund
Oliver Amft
author_sort Florian Wahl
title WISEglass: Smart eyeglasses recognising context
title_short WISEglass: Smart eyeglasses recognising context
title_full WISEglass: Smart eyeglasses recognising context
title_fullStr WISEglass: Smart eyeglasses recognising context
title_full_unstemmed WISEglass: Smart eyeglasses recognising context
title_sort wiseglass: smart eyeglasses recognising context
publisher European Alliance for Innovation (EAI)
series EAI Endorsed Transactions on Pervasive Health and Technology
issn 2411-7145
publishDate 2016-11-01
description We investigated how regular eyeglasses could be extended with multi-modal sensing and processing functions to support context-awareness applications. Our aim was to leverage eyeglasses as a platform for acquiring and processing context information according to the wearer’s needs. The WISEglass architecture consists of inertial motion, environmental light, and pulse sensors, processing and wireless data transmission functionality, besides a rechargeable battery. We implemented prototypes of WISEglass and evaluated them in three application scenarios: daily activity recognition, screen-use detection, and heart rate estimation. We conducted a daily activity study with nine participants, each wearing WISEglass and recording for one day. When evaluating daily activity recognition, we obtained 77 % average accuracy for continuous recognition using Gaussian Mixture Models and classifier reject to ignore null class data. Using the light sensor for detecting screen-use, yielded 80 % accuracy. Against a chest-worn ECG reference, our heart rate estimation showed an difference below 10 beats for stationary activities across the full recording day. We concluded that smart eyeglasses provide information from a single measurement spot that is relevant in various context recognition applications.
topic context inference
mobile sensing
smart glasses
activity recognition
eyewear
url http://eudl.eu/doi/10.4108/eai.28-9-2015.2261470
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