Estimativa da Frequência Respiratória Usando Dados Wi-Fi CSI Comparada a Medições com Dispositivos Comerciais
Resumo
Os avanços tecnológicos têm impulsionado o desenvolvimento de diversos dispositivos capazes de estimar sinais vitais, como a frequência respiratória. Apesar da disponibilidade desses dispositivos, eles ainda apresentam desvantagens, como o desconforto gerado durante a estimativa da frequência respiratória, devido à necessidade de contato físico com o paciente. Nesse contexto, a tecnologia baseada em dados de Informação do Estado do Canal (CSI) tem emergido como uma alternativa promissora. Ela permite a utilização de sinais Wi-Fi, que contêm informações sobre o estado do canal de transmissão, para estimar a taxa de respiração em ambientes domiciliares e hospitalares. Neste trabalho, apresentamos a aplicação da CSI, juntamente com técnicas de processamento de sinais, para a estimativa da frequência respiratória em indivíduos. Para validar nossa abordagem, comparamos as estimativas da frequência respiratória obtidas com o CSI com as de dispositivos comerciais já validados, como o Polar H10 e o Biopac. A base de dados utilizada é composta por cerca de 100 voluntários. Os resultados obtidos demonstram uma alta similaridade entre as estimativas do CSI e as dos dispositivos comerciais validados.Referências
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Mosleh, S., Coder, J. B., Scully, C. G., Forsyth, K., and Kalaa, M. O. A. (2022). Monitoring respiratory motion with wi-fi csi: Characterizing performance and the breathesmart algorithm. IEEE Access, 10:131932–131951.
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Wang, X., Yang, C., and Mao, S. (2017). Phasebeat: Exploiting csi phase data for vital sign monitoring with commodity wifi devices. In 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS), pages 1230–1239.
Wang, X., Yang, C., and Mao, S. (2020). Resilient respiration rate monitoring with real-time bimodal csi data. IEEE Sensors Journal, 20(17):10187–10198.
Yu, B., Wang, Y., Niu, K., Zeng, Y., Gu, T., Wang, L., Guan, C., and Zhang, D. (2021). Wifi-sleep: Sleep stage monitoring using commodity wi-fi devices. IEEE Internet of Things Journal, 8(18):13900–13913.
Alzaabi, A., Arslan, T., and Polydorides, N. (2024). Non-contact wi-fi sensing of respiration rate for older adults in care: A validity and repeatability study. IEEE Access, 12:6400–6412.
Caballero, E., Galdino, I., Soto, J. C., Ramos, T. C., Guerra, R., Muchaluat-Saade, D., and Albuquerque, C. (2023). Human activity recognition using wi-fi csi. In International Conference on Pervasive Computing Technologies for Healthcare, pages 309–321. Springer.
Chen, Z., Zhang, L., Jiang, C., Cao, Z., and Cui, W. (2019). Wifi csi based passive human activity recognition using attention based blstm. IEEE Transactions on Mobile Computing, 18(11):2714–2724.
Galdino, I., Gouveia, B., Soto, J., Caballero, E., Ramos, T., Muchaluat-Saade, D., and Albuquerque, C. (2023a). Otimização de parâmetros para detecção de batimentos cardíacos através do sinal wi-fi. In Anais do XXIII Simpósio Brasileiro de Computação Aplicada à Saúde, pages 348–359, Porto Alegre, RS, Brasil. SBC.
Galdino, I., Soto, J. C. H., Caballero, E., Ferreira, V., Ramos, T. C., Albuquerque, C., and Muchaluat-Saade, D. C. (2023b). ehealth csi: A wi-fi csi dataset of human activities. IEEE Access, 11:71003–71012.
Gu, Y., Liu, T., Li, J., Ren, F., Liu, Z., Wang, X., and Li, P. (2018). Emosense: Data-driven emotion sensing via off-the-shelf wifi devices. In 2018 IEEE International Conference on Communications (ICC), pages 1–6.
Gu, Y., Zhan, J., Ji, Y., Li, J., Ren, F., and Gao, S. (2017). Mosense: An rf-based motion detection system via off-the-shelf wifi devices. IEEE Internet of Things Journal, 4(6):2326–2341.
He, Z., Guo, L., Lu, Z., Wen, X., Zheng, W., and Zhou, S. (2019). Contact-free in-home health monitoring system with commodity wi-fi. In 2019 IEEE International Conference on Communications Workshops (ICC Workshops), pages 1–6.
Khan, S. F. (2017). Health care monitoring system in internet of things (iot) by using rfid. In 2017 6th International Conference on Industrial Technology and Management (ICITM), pages 198–204.
Li, H., He, X., Chen, X., Fang, Y., and Fang, Q. (2019). Wi-motion: A robust human activity recognition using wifi signals. IEEE Access, 7:153287–153299.
Liu, X., Cao, J., Tang, S., and Wen, J. (2014). Wi-sleep: Contactless sleep monitoring via wifi signals. In 2014 IEEE Real-Time Systems Symposium, pages 346–355.
Liu, X., Cao, J., Tang, S., Wen, J., and Guo, P. (2016). Contactless respiration monitoring via off-the-shelf wifi devices. IEEE Transactions on Mobile Computing, 15(10):2466–2479.
Mosleh, S., Coder, J. B., Scully, C. G., Forsyth, K., and Kalaa, M. O. A. (2022). Monitoring respiratory motion with wi-fi csi: Characterizing performance and the breathesmart algorithm. IEEE Access, 10:131932–131951.
Pradhan, A., Singh, A., and Saraswat, S. (2017). Emotion recognition through wireless signal. In 2017 4th International Conference on Signal Processing and Integrated Networks (SPIN), pages 91–95.
Schafer, R. W. (2011). What is a savitzky-golay filter? [lecture notes]. IEEE Signal Processing Magazine, 28(4):111–117.
Sharma, A., Li, J., Mishra, D., Batista, G., and Seneviratne, A. (2021). Passive wifi csi sensing based machine learning framework for covid-safe occupancy monitoring. In 2021 IEEE International Conference on Communications Workshops (ICC Workshops), pages 1–6.
Soto, J. C., Galdino, I., Caballero, E., Ferreira, V., Muchaluat-Saade, D., and Albuquerque, C. (2022a). A survey on vital signs monitoring based on wi-fi csi data. Computer Communications, 195:99–110.
Soto, J. C. H., Galdino, I., Gouveia, B. G., Caballero, E., Ferreira, V., Muchaluat-Saade, D., and Albuquerque, C. (2022b). Wi-fi csi-based human presence detection using dtw features and machine learning. In 2022 IEEE Latin-American Conference on Communications (LATINCOM), pages 1–6.
Tan, B., Chen, Q., Chetty, K., Woodbridge, K., Li, W., and Piechocki, R. (2018). Exploiting wifi channel state information for residential healthcare informatics. IEEE Communications Magazine, 56(5):130–137.
Wang, X., Yang, C., and Mao, S. (2017). Phasebeat: Exploiting csi phase data for vital sign monitoring with commodity wifi devices. In 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS), pages 1230–1239.
Wang, X., Yang, C., and Mao, S. (2020). Resilient respiration rate monitoring with real-time bimodal csi data. IEEE Sensors Journal, 20(17):10187–10198.
Yu, B., Wang, Y., Niu, K., Zeng, Y., Gu, T., Wang, L., Guan, C., and Zhang, D. (2021). Wifi-sleep: Sleep stage monitoring using commodity wi-fi devices. IEEE Internet of Things Journal, 8(18):13900–13913.
Publicado
09/06/2025
Como Citar
QUEIRÓS, Fábio G.; SOTO, Julio C. H.; GALDINO, Iandra; SILVA, Carla E. C.; VIANA, Arthur; OLIVEIRA, Leticia de; ALBUQUERQUE, Célio; MUCHALUAT-SAADE, Débora C..
Estimativa da Frequência Respiratória Usando Dados Wi-Fi CSI Comparada a Medições com Dispositivos Comerciais. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO APLICADA À SAÚDE (SBCAS), 25. , 2025, Porto Alegre/RS.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 838-849.
ISSN 2763-8952.
DOI: https://doi.org/10.5753/sbcas.2025.7821.