TY - GEN
T1 - Automatic Detection of Obstructive Sleep Apnea Based on Multimodal Imaging System and Binary Code Alignment
AU - Yang, Ruoshu
AU - Zhang, Ludan
AU - Wang, Yunlu
AU - Hu, Menghan
AU - Li, Qingli
AU - Zhang, Xiao Ping
N1 - Publisher Copyright:
© 2022, Springer Nature Singapore Pte Ltd.
PY - 2022
Y1 - 2022
N2 - There are many patients with obstructive sleep apnea syndrome, which has caused concern. When it occurs, the nasal airflow disappears, and the breathing action of the chest and abdomen still exists. Therefore, we propose a multimodal imaging system in tandem with binary code alignment to remotely and automatically detect the obstructive sleep apnea. The RGB-thermal imaging module is applied to monitor the breathing conditions in the nose or mouth area. The depth camera is utilized to monitor the undulating state of the chest cavity. The obtained respiratory waveform is afterwards subjected to the limiting filter to suppress noisy signals that are not related to the mission objective. The signals derived from thermal camera and depth camera are pooled together for binary code alignment. When these two synchronously acquired bimodal signals do not match well, the obstructive sleep apnea is present. Our method achieves the satisfactory performance with accuracy, precision, recall and F1 of 91.38 %, 96.15 %, 86.21 %, and 90.91 %, respectively. This indicates that the proposed multimodal imaging system coupled with binary code alignment has a potential for non-contact and automatic detection of obstructive sleep apnea.
AB - There are many patients with obstructive sleep apnea syndrome, which has caused concern. When it occurs, the nasal airflow disappears, and the breathing action of the chest and abdomen still exists. Therefore, we propose a multimodal imaging system in tandem with binary code alignment to remotely and automatically detect the obstructive sleep apnea. The RGB-thermal imaging module is applied to monitor the breathing conditions in the nose or mouth area. The depth camera is utilized to monitor the undulating state of the chest cavity. The obtained respiratory waveform is afterwards subjected to the limiting filter to suppress noisy signals that are not related to the mission objective. The signals derived from thermal camera and depth camera are pooled together for binary code alignment. When these two synchronously acquired bimodal signals do not match well, the obstructive sleep apnea is present. Our method achieves the satisfactory performance with accuracy, precision, recall and F1 of 91.38 %, 96.15 %, 86.21 %, and 90.91 %, respectively. This indicates that the proposed multimodal imaging system coupled with binary code alignment has a potential for non-contact and automatic detection of obstructive sleep apnea.
KW - Binary code alignment
KW - Depth imaging
KW - Limiting filter processing
KW - Obstructive Sleep Apnea (OSA)
KW - RGB-thermal imaging
UR - https://www.scopus.com/pages/publications/85128984998
U2 - 10.1007/978-981-19-2266-4_9
DO - 10.1007/978-981-19-2266-4_9
M3 - 会议稿件
AN - SCOPUS:85128984998
SN - 9789811922657
T3 - Communications in Computer and Information Science
SP - 108
EP - 119
BT - Digital TV and Wireless Multimedia Communications - 18th International Forum, IFTC 2021, Revised Selected Papers
A2 - Zhai, Guangtao
A2 - Zhou, Jun
A2 - Yang, Hua
A2 - An, Ping
A2 - Yang, Xiaokang
PB - Springer Science and Business Media Deutschland GmbH
T2 - 18th International Forum of Digital Multimedia Communication, IFTC 2021
Y2 - 3 December 2021 through 4 December 2021
ER -