Activity-Aware Vital Sign Monitoring Based on a Multi-Agent Architecture
Vital sign monitoring outside the clinical environment based on wearable sensors ensures better support in assessing a patient’s health condition, and in case of health deterioration, automatic alerts can be sent to the care providers. In everyday life, the users can perform different physical activ...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-06-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/21/12/4181 |
| _version_ | 1797529678407270400 |
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| author | Todor Ivașcu Viorel Negru |
| author_facet | Todor Ivașcu Viorel Negru |
| author_sort | Todor Ivașcu |
| collection | DOAJ |
| description | Vital sign monitoring outside the clinical environment based on wearable sensors ensures better support in assessing a patient’s health condition, and in case of health deterioration, automatic alerts can be sent to the care providers. In everyday life, the users can perform different physical activities, and considering that vital sign measurements depend on the intensity of the activity, we proposed an architecture based on the multi-agent paradigm to handle this issue dynamically. Different types of agents were proposed that processed different sensor signals and recognized simple activities of daily living. The system was validated using a real-life dataset where subjects wore accelerometer sensors on the chest, wrist, and ankle. The system relied on ontology-based models to address the data heterogeneity and combined different wearable sensor sources in order to achieve better performance. The results showed an accuracy of 95.25% on intersubject activity classification. Moreover, the proposed method, which automatically extracted vital sign threshold ranges for each physical activity recognized by the system, showed promising results for remote health status evaluation. |
| first_indexed | 2024-03-10T10:18:09Z |
| format | Article |
| id | doaj.art-07ff4bd0cfdf40b087007750911d8218 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T10:18:09Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-07ff4bd0cfdf40b087007750911d82182023-11-22T00:39:14ZengMDPI AGSensors1424-82202021-06-012112418110.3390/s21124181Activity-Aware Vital Sign Monitoring Based on a Multi-Agent ArchitectureTodor Ivașcu0Viorel Negru1Department of Computer Science, Faculty of Mathematics and Informatics, West University of Timisoara, Blvd. V. Pârvan nr. 4, 300223 Timișoara, RomaniaDepartment of Computer Science, Faculty of Mathematics and Informatics, West University of Timisoara, Blvd. V. Pârvan nr. 4, 300223 Timișoara, RomaniaVital sign monitoring outside the clinical environment based on wearable sensors ensures better support in assessing a patient’s health condition, and in case of health deterioration, automatic alerts can be sent to the care providers. In everyday life, the users can perform different physical activities, and considering that vital sign measurements depend on the intensity of the activity, we proposed an architecture based on the multi-agent paradigm to handle this issue dynamically. Different types of agents were proposed that processed different sensor signals and recognized simple activities of daily living. The system was validated using a real-life dataset where subjects wore accelerometer sensors on the chest, wrist, and ankle. The system relied on ontology-based models to address the data heterogeneity and combined different wearable sensor sources in order to achieve better performance. The results showed an accuracy of 95.25% on intersubject activity classification. Moreover, the proposed method, which automatically extracted vital sign threshold ranges for each physical activity recognized by the system, showed promising results for remote health status evaluation.https://www.mdpi.com/1424-8220/21/12/4181human activity recognitionvital signshealth status monitoringwearable sensorsmulti-agent architectureknowledge-based system |
| spellingShingle | Todor Ivașcu Viorel Negru Activity-Aware Vital Sign Monitoring Based on a Multi-Agent Architecture Sensors human activity recognition vital signs health status monitoring wearable sensors multi-agent architecture knowledge-based system |
| title | Activity-Aware Vital Sign Monitoring Based on a Multi-Agent Architecture |
| title_full | Activity-Aware Vital Sign Monitoring Based on a Multi-Agent Architecture |
| title_fullStr | Activity-Aware Vital Sign Monitoring Based on a Multi-Agent Architecture |
| title_full_unstemmed | Activity-Aware Vital Sign Monitoring Based on a Multi-Agent Architecture |
| title_short | Activity-Aware Vital Sign Monitoring Based on a Multi-Agent Architecture |
| title_sort | activity aware vital sign monitoring based on a multi agent architecture |
| topic | human activity recognition vital signs health status monitoring wearable sensors multi-agent architecture knowledge-based system |
| url | https://www.mdpi.com/1424-8220/21/12/4181 |
| work_keys_str_mv | AT todorivascu activityawarevitalsignmonitoringbasedonamultiagentarchitecture AT viorelnegru activityawarevitalsignmonitoringbasedonamultiagentarchitecture |