scholarly journals Categorizing Touch-Input Locations from Touchscreen Device Interfaces via On-Board Mechano-Acoustic Transducers

2021 ◽  
Vol 11 (11) ◽  
pp. 4834
Author(s):  
Kai Ren Teo ◽  
Balamurali B T ◽  
Jianying Zhou ◽  
Jer-Ming Chen
Keyword(s):  
User Interaction ◽  
Data Access ◽  
Machine Learning Techniques ◽  
Acoustic Features ◽  
Touch Input ◽  
Acoustic Transducers ◽  
Learning Techniques ◽  
Access Controls ◽  
Input Location ◽  
Mitigation Methods

Many mobile electronics devices, including smartphones and tablets, require the user to interact physically with the device via tapping the touchscreen. Conveniently, these compact devices are also equipped with high-precision transducers such as accelerometers and microphones, integrated mechanically and designed on-board to support a range of user functionalities. However, unintended access to these transducer signals (bypassing normal on-board data access controls) may allow sensitive user interaction information to be detected and thereby exploited. In this study, we show that acoustic features extracted from the on-board microphone signals, supported with accelerometer and gyroscope signals, may be used together with machine learning techniques to successfully determine the user’s touch input location on a touchscreen: our ensemble model, namely the random forest model, predicts touch input location with up to 86% accuracy in a realistic scenario. Accordingly, we present the approach and techniques used, the performance of the model developed, and also discuss limitations and possible mitigation methods to thwart possible exploitation of such unintended signal channels.

scholarly journals Multi-Touch Interaction Generation Device by Spatiotemporally Switching Electrodes

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1475
Author(s):  
Masahiro Okamoto ◽  
Kazuya Murao
Keyword(s):  
High Speed ◽  
High Accuracy ◽  
Conductive Ink ◽  
Control Board ◽  
Touch Panel ◽  
Electrode Size ◽  
Touch Input ◽  
Touch Interaction ◽  
Multiple Electrodes ◽  
Touch Panels

With the spread of devices equipped with touch panels, such as smartphones, tablets, and laptops, the opportunity for users to perform touch interaction has increased. In this paper, we constructed a device that generates multi-touch interactions to realize high-speed, continuous, or hands-free touch input on a touch panel. The proposed device consists of an electrode sheet printed with multiple electrodes using conductive ink and a voltage control board, and generates eight multi-touch interactions: tap, double-tap, long-press, press-and-tap, swipe, pinch-in, pinch-out, and rotation, by changing the capacitance of the touch panel in time and space. In preliminary experiments, we investigated the appropriate electrode size and spacing for generating multi-touch interactions, and then implemented the device. From the evaluation experiments, it was confirmed that the proposed device can generate multi-touch interactions with high accuracy. As a result, tap, press-and-tap, swipe, pinch-in, pinch-out, and rotation can be generated with a success rate of 100%. It was confirmed that all the multi-touch interactions evaluated by the proposed device could be generated with high accuracy and acceptable speed.

scholarly journals Touchscreens for Whom? Working Memory and Age Moderate the Impact of Contingency on Toddlers' Transfer From Video

2021 ◽  
Vol 12 ◽  
Author(s):  
Koeun Choi ◽  
Heather L. Kirkorian ◽  
Tiffany A. Pempek
Keyword(s):  
Working Memory ◽  
Real World ◽  
Transfer Of Learning ◽  
Optimal Conditions ◽  
Older Children ◽  
Child Characteristics ◽  
Touch Input ◽  
The Impact

Toddlers exhibit poor transfer between video and real-world contexts. Contingently responsive video such as that found in touchscreen apps appears to assist transfer for some toddlers but not others. This study investigated the extent to which toddlers' working memory moderates the impact of contingency on toddler's transfer of learning from video. Toddlers (24–36 months; N = 134) watched a hiding event on either (a) contingent video that advanced only after touch input or (b) non-contingent video that proceeded automatically. Toddlers then searched for a corresponding object on a felt board. Additionally, toddlers' working memory (WM) was assessed. Findings indicate WM and age moderated the impact of contingency on transfer: Contingency decreased transfer in younger children while increasing transfer among older children. However, this was only true for children with relatively low WM. Contingency had little impact on transfer among children with relatively high WM, regardless of age. Results from this study suggest that WM is one specific moderator that predicts whether toddlers are likely to learn from contingent vs. non-contingent video, yet WM does not operate in isolation. Together, these findings underscore the importance of considering multiple child characteristics when identifying the optimal conditions for toddlers' learning from symbolic media.

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