Design and Testing of a Smart Facemask for Respiratory Monitoring during Cycling Exercise
Given the importance of respiratory frequency (<i>f</i><sub>R</sub>) as a valid marker of physical effort, there is a growing interest in developing wearable devices measuring <i>f</i><sub>R</sub> in applied exercise settings. Biosensors measuring ches...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | Biosensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-6374/13/3/369 |
| _version_ | 1797613234216239104 |
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| author | Chiara Romano Andrea Nicolò Lorenzo Innocenti Massimo Sacchetti Emiliano Schena Carlo Massaroni |
| author_facet | Chiara Romano Andrea Nicolò Lorenzo Innocenti Massimo Sacchetti Emiliano Schena Carlo Massaroni |
| author_sort | Chiara Romano |
| collection | DOAJ |
| description | Given the importance of respiratory frequency (<i>f</i><sub>R</sub>) as a valid marker of physical effort, there is a growing interest in developing wearable devices measuring <i>f</i><sub>R</sub> in applied exercise settings. Biosensors measuring chest wall movements are attracting attention as they can be integrated into textiles, but their susceptibility to motion artefacts may limit their use in some sporting activities. Hence, there is a need to exploit sensors with signals minimally affected by motion artefacts. We present the design and testing of a smart facemask embedding a temperature biosensor for <i>f</i><sub>R</sub> monitoring during cycling exercise. After laboratory bench tests, the proposed solution was tested on cyclists during a ramp incremental frequency test (RIFT) and high-intensity interval training (HIIT), both indoors and outdoors. A reference flowmeter was used to validate the <i>f</i><sub>R</sub> extracted from the temperature respiratory signal. The smart facemask showed good performance, both at a breath-by-breath level (MAPE = 2.56% and 1.64% during RIFT and HIIT, respectively) and on 30 s average <i>f</i><sub>R</sub> values (MAPE = 0.37% and 0.23% during RIFT and HIIT, respectively). Both accuracy and precision (MOD ± LOAs) were generally superior to those of other devices validated during exercise. These findings have important implications for exercise testing and management in different populations. |
| first_indexed | 2024-03-11T06:52:01Z |
| format | Article |
| id | doaj.art-ddbfbd6b92ea4cc8ac02dd86c6444363 |
| institution | Directory Open Access Journal |
| issn | 2079-6374 |
| language | English |
| last_indexed | 2024-03-11T06:52:01Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biosensors |
| spelling | doaj.art-ddbfbd6b92ea4cc8ac02dd86c64443632023-11-17T09:54:24ZengMDPI AGBiosensors2079-63742023-03-0113336910.3390/bios13030369Design and Testing of a Smart Facemask for Respiratory Monitoring during Cycling ExerciseChiara Romano0Andrea Nicolò1Lorenzo Innocenti2Massimo Sacchetti3Emiliano Schena4Carlo Massaroni5The Departmental Faculty of Engineering, Università Campus Bio-Medico di Roma, 00128 Rome, ItalyDepartment of Movement, Human and Health Sciences, University of Rome “Foro Italico”, 00135 Rome, ItalyDepartment of Movement, Human and Health Sciences, University of Rome “Foro Italico”, 00135 Rome, ItalyDepartment of Movement, Human and Health Sciences, University of Rome “Foro Italico”, 00135 Rome, ItalyThe Departmental Faculty of Engineering, Università Campus Bio-Medico di Roma, 00128 Rome, ItalyThe Departmental Faculty of Engineering, Università Campus Bio-Medico di Roma, 00128 Rome, ItalyGiven the importance of respiratory frequency (<i>f</i><sub>R</sub>) as a valid marker of physical effort, there is a growing interest in developing wearable devices measuring <i>f</i><sub>R</sub> in applied exercise settings. Biosensors measuring chest wall movements are attracting attention as they can be integrated into textiles, but their susceptibility to motion artefacts may limit their use in some sporting activities. Hence, there is a need to exploit sensors with signals minimally affected by motion artefacts. We present the design and testing of a smart facemask embedding a temperature biosensor for <i>f</i><sub>R</sub> monitoring during cycling exercise. After laboratory bench tests, the proposed solution was tested on cyclists during a ramp incremental frequency test (RIFT) and high-intensity interval training (HIIT), both indoors and outdoors. A reference flowmeter was used to validate the <i>f</i><sub>R</sub> extracted from the temperature respiratory signal. The smart facemask showed good performance, both at a breath-by-breath level (MAPE = 2.56% and 1.64% during RIFT and HIIT, respectively) and on 30 s average <i>f</i><sub>R</sub> values (MAPE = 0.37% and 0.23% during RIFT and HIIT, respectively). Both accuracy and precision (MOD ± LOAs) were generally superior to those of other devices validated during exercise. These findings have important implications for exercise testing and management in different populations.https://www.mdpi.com/2079-6374/13/3/369wearable sensorsvalidityrespiratory frequencycadencemeasurement accuracyexercise |
| spellingShingle | Chiara Romano Andrea Nicolò Lorenzo Innocenti Massimo Sacchetti Emiliano Schena Carlo Massaroni Design and Testing of a Smart Facemask for Respiratory Monitoring during Cycling Exercise Biosensors wearable sensors validity respiratory frequency cadence measurement accuracy exercise |
| title | Design and Testing of a Smart Facemask for Respiratory Monitoring during Cycling Exercise |
| title_full | Design and Testing of a Smart Facemask for Respiratory Monitoring during Cycling Exercise |
| title_fullStr | Design and Testing of a Smart Facemask for Respiratory Monitoring during Cycling Exercise |
| title_full_unstemmed | Design and Testing of a Smart Facemask for Respiratory Monitoring during Cycling Exercise |
| title_short | Design and Testing of a Smart Facemask for Respiratory Monitoring during Cycling Exercise |
| title_sort | design and testing of a smart facemask for respiratory monitoring during cycling exercise |
| topic | wearable sensors validity respiratory frequency cadence measurement accuracy exercise |
| url | https://www.mdpi.com/2079-6374/13/3/369 |
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