Design Concept of Clothing Recognizing Back Postures

Mattmann, Corinne; Tröster, Gerhard

doi:10.1109/issmdbs.2006.360088

Cited by 5 publications

(1 citation statement)

References 9 publications

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“…Several persons also wanted the button functions to be different while standing. We suggest using a built-in accelerometer and refer to, e.g., [12], [15] for projects and links to more advanced recognition methods.…”

Section: Optimal Position Of Controls Influenced By Posturementioning

confidence: 99%

Evaluating capacitive touch input on clothes

Holleis

Schmidt

Paasovaara

et al. 2008

Proceedings of the 10th International Conference on Human Computer Interaction With Mobile Devices and Services

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Wearable computing and smart clothing have attracted a lot of attention in the last years. For a variety of applications, it can be seen as potential future direction of mobile user interfaces. In this paper, we concentrate on usability and applicability issues concerned with capacitive touch input on clothing. To be able to perform user studies, we built a generic platform for attaching, e.g., capacitive sensors of different types. On top of that, several prototypes of wearable accessories and clothing and implemented various application scenarios. We report on two studies we undertook with these implementations with a user group randomly sampled at a shopping mall. We provide a significant set of guidelines and lessons learned that emerged from our experiences and those studies. Thus, developers of similar projects have to put major efforts into minimizing the delay between button activation and feedback and to make location and identification of controls and their function as simple and quick as possible. Issues that have to be treated in all designs include the requirement of onehanded interaction and that, even for minimal functionality, to find a general solution with regard to layout and button-tofunction mapping is hardly possible. Additionally, in order to generate a satisfactory user experience good usability must be combined with aesthetical factors.

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Section: Optimal Position Of Controls Influenced By Posturementioning

confidence: 99%

Evaluating capacitive touch input on clothes

Holleis

Schmidt

Paasovaara

et al. 2008

Proceedings of the 10th International Conference on Human Computer Interaction With Mobile Devices and Services

View full text Add to dashboard Cite

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Design and prototyping of wearable measuring system for trunk movement using textile sensors

Mokhlespour

Zobeiri

Narimani

et al. 2012

20th Iranian Conference on Electrical Engineering (ICEE2012)

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Recognizing Upper Body Postures using Textile Strain Sensors

Mattmann

Amft

Harms

et al. 2007

2007 11th IEEE International Symposium on Wearable Computers

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171

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In this paper we present a garment prototype using strain sensors to recognize upper body postures. A novel thermoplastic elastomer strain sensor was used for measuring strain in the clothing. This sensor has a linear resistance response to strain, a small hysteresis and can be fully integrated into textile.A study was conducted with eight participants wearing the garment and performing a total of 27 upper body postures. A Naïve Bayes classification was applied to identify the different postures. Nearly a complete recognition rate of 97% was achieved when the classification was adapted to the individual participant. A classification rate of 84% was achieved for an all-user classification and 65% for an independent user. These results show the feasibility to recognize postures with our setup, even in an unseen user setting.Furthermore, we used the garment prototype in a gym experiment to explore its potential for rehabilitation and fitness training. Intensity, speed and number of repetitions could be obtained from the garment sensor data.

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Design Concept of Clothing Recognizing Back Postures

Cited by 5 publications

References 9 publications

Evaluating capacitive touch input on clothes

Evaluating capacitive touch input on clothes

Design and prototyping of wearable measuring system for trunk movement using textile sensors

Recognizing Upper Body Postures using Textile Strain Sensors

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