Time-Based and Path-Based Analysis of Upper-Limb Movements during Activities of Daily Living
Patients after stroke need to re-learn functional movements required for independent living throughout the rehabilitation process. In the study, we used a wearable sensory system for monitoring the movement of the upper limbs while performing activities of daily living. We implemented time-based and...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/23/3/1289 |
| _version_ | 1797623287024451584 |
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| author | Sebastjan Šlajpah Eva Čebašek Marko Munih Matjaž Mihelj |
| author_facet | Sebastjan Šlajpah Eva Čebašek Marko Munih Matjaž Mihelj |
| author_sort | Sebastjan Šlajpah |
| collection | DOAJ |
| description | Patients after stroke need to re-learn functional movements required for independent living throughout the rehabilitation process. In the study, we used a wearable sensory system for monitoring the movement of the upper limbs while performing activities of daily living. We implemented time-based and path-based segmentation of movement trajectories and muscle activity to quantify the activities of the unaffected and the affected upper limbs. While time-based segmentation splits the trajectory in quants of equal duration, path-based segmentation isolates completed movements. We analyzed the hand movement path and forearm muscle activity and introduced a bimanual movement parameter, which enables differentiation between unimanual and bimanual activities. The approach was validated in a study that included a healthy subject and seven patients after stroke with different levels of disabilities. Path-based segmentation provides a more detailed and comprehensive evaluation of upper limb activities, while time-based segmentation is more suitable for real-time assessment and providing feedback to patients. Bimanual movement parameter effectively differentiates between different levels of upper limb involvement and is a clear indicator of the activity of the affected limb relative to the unaffected limb. |
| first_indexed | 2024-03-11T09:26:32Z |
| format | Article |
| id | doaj.art-d08c7fb6f3bd45fcaae702765039d9df |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T09:26:32Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-d08c7fb6f3bd45fcaae702765039d9df2023-11-16T17:58:54ZengMDPI AGSensors1424-82202023-01-01233128910.3390/s23031289Time-Based and Path-Based Analysis of Upper-Limb Movements during Activities of Daily LivingSebastjan Šlajpah0Eva Čebašek1Marko Munih2Matjaž Mihelj3Faculty of Electrical Engineering, University of Ljubljana, Tržaška cesta 25, 1000 Ljubljana, SloveniaFaculty of Electrical Engineering, University of Ljubljana, Tržaška cesta 25, 1000 Ljubljana, SloveniaFaculty of Electrical Engineering, University of Ljubljana, Tržaška cesta 25, 1000 Ljubljana, SloveniaFaculty of Electrical Engineering, University of Ljubljana, Tržaška cesta 25, 1000 Ljubljana, SloveniaPatients after stroke need to re-learn functional movements required for independent living throughout the rehabilitation process. In the study, we used a wearable sensory system for monitoring the movement of the upper limbs while performing activities of daily living. We implemented time-based and path-based segmentation of movement trajectories and muscle activity to quantify the activities of the unaffected and the affected upper limbs. While time-based segmentation splits the trajectory in quants of equal duration, path-based segmentation isolates completed movements. We analyzed the hand movement path and forearm muscle activity and introduced a bimanual movement parameter, which enables differentiation between unimanual and bimanual activities. The approach was validated in a study that included a healthy subject and seven patients after stroke with different levels of disabilities. Path-based segmentation provides a more detailed and comprehensive evaluation of upper limb activities, while time-based segmentation is more suitable for real-time assessment and providing feedback to patients. Bimanual movement parameter effectively differentiates between different levels of upper limb involvement and is a clear indicator of the activity of the affected limb relative to the unaffected limb.https://www.mdpi.com/1424-8220/23/3/1289strokeupper-limb movementmovement estimationactivities of daily livinginertial measurement unitelectromyography |
| spellingShingle | Sebastjan Šlajpah Eva Čebašek Marko Munih Matjaž Mihelj Time-Based and Path-Based Analysis of Upper-Limb Movements during Activities of Daily Living Sensors stroke upper-limb movement movement estimation activities of daily living inertial measurement unit electromyography |
| title | Time-Based and Path-Based Analysis of Upper-Limb Movements during Activities of Daily Living |
| title_full | Time-Based and Path-Based Analysis of Upper-Limb Movements during Activities of Daily Living |
| title_fullStr | Time-Based and Path-Based Analysis of Upper-Limb Movements during Activities of Daily Living |
| title_full_unstemmed | Time-Based and Path-Based Analysis of Upper-Limb Movements during Activities of Daily Living |
| title_short | Time-Based and Path-Based Analysis of Upper-Limb Movements during Activities of Daily Living |
| title_sort | time based and path based analysis of upper limb movements during activities of daily living |
| topic | stroke upper-limb movement movement estimation activities of daily living inertial measurement unit electromyography |
| url | https://www.mdpi.com/1424-8220/23/3/1289 |
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