Hybrid RF and PCA method: The number and Posture of piezoresistive sensors in a multifunctional technology for respiratory monitoring
The motivation of the research work is Respiratory Rate (RR) monitoring which is susceptible to environmental and physiological stimuli, knowing it may help in assessing the health of patients. In this work, at rest, six trials on a treadmill were to be completed by 10 healthy males, while low-speed...
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| Format: | Article |
| Language: | English |
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Elsevier
2023-10-01
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| Series: | Measurement: Sensors |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S266591742300168X |
| _version_ | 1827815750917685248 |
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| author | J. Vandarkuzhali Yandrapati prakashbabu S. Kamatchi M. Kalyan Chakravarthi DhanaSekaran Selvaraj R. Dhanapal |
| author_facet | J. Vandarkuzhali Yandrapati prakashbabu S. Kamatchi M. Kalyan Chakravarthi DhanaSekaran Selvaraj R. Dhanapal |
| author_sort | J. Vandarkuzhali |
| collection | DOAJ |
| description | The motivation of the research work is Respiratory Rate (RR) monitoring which is susceptible to environmental and physiological stimuli, knowing it may help in assessing the health of patients. In this work, at rest, six trials on a treadmill were to be completed by 10 healthy males, while low-speed jogging in order to evaluate a new approach based on Principal Component Analysis (PCA). Random Forest (RF) with PCA for sensory selection using a special wearable system with six piezoresistive sensors. For instance, a single sensor is needed for a breathing evaluation while at rest, three sensors are needed for a low-speed walk, and four sensors are needed for a high-speed walk and run assessment. The findings may be helpful in the deployment of specialized algorithms to continuously and accurately monitor RR, as well as the creation of the best instrumented wearable devices for RR monitoring both while the subject is at rest and when they are engaging in physical activity. A smart garment was utilized to obtain the breathing information delivering six respiration signals in the three compartmental parts, and a data gathering board (DAQ NI USB6002 from National Instruments) was used to gather the reference respiratory data. The performance measurements are often calculated using it (e.g., accuracy, sensitivity, specificity, precision and F1 score). |
| first_indexed | 2024-03-12T00:05:05Z |
| format | Article |
| id | doaj.art-57453dfe6a544f10a106aada12c4c14b |
| institution | Directory Open Access Journal |
| issn | 2665-9174 |
| language | English |
| last_indexed | 2024-03-12T00:05:05Z |
| publishDate | 2023-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Measurement: Sensors |
| spelling | doaj.art-57453dfe6a544f10a106aada12c4c14b2023-09-17T04:57:22ZengElsevierMeasurement: Sensors2665-91742023-10-0129100832Hybrid RF and PCA method: The number and Posture of piezoresistive sensors in a multifunctional technology for respiratory monitoringJ. Vandarkuzhali0Yandrapati prakashbabu1S. Kamatchi2M. Kalyan Chakravarthi3DhanaSekaran Selvaraj4R. Dhanapal5PG and Research Department of Computer Science, Erode Arts and Science College, Erode, Tamil Nadu, India; Ccorresponding author.Department of Computer Science and Engineering, GITAM Deemed to Be University, Hyderabad, IndiaDepartment of Electronics and Communication Engineering, Amrita School of Engineering, Amrita Vishwa Vidhyapeetham, Bangalore, IndiaSchool of Electronics Engineering, VIT-AP University, Amaravathi, IndiaDepartment of Electronics and Communication Engineering, Sri Eshwar College of Engineering, Coimbatore, Tamil Nadu, IndiaDepartment of Computer Science and Engineering, Karpagam Academy of Higher Education, Coimbatore, Tamil Nadu, IndiaThe motivation of the research work is Respiratory Rate (RR) monitoring which is susceptible to environmental and physiological stimuli, knowing it may help in assessing the health of patients. In this work, at rest, six trials on a treadmill were to be completed by 10 healthy males, while low-speed jogging in order to evaluate a new approach based on Principal Component Analysis (PCA). Random Forest (RF) with PCA for sensory selection using a special wearable system with six piezoresistive sensors. For instance, a single sensor is needed for a breathing evaluation while at rest, three sensors are needed for a low-speed walk, and four sensors are needed for a high-speed walk and run assessment. The findings may be helpful in the deployment of specialized algorithms to continuously and accurately monitor RR, as well as the creation of the best instrumented wearable devices for RR monitoring both while the subject is at rest and when they are engaging in physical activity. A smart garment was utilized to obtain the breathing information delivering six respiration signals in the three compartmental parts, and a data gathering board (DAQ NI USB6002 from National Instruments) was used to gather the reference respiratory data. The performance measurements are often calculated using it (e.g., accuracy, sensitivity, specificity, precision and F1 score).http://www.sciencedirect.com/science/article/pii/S266591742300168XRespiratory ratePrincipal component analysisRandom forestSensory selection and piezoresistive sensors |
| spellingShingle | J. Vandarkuzhali Yandrapati prakashbabu S. Kamatchi M. Kalyan Chakravarthi DhanaSekaran Selvaraj R. Dhanapal Hybrid RF and PCA method: The number and Posture of piezoresistive sensors in a multifunctional technology for respiratory monitoring Measurement: Sensors Respiratory rate Principal component analysis Random forest Sensory selection and piezoresistive sensors |
| title | Hybrid RF and PCA method: The number and Posture of piezoresistive sensors in a multifunctional technology for respiratory monitoring |
| title_full | Hybrid RF and PCA method: The number and Posture of piezoresistive sensors in a multifunctional technology for respiratory monitoring |
| title_fullStr | Hybrid RF and PCA method: The number and Posture of piezoresistive sensors in a multifunctional technology for respiratory monitoring |
| title_full_unstemmed | Hybrid RF and PCA method: The number and Posture of piezoresistive sensors in a multifunctional technology for respiratory monitoring |
| title_short | Hybrid RF and PCA method: The number and Posture of piezoresistive sensors in a multifunctional technology for respiratory monitoring |
| title_sort | hybrid rf and pca method the number and posture of piezoresistive sensors in a multifunctional technology for respiratory monitoring |
| topic | Respiratory rate Principal component analysis Random forest Sensory selection and piezoresistive sensors |
| url | http://www.sciencedirect.com/science/article/pii/S266591742300168X |
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