Integrating Wearable Textiles Sensors and IoT for Continuous sEMG Monitoring
Surface electromyography is a technique used to measure the electrical activity of muscles. sEMG can be used to assess muscle function in various settings, including clinical, academic/industrial research, and sports medicine. The aim of this study is to develop a wearable textile sensor for continu...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-03-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/24/6/1834 |
| _version_ | 1797239373143474176 |
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| author | Bulcha Belay Etana Benny Malengier Janarthanan Krishnamoorthy Lieva Van Langenhove |
| author_facet | Bulcha Belay Etana Benny Malengier Janarthanan Krishnamoorthy Lieva Van Langenhove |
| author_sort | Bulcha Belay Etana |
| collection | DOAJ |
| description | Surface electromyography is a technique used to measure the electrical activity of muscles. sEMG can be used to assess muscle function in various settings, including clinical, academic/industrial research, and sports medicine. The aim of this study is to develop a wearable textile sensor for continuous sEMG monitoring. Here, we have developed an integrated biomedical monitoring system that records sEMG signals through a textile electrode embroidered within a smart sleeve bandage for telemetric assessment of muscle activities and fatigue. We have taken an “Internet of Things”-based approach to acquire the sEMG, using a Myoware sensor and transmit the signal wirelessly through a WiFi-enabled microcontroller unit (NodeMCU; ESP8266). Using a wireless router as an access point, the data transmitted from ESP8266 was received and routed to the webserver-cum-database (Xampp local server) installed on a mobile phone or PC for processing and visualization. The textile electrode integrated with IoT enabled us to measure sEMG, whose quality is similar to that of conventional methods. To verify the performance of our developed prototype, we compared the sEMG signal recorded from the biceps, triceps, and tibialis muscles, using both the smart textile electrode and the gelled electrode. The root mean square and average rectified values of the sEMG measured using our prototype for the three muscle types were within the range of 1.001 ± 0.091 mV to 1.025 ± 0.060 mV and 0.291 ± 0.00 mV to 0.65 ± 0.09 mV, respectively. Further, we also performed the principal component analysis for a total of 18 features (15 time domain and 3 frequency domain) for the same muscle position signals. On the basis on the hierarchical clustering analysis of the PCA’s score, as well as the one-way MANOVA of the 18 features, we conclude that the differences observed in the data for the different muscle types as well as the electrode types are statistically insignificant. |
| first_indexed | 2024-04-24T17:50:30Z |
| format | Article |
| id | doaj.art-5fe987f5f3c34439989a18f36c19d3f4 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-24T17:50:30Z |
| publishDate | 2024-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-5fe987f5f3c34439989a18f36c19d3f42024-03-27T14:03:54ZengMDPI AGSensors1424-82202024-03-01246183410.3390/s24061834Integrating Wearable Textiles Sensors and IoT for Continuous sEMG MonitoringBulcha Belay Etana0Benny Malengier1Janarthanan Krishnamoorthy2Lieva Van Langenhove3Department of Materials, Textiles and Chemical Engineering, Ghent University, 9000 Gent, BelgiumDepartment of Materials, Textiles and Chemical Engineering, Ghent University, 9000 Gent, BelgiumSchool of Biomedical Engineering, Jimma Institute of Technology, Jimma University, Jimma 378, EthiopiaDepartment of Materials, Textiles and Chemical Engineering, Ghent University, 9000 Gent, BelgiumSurface electromyography is a technique used to measure the electrical activity of muscles. sEMG can be used to assess muscle function in various settings, including clinical, academic/industrial research, and sports medicine. The aim of this study is to develop a wearable textile sensor for continuous sEMG monitoring. Here, we have developed an integrated biomedical monitoring system that records sEMG signals through a textile electrode embroidered within a smart sleeve bandage for telemetric assessment of muscle activities and fatigue. We have taken an “Internet of Things”-based approach to acquire the sEMG, using a Myoware sensor and transmit the signal wirelessly through a WiFi-enabled microcontroller unit (NodeMCU; ESP8266). Using a wireless router as an access point, the data transmitted from ESP8266 was received and routed to the webserver-cum-database (Xampp local server) installed on a mobile phone or PC for processing and visualization. The textile electrode integrated with IoT enabled us to measure sEMG, whose quality is similar to that of conventional methods. To verify the performance of our developed prototype, we compared the sEMG signal recorded from the biceps, triceps, and tibialis muscles, using both the smart textile electrode and the gelled electrode. The root mean square and average rectified values of the sEMG measured using our prototype for the three muscle types were within the range of 1.001 ± 0.091 mV to 1.025 ± 0.060 mV and 0.291 ± 0.00 mV to 0.65 ± 0.09 mV, respectively. Further, we also performed the principal component analysis for a total of 18 features (15 time domain and 3 frequency domain) for the same muscle position signals. On the basis on the hierarchical clustering analysis of the PCA’s score, as well as the one-way MANOVA of the 18 features, we conclude that the differences observed in the data for the different muscle types as well as the electrode types are statistically insignificant.https://www.mdpi.com/1424-8220/24/6/1834sEMGelectrode positionsmart wearabletextile sensorIoT-integrated textile sensor |
| spellingShingle | Bulcha Belay Etana Benny Malengier Janarthanan Krishnamoorthy Lieva Van Langenhove Integrating Wearable Textiles Sensors and IoT for Continuous sEMG Monitoring Sensors sEMG electrode position smart wearable textile sensor IoT-integrated textile sensor |
| title | Integrating Wearable Textiles Sensors and IoT for Continuous sEMG Monitoring |
| title_full | Integrating Wearable Textiles Sensors and IoT for Continuous sEMG Monitoring |
| title_fullStr | Integrating Wearable Textiles Sensors and IoT for Continuous sEMG Monitoring |
| title_full_unstemmed | Integrating Wearable Textiles Sensors and IoT for Continuous sEMG Monitoring |
| title_short | Integrating Wearable Textiles Sensors and IoT for Continuous sEMG Monitoring |
| title_sort | integrating wearable textiles sensors and iot for continuous semg monitoring |
| topic | sEMG electrode position smart wearable textile sensor IoT-integrated textile sensor |
| url | https://www.mdpi.com/1424-8220/24/6/1834 |
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