TY - GEN
T1 - A Pinch-based Text Entry Method for Head-mounted Displays
AU - Jiang, Haiyan
AU - Weng, Dongdong
AU - Dongye, Xiaonuo
AU - Liu, Yue
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Pinch gestures have been used for text entry in Head-mounted dis-plays (HMDs), enabling a comfortable and eyes-free text entry. However, the number of pinch gestures is limited, making it difficult to input all characters. In addition, the common pinch-based meth-ods with a QWERTY keyboard require accurate control of the hand position and angle, which could be affected by natural tremors and the Heisenberg effect. So, we propose a new text entry method for HMDs, which combines hand positions and pinch gestures with a condensed key-based keyboard, enabling one-handed text entry for HMDs. With this method, users move their hands with a naturally comfortable posture between three large different spaces in the air to choose one key set and then execute one of the pinch gestures to choose one character, where hand jitter does not affect the selection, helping to improve the input speed. The results of a primary study show that the mean input speed of the proposed method is 7.60 words-per-minute (WPM).
AB - Pinch gestures have been used for text entry in Head-mounted dis-plays (HMDs), enabling a comfortable and eyes-free text entry. However, the number of pinch gestures is limited, making it difficult to input all characters. In addition, the common pinch-based meth-ods with a QWERTY keyboard require accurate control of the hand position and angle, which could be affected by natural tremors and the Heisenberg effect. So, we propose a new text entry method for HMDs, which combines hand positions and pinch gestures with a condensed key-based keyboard, enabling one-handed text entry for HMDs. With this method, users move their hands with a naturally comfortable posture between three large different spaces in the air to choose one key set and then execute one of the pinch gestures to choose one character, where hand jitter does not affect the selection, helping to improve the input speed. The results of a primary study show that the mean input speed of the proposed method is 7.60 words-per-minute (WPM).
KW - Haptic devices
KW - Human computer interaction
KW - Human computer interaction
KW - Human computer interaction
KW - Human-centered computing
KW - Human-centered computing
KW - Human-centered computing
KW - Interaction devices
KW - Interaction paradigms
KW - Interaction techniques
KW - Text input
KW - Virtual reality
UR - http://www.scopus.com/inward/record.url?scp=85129631730&partnerID=8YFLogxK
U2 - 10.1109/VRW55335.2022.00174
DO - 10.1109/VRW55335.2022.00174
M3 - Conference contribution
AN - SCOPUS:85129631730
T3 - Proceedings - 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2022
SP - 646
EP - 647
BT - Proceedings - 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2022
Y2 - 12 March 2022 through 16 March 2022
ER -