scholarly journals Input Interface Using Wrinkles on Clothes for Wearable Computing

2019 ◽  
Vol 27 (0) ◽  
pp. 96-105 ◽  
Author(s):  
Kentaro Ueda ◽  
Tsutomu Terada ◽  
Masahiko Tsukamoto
Keyword(s):  
Wearable Computing ◽  
Input Interface

Evaluation of Input/Output Interface using Wrinkles on Clothes

2020 ◽  
Vol 1 (1) ◽  
pp. 36-54
Author(s):  
Kentaro Ueda ◽  
Tsutomu Terada ◽  
Masahiko Tsukamoto
Keyword(s):  
Wearable Computing ◽  
Input Interface ◽  
Input Method ◽  
Output Device ◽  
Touch Input ◽  
Operation Speed ◽  
Operating Environments ◽  
Tactile Sensations ◽  
Speed And Accuracy ◽  
Output Interface

Wearable computing has created textile-based interfaces utilizing the interaction between the user and cloth for operation, as well as the touch and the pinch input operation. The user wears and uses the device in various postures, environments, and operating positions that affect the operation speed and accuracy. However, no study has assessed such factors of touching and pinching using the same input interface. One of the textile interfaces has an input interface using wrinkles on clothes. A ridge of cloth produces a wrinkle that forms naturally on clothes, and the shape of these wrinkles can be recognized by their tactile sensations. Additionally, the act touching or pinching wrinkles does not look strange to an onlooker, which reach that wrinkles have the potential suitable for the wearable computing operation. To reveal the potential, this paper evaluates the input performance using wrinkles on clothes. We designed three touch input methods and one pinch input method for the operation using wrinkles. We implemented the input and the output device which use wrinkles and carried out four evaluations. The results indicated that the pinch input reached the highest accuracy of 98\% of four input methods after learning. The narrowing-down selection reached the fastest input time of 1.64 seconds of four methods after learning. The long press touch and the pinch input achieved the accuracy of 90\% or more in all combination of operating environments and device positions. According to the result of the wrinkle recognition, users have a high accuracy of the identification of wrinkles of 89.4\% and recognize their shape in approximately 12 seconds.

Improvement of Determination Algorithm for Eye Glance Input Interface

2014 ◽  
Vol 134 (7) ◽  
pp. 924-930 ◽  
Author(s):  
Yuta Ito ◽  
Naoaki Itakura ◽  
Kazuyuki Mito ◽  
Tota Mizuno
Keyword(s):  
Input Interface

A Multiple-choice Input Interface using Slanting Eye Glance

2017 ◽  
Vol 137 (4) ◽  
pp. 621-627 ◽  
Author(s):  
Shogo Matsuno ◽  
Yuta Ito ◽  
Kota Akehi ◽  
Naoaki Itakura ◽  
Tota Mizuno ◽  
...  
Keyword(s):  
Multiple Choice ◽  
Input Interface

Study of Gesture Input Interface for Smart Device by Wrist Movement

2019 ◽  
Vol 139 (11) ◽  
pp. 579-584 ◽  
Author(s):  
Hayato Matsuura ◽  
Tota Mizuno ◽  
Kota Akehi ◽  
Marzieh Aliabadi Farahani ◽  
Kazuyuki Mito ◽  
...  
Keyword(s):  
Smart Device ◽  
Wrist Movement ◽  
Input Interface ◽  
Gesture Input

Wearable Computing With Distributed Deep Learning Hierarchy: A Study of Fall Detection

2020 ◽  
Vol 20 (16) ◽  
pp. 9408-9416
Author(s):  
Xiaoye Qian ◽  
Huan Chen ◽  
Haotian Jiang ◽  
Justin Green ◽  
Haoyou Cheng ◽  
...  
Keyword(s):  
Deep Learning ◽  
Wearable Computing ◽  
Fall Detection

Issues in wearable computing

1997 ◽  
Vol 29 (4) ◽  
pp. 34-39 ◽  
Author(s):  
Len Bass ◽  
Steve Mann ◽  
Dan Siewiorek ◽  
Chris Thompson
Keyword(s):  
Wearable Computing

Wearable computing struggles for social acceptance

IEE Review ◽  
2003 ◽  
Vol 49 (9) ◽  
pp. 24-25 ◽  
Author(s):  
C. Edwards
Keyword(s):  
Social Acceptance ◽  
Wearable Computing
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