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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European Alliance for Innovation (EAI)
2016-11-01
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Online Access: | http://eudl.eu/doi/10.4108/eai.28-9-2015.2261470 |
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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 |
work_keys_str_mv |
AT florianwahl wiseglasssmarteyeglassesrecognisingcontext AT martinfreund wiseglasssmarteyeglassesrecognisingcontext AT oliveramft wiseglasssmarteyeglassesrecognisingcontext |
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