A Distributed Wearable System Based on Multimodal Fusion

Cho, Il-Yeon; Sunwoo, John; Jeong, Hyuntae; Son, Yong-Ki; Ahn, Hee-Joong; Lee, Dong Hoon; Han, Dongwon; Lee, Cheol-Hoon

doi:10.1007/978-3-540-72685-2_35

Cited by 4 publications

(4 citation statements)

References 5 publications

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“…By comparing the data with one of our previous works [5] that uses piezoelectric sensor, the data generated illustrates interesting fact. In the previous work, the piezoelectric sensor measured minute sounds that are generated by pinching two fingers.…”

Section: Fig 1 Ir-emitter and Ir-optic Sensormentioning

confidence: 91%

“…Using the sEMG technique can achieve relatively accurate recognition results, however the recognition rate can be varied depends on an attaching location of the sensor [3]. Meanwhile, the piezoelectric sensors, which is used to monitor bone-conducting sounds from the body movement can be an alternative solution to recognize hand gestures [4] [5].…”

Section: Introductionmentioning

confidence: 99%

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Recognizing hand gestures using wrist shapes

Lim

Lee

Kim

et al. 2010

2010 Digest of Technical Papers International Conference on Consumer Electronics (ICCE)

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We introduce a new hand gesture recognition interface, called virtual button. The virtual button utilizes patterns of the wrist shape. It can recognize a pinch motion and it can be used as a generic button event. Using the pinch motion is favorable in multi-touch based interactions or games because it can express picking, moving, and releasing (or putting) activities in a natural way. We use a small-sized IR optic sensor to get patterns of finger flexor tendons on wrist cause by moving fingers. These patterns are used to recognize finger/hand movements. Our method can also measure applied forces at the picking operation where using a vision-based approach may encounter difficulties. Finally, our experimental result shows that using the IR-optic sensor can be an effective solution to implement the virtual button. Our system also shows that it can recognize effectively various kinds of other hand motions such as a shaking of hands or bending of fingers.

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Section: Fig 1 Ir-emitter and Ir-optic Sensormentioning

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Recognizing hand gestures using wrist shapes

Lim

Lee

Kim

et al. 2010

2010 Digest of Technical Papers International Conference on Consumer Electronics (ICCE)

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“…In health care, proposed systems [9], [10], [11] combine ambient and wearable sensors (e.g., ear-worn and blob-based vision sensors, accelerometers, gyroscopes, and bio-signal sensors) to enable the robust recognition of activities and motions. Similarly, the work by Cho et al [7] proposes a distributed system that comprises a wristband-type device and a mobile gateway. The system supports voice and gesture recognition simultaneously in order to achieve a better combined recognition rate.…”

Section: Related Workmentioning

confidence: 99%

“…Instead, combining different types of wearables together holds the promise of improving mUX. Previous work attempted to combine different wearables to, for e.g., offer accurate location awareness services in AR settings [6] or use voice and gesture recognition simultaneously to achieve a better combined recognition rate [7]. However, building distributed apps on top of heterogeneous platforms entails challenges across the entire development stack.…”

Section: Introductionmentioning

confidence: 99%

MULTI-WEAR: A multi-wearable platform for enhancing mobile experiences

Pamboris¹,

Andreou²,

Herodotou

et al. 2018

2018 15th IEEE Annual Consumer Communications &Amp; Networking Conference (CCNC)

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The uptake of wearable technology suggests that the time is ripe to explore new opportunities for improving mobile experiences. Apps, however, are not keeping up with the pace of technological advancement because wearables are treated as standalone devices, although their individual capabilities better classify them as peripherals with complementary roles. We foresee that the next generation of apps will orchestrate multiple wearable devices to enhance mobile user experiences. However, currently there is limited support for combining heterogeneous devices. This paper introduces MULTI-WEAR, a platform to scaffold the development of apps that span multiple wearables. It demonstrates experimentally how MULTI-WEAR can help bring changes to mobile apps that go beyond conventional practices.

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