innovative human computer interactions for wearable...
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Innovative Human‐Computer Interactions for Wearable Devices
Wearable devices are a kind of technologies that can be worn on human body. This type of
devices has become more and more important to be a part of our daily life because it provides
much convenient and powerful functions. Many companies have started to develop more and more
wearable devices embedded powerful sensors to collect and/or deliver information.
Human‐computer interaction (commonly referred to as HCI) is a research to study how human
interact with computers and to improve the interactive models to provide much convenient and
powerful functions. There are many corporations and academic institutions now study HCI, such as
University of California, Berkeley, Massachusetts Institute of Technology (MIT), Carnegie Mellon
University (CMU), Adobe Research, Disney Research, Google Research, etc.
The goal of this project is to design innovative human‐computer interactions that are essential
for enhancing the interactive models of wearable devices. However, to design a good user interface
for wearable devices is still a challenging problem, because it depends on understanding and
recognizing the vast range of cross‐disciplinary variables that affect user interactions with a
wearable device.
For increasing the user experiences on wearable user interfaces, we explored three directions
to enable different interaction models:
1. FlexiBend: Designing Shape‐Aware Strip for Sensing Deformable.
This work was published in the Proceedings of the 28th Annual ACM Symposium on User
Interface Software & Technology (ACM UIST 2015), which presents FlexiBend, an easily
installable shape‐sensing strip that enables interactivity of multi‐part, de‐formable fabrications.
The flexible sensor strip is composed of a dense linear array of strain gauges; therefore, it has
shape sensing capability. After installation, FlexiBend can simultaneously sense user inputs in
different parts of a fabrication or even capture the geometry of a deformable fabrication. Due
to the feature of changeable, it can be worn on the user’s wrist to interact with user allow the
user to control the remote device.
2. DigitSpace: Designing Thumb‐to‐fingers Touch Interfaces for One‐handed and Eyes‐Free
Interactions.
This work was published in the Proceedings of the 2016 ACM SIGCHI Conference on Human
Factors in Computing Systems (ACM CHI 2016), which presents DigitSpace, a thumb‐to‐fingers
interface that considers hand anatomy and touch precision. Its first study identified the regions
of fingers where thumb‐to‐fingers touch interactions can be comfortably performed. After
identifying the comfort regions, the second and the third studies further explored how to
arrange two general touch widgets, buttons and touchpads, for effective discrete and
continuous touch input. The study results reveal several factors that should be considered in
designs for thumb‐to‐fingers touch interactions. A DigitSpace prototype, a wearable device
based on magnetic tracking to enable thumb‐to‐fingers interactions and its applications, is then
developed based on the studies. As for future work, we have seen that allowing users to open
their fingers while performing thumb‐to‐fingers interaction will increase physical comfort. We
consider to investigate whether this increase in comfort also permits a boost in user
performance. Sensing techniques for supporting this feature will also be explored.
3. NailTactors: Eyes‐Free Spatial Output Using an Nail‐Mounted Tactor Array.
This work was published in the Proceedings of the 18th International Conference on
Human‐Computer Interaction with Mobile Devices and Services (ACM MobileHCI 2016), which
presents NailTactors, a system of nail‐mounted tactor array for enabling eyes‐free spatial
output. By erecting the disc‐like eccentric‐rotating‐mass (ERM) vibrators on the artificial nail,
miniatured high‐resolution tactile displays are realized. To understand how to deliver rich
signals to users for valid signal perception, three user studies were conducted. The results not
only suggest that users are able to recognize the delivered absolute and relative directional cues,
as well as numerical characters in EdgeWrite pattern with an overall 89% recognition rate, but
also identified the optimal placement of ERM actuators maximizing the information transfer.
MediaTek‐NTU Center
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Taiwan
Tel: +886‐2‐3366‐1836
About the Author
Meng‐Ju Hsieh and Bing‐Yu Chen
National Taiwan University
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