TY - JOUR
T1 - Mitigation of Biodynamic Feedthrough for Touchscreens on the Flight Deck
AU - Khoshnewiszadeh, Arwin
AU - Pool, Daan M.
PY - 2021
Y1 - 2021
N2 - Biodynamic feedthrough (BDFT) is a key issue for touchscreen operations on the future flight deck, as cockpit accelerations due to turbulence leave pilots vulnerable to erroneous touches that disrupt task performance. This research focuses on the implementation of a software-based cancellation approach to mitigate the adverse effects of BDFT in touchscreen dragging tasks. A flight-simulator experiment with 18 participants was performed to estimate models of BDFT dynamics for horizontal and vertical touch-inputs on a primary flight display. The averaged BDFT models were used to cancel BDFT in the same continuous dragging task used for model identification and a discrete point-to-point dragging task. While for the continuous task the cancellation enabled 63% mitigation in BDFT, the same cancellation was ineffective for the discrete task, due to reduced BDFT susceptibility. Overall, the results show that while model-based BDFT cancellation can be highly effective, a key technical challenge will be ensuring it is sufficiently task-adaptive.
AB - Biodynamic feedthrough (BDFT) is a key issue for touchscreen operations on the future flight deck, as cockpit accelerations due to turbulence leave pilots vulnerable to erroneous touches that disrupt task performance. This research focuses on the implementation of a software-based cancellation approach to mitigate the adverse effects of BDFT in touchscreen dragging tasks. A flight-simulator experiment with 18 participants was performed to estimate models of BDFT dynamics for horizontal and vertical touch-inputs on a primary flight display. The averaged BDFT models were used to cancel BDFT in the same continuous dragging task used for model identification and a discrete point-to-point dragging task. While for the continuous task the cancellation enabled 63% mitigation in BDFT, the same cancellation was ineffective for the discrete task, due to reduced BDFT susceptibility. Overall, the results show that while model-based BDFT cancellation can be highly effective, a key technical challenge will be ensuring it is sufficiently task-adaptive.
UR - http://www.scopus.com/inward/record.url?scp=85103045853&partnerID=8YFLogxK
U2 - 10.1080/10447318.2021.1890490
DO - 10.1080/10447318.2021.1890490
M3 - Article
AN - SCOPUS:85103045853
SN - 1044-7318
VL - 37
SP - 680
EP - 692
JO - International Journal of Human-Computer Interaction
JF - International Journal of Human-Computer Interaction
IS - 7
ER -