Avian, Cries and Leu, Jenq-Shiou and Ali, Erfansyah and Putro, Nur Achmad Sulistyo and Song, Hang and Takada, Jun-ichi and Prakosa, Setya Widyawan and Purnomo, Ariana Tulus (2023) Non-contact Breathing Patterns Recognition with FMCW Radar by Processing Temporal Information using Transformer Network. In: 2023 ASIA-PACIFIC MICROWAVE CONFERENCE, APMC, 5th to 8th December 2023, Taipei City, Taiwan.
Non-contact_Breathing_Patterns_Recognition_with_FMCW_Radar_by_Processing_Temporal_Information_using_Transformer_Network.pdf - Published Version
Restricted to Registered users only
Download (476kB) | Request a copy
Abstract
This paper proposed non-contact monitoring by classifying breathing patterns using a frequency-modulated continuous wave (FMCW) radar sensor. First, the data were from the subject to conducting breathing pattern: normal, quick, hold, deep, deep quick. Second, we extract the breath wave patterns by employing several block preprocessing and extracting its temporal information that was not investigated by our previous work. Then, to distinguish those five breath wave conditions, the designated Transformer architecture is proposed. Finally, we compared our previous work and demonstrated that our model could enhance accuracy and attained 98.6% of F1-Scores.
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Additional Information: | 31st Asia-Pacific Microwave Conference (APMC) - Microwave Linking the World, Taipei, TAIWAN, DEC 05-08, 2023 |
Uncontrolled Keywords: | Breathing Pattern; FMCW; Non-contact monitoring; Transformer |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Divisions: | Faculty of Engineering > Electrical and Information Technology Department |
Depositing User: | Rita Yulianti Yulianti |
Date Deposited: | 05 Nov 2024 08:31 |
Last Modified: | 05 Nov 2024 08:31 |
URI: | https://ir.lib.ugm.ac.id/id/eprint/10414 |