Classification of Standing and Walking States Using Ground Reaction Forces
The operation of wearable robots, such as gait rehabilitation robots, requires real-time classification of the standing or walking state of the wearer. This report explains a technique that measures the ground reaction force (GRF) using an insole device equipped with force sensing resistors, and det...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-03-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/21/6/2145 |
| _version_ | 1797540809429483520 |
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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 | The operation of wearable robots, such as gait rehabilitation robots, requires real-time classification of the standing or walking state of the wearer. This report explains a technique that measures the ground reaction force (GRF) using an insole device equipped with force sensing resistors, and detects whether the insole wearer is standing or walking based on the measured results. The technique developed in the present study uses the waveform length that represents the sum of the changes in the center of pressure within an arbitrary time window as the determining factor, and applies this factor to a conventional threshold method and an artificial neural network (ANN) model for classification of the standing and walking states. The results showed that applying the newly developed technique could significantly reduce classification errors due to shuffling movements of the patient, typically noticed in the conventional threshold method using GRF, i.e., real-time classification of the standing and walking states is possible in the ANN model. The insole device used in the present study can be applied not only to gait analysis systems used in wearable robot operations, but also as a device for remotely monitoring the activities of daily living of the wearer. |
| first_indexed | 2024-03-10T13:06:16Z |
| format | Article |
| id | doaj.art-e2d5099a07f84ea69644fdfc2e4be773 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T13:06:16Z |
| publishDate | 2021-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-e2d5099a07f84ea69644fdfc2e4be7732023-11-21T11:06:18ZengMDPI AGSensors1424-82202021-03-01216214510.3390/s21062145Classification of Standing and Walking States Using Ground Reaction ForcesJi Su Park0Sang-Mo Koo1Choong Hyun Kim2Center for Bionics, Korea Institute of Science and Technology, Seoul 02792, KoreaElectronic Materials Engineering, Kwangwoon University, Seoul 01890, KoreaCenter for Bionics, Korea Institute of Science and Technology, Seoul 02792, KoreaThe operation of wearable robots, such as gait rehabilitation robots, requires real-time classification of the standing or walking state of the wearer. This report explains a technique that measures the ground reaction force (GRF) using an insole device equipped with force sensing resistors, and detects whether the insole wearer is standing or walking based on the measured results. The technique developed in the present study uses the waveform length that represents the sum of the changes in the center of pressure within an arbitrary time window as the determining factor, and applies this factor to a conventional threshold method and an artificial neural network (ANN) model for classification of the standing and walking states. The results showed that applying the newly developed technique could significantly reduce classification errors due to shuffling movements of the patient, typically noticed in the conventional threshold method using GRF, i.e., real-time classification of the standing and walking states is possible in the ANN model. The insole device used in the present study can be applied not only to gait analysis systems used in wearable robot operations, but also as a device for remotely monitoring the activities of daily living of the wearer.https://www.mdpi.com/1424-8220/21/6/2145gait analysiswearable devicesinsoleforce sensing resistorsground reaction forcecenter of pressure |
| spellingShingle | Ji Su Park Sang-Mo Koo Choong Hyun Kim Classification of Standing and Walking States Using Ground Reaction Forces Sensors gait analysis wearable devices insole force sensing resistors ground reaction force center of pressure |
| title | Classification of Standing and Walking States Using Ground Reaction Forces |
| title_full | Classification of Standing and Walking States Using Ground Reaction Forces |
| title_fullStr | Classification of Standing and Walking States Using Ground Reaction Forces |
| title_full_unstemmed | Classification of Standing and Walking States Using Ground Reaction Forces |
| title_short | Classification of Standing and Walking States Using Ground Reaction Forces |
| title_sort | classification of standing and walking states using ground reaction forces |
| topic | gait analysis wearable devices insole force sensing resistors ground reaction force center of pressure |
| url | https://www.mdpi.com/1424-8220/21/6/2145 |
| work_keys_str_mv | AT jisupark classificationofstandingandwalkingstatesusinggroundreactionforces AT sangmokoo classificationofstandingandwalkingstatesusinggroundreactionforces AT choonghyunkim classificationofstandingandwalkingstatesusinggroundreactionforces |