Can rhythm be touched? An evaluation of rhythmic sketch performance with augmented multimodal feedback
February 16, 2020 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Feng Feng, Shang Kai, Tony Stockman
arXiv ID
2002.06638
Category
cs.HC: Human-Computer Interaction
Citations
1
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Although it has been shown that augmented multimodal feedback has a facilitatory effect on motor performance for motor learning and music training, the functionality of haptic feedback combined with other modalities in rhythmic movement tasks has rarely been explored and analysed. In this paper, we evaluate the functionality of visual-haptic feedback in a rhythmic sketch task by comparing it with other multimodal conditions. Further, we examine the possibility of accessing the quality of task execution through kinematic analysis. Based on participants' speed profiles, we investigate the quality of motor control and movement smoothness under different feedback conditions. Results revealed better motor control ability with auditory feedback and improved movement smoothness with haptic feedback. Finally, we propose that haptic feedback can be integrated with other modal stimuli for different interaction purposes, and that kinematic analysis can be a complementary approach to gesture analysis as well as providing subjective evaluation of interaction performance.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted