Rong-Hao Liang

ACM CHI 2018: ACM SIGCHI Conference on Human Factors in Computing Systems

BioFidget: Biofeedback for Respiration Training Using an Augmented Fidget Spinner

Rong-Hao Liang, Bin Yu, Mengru Xue, Jun Hu, Loe M.G. Feijs

TU Eindhoven

ACM Digital Library

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Abstract

This paper presents BioFidget, a biofeedback system that integrates physiological sensing and display into a smart fidget spinner for respiration training. We present a simple yet novel hardware design that transforms a fidget spinner into 1) a nonintrusive heart rate variability (HRV) sensor, 2) an electromechanical respiration sensor, and 3) an information display. The combination of these features enables users to engage in respiration training through designed tangible and embodied interactions, without requiring them to wear additional physiological sensors. The results of this empirical user study prove that the respiration training method reduces stress, and the proposed system meets the requirements of sensing validity and engagement with 32 participants in a practical setting.

Keywords

fidget spinner, tangible interaction, stress, respiration training, biofeedback, physiological sensing

Cite this work (ACM)

Rong-Hao Liang, Bin Yu, Mengru Xue, Jun Hu, and Loe M. G. Feijs. 2018. BioFidget: Biofeedback for Respiration Training Using an Augmented Fidget Spinner. In <i>Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems</i> (<i>CHI '18</i>). Association for Computing Machinery, New York, NY, USA, Paper 613, 1–12. DOI:https://doi.org/10.1145/3173574.3174187

Cite this work (Bibtex)

@inproceedings{10.1145/3173574.3174187,
author = {Liang, Rong-Hao and Yu, Bin and Xue, Mengru and Hu, Jun and Feijs, Loe M. G.},
title = {BioFidget: Biofeedback for Respiration Training Using an Augmented Fidget Spinner},
year = {2018},
isbn = {9781450356206},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3173574.3174187},
doi = {10.1145/3173574.3174187},
abstract = {This paper presents BioFidget, a biofeedback system that integrates physiological sensing and display into a smart fidget spinner for respiration training. We present a simple yet novel hardware design that transforms a fidget spinner into 1) a nonintrusive heart rate variability (HRV) sensor, 2) an electromechanical respiration sensor, and 3) an information display. The combination of these features enables users to engage in respiration training through designed tangible and embodied interactions, without requiring them to wear additional physiological sensors. The results of this empirical user study prove that the respiration training method reduces stress, and the proposed system meets the requirements of sensing validity and engagement with 32 participants in a practical setting.},
booktitle = {Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems},
pages = {1–12},
numpages = {12},
keywords = {fidget spinner, tangible interaction, stress, respiration training, biofeedback, physiological sensing},
location = {Montreal QC, Canada},
series = {CHI '18}
}