Capacitive-Type Pressure Sensor for Classification of the Activities of Daily Living
In order to operate a gait rehabilitation device, it is necessary to accurately classify the states appearing in activities of daily living (ADLs). In the case of force sensing resistors (FSRs), which are often used as pressure sensors in gait analysis, it is desirable to replace them with other sen...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Micro |
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| Online Access: | https://www.mdpi.com/2673-8023/3/1/4 |
| _version_ | 1797610111519162368 |
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| author | Ji Su Park Sang-Mo Koo Choong Hyun Kim |
| author_facet | Ji Su Park Sang-Mo Koo Choong Hyun Kim |
| author_sort | Ji Su Park |
| collection | DOAJ |
| description | In order to operate a gait rehabilitation device, it is necessary to accurately classify the states appearing in activities of daily living (ADLs). In the case of force sensing resistors (FSRs), which are often used as pressure sensors in gait analysis, it is desirable to replace them with other sensors because of their low durability. In the present study, capacitive-type pressure sensors, as an alternative to FSRs, were developed, and their performance was evaluated. In addition, the timed up and go test was performed to measure the ground reaction force in healthy individuals, and a machine learning technique was applied to the calculated biosignal parameters for the classification of five types of ADLs. The performance evaluation results showed that a sensor with thermoplastic polyurethane (substrate and dielectric layer material) and multiwall carbon nanotubes (conductive layer) has sufficient sensitivity and durability for use as a gait analysis pressure sensor. Moreover, when an overlapping filter was applied to the four-layer long short-term memory (LSTM) or the five-layer LSTM model developed for motion classification, the precision was greater or equal to 95%, and unstable errors did not occur. Therefore, when the pressure sensor and ADLs classification algorithm developed in this study are applied, it is expected that motion classification can be completed within a time range that does not affect the control of the gait rehabilitation device. |
| first_indexed | 2024-03-11T06:09:53Z |
| format | Article |
| id | doaj.art-083b99e6d9b14353b6249d8d3ceb4c4a |
| institution | Directory Open Access Journal |
| issn | 2673-8023 |
| language | English |
| last_indexed | 2024-03-11T06:09:53Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Micro |
| spelling | doaj.art-083b99e6d9b14353b6249d8d3ceb4c4a2023-11-17T12:40:52ZengMDPI AGMicro2673-80232023-01-0131355010.3390/micro3010004Capacitive-Type Pressure Sensor for Classification of the Activities of Daily LivingJi Su Park0Sang-Mo Koo1Choong Hyun Kim2Center for Bionic, Korea Institute of Science and Technology, Seoul 02792, Republic of KoreaElectronic Materials Engineering, Kwangwoon University, Seoul 01890, Republic of KoreaCenter for Bionic, Korea Institute of Science and Technology, Seoul 02792, Republic of KoreaIn order to operate a gait rehabilitation device, it is necessary to accurately classify the states appearing in activities of daily living (ADLs). In the case of force sensing resistors (FSRs), which are often used as pressure sensors in gait analysis, it is desirable to replace them with other sensors because of their low durability. In the present study, capacitive-type pressure sensors, as an alternative to FSRs, were developed, and their performance was evaluated. In addition, the timed up and go test was performed to measure the ground reaction force in healthy individuals, and a machine learning technique was applied to the calculated biosignal parameters for the classification of five types of ADLs. The performance evaluation results showed that a sensor with thermoplastic polyurethane (substrate and dielectric layer material) and multiwall carbon nanotubes (conductive layer) has sufficient sensitivity and durability for use as a gait analysis pressure sensor. Moreover, when an overlapping filter was applied to the four-layer long short-term memory (LSTM) or the five-layer LSTM model developed for motion classification, the precision was greater or equal to 95%, and unstable errors did not occur. Therefore, when the pressure sensor and ADLs classification algorithm developed in this study are applied, it is expected that motion classification can be completed within a time range that does not affect the control of the gait rehabilitation device.https://www.mdpi.com/2673-8023/3/1/4capacitive-type pressure sensorforce sensing resistors (FSRs)activities of daily living (ADLs)ground reaction force (GRF)center of pressure (COP)insole device |
| spellingShingle | Ji Su Park Sang-Mo Koo Choong Hyun Kim Capacitive-Type Pressure Sensor for Classification of the Activities of Daily Living Micro capacitive-type pressure sensor force sensing resistors (FSRs) activities of daily living (ADLs) ground reaction force (GRF) center of pressure (COP) insole device |
| title | Capacitive-Type Pressure Sensor for Classification of the Activities of Daily Living |
| title_full | Capacitive-Type Pressure Sensor for Classification of the Activities of Daily Living |
| title_fullStr | Capacitive-Type Pressure Sensor for Classification of the Activities of Daily Living |
| title_full_unstemmed | Capacitive-Type Pressure Sensor for Classification of the Activities of Daily Living |
| title_short | Capacitive-Type Pressure Sensor for Classification of the Activities of Daily Living |
| title_sort | capacitive type pressure sensor for classification of the activities of daily living |
| topic | capacitive-type pressure sensor force sensing resistors (FSRs) activities of daily living (ADLs) ground reaction force (GRF) center of pressure (COP) insole device |
| url | https://www.mdpi.com/2673-8023/3/1/4 |
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