Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2409.16692 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866909325468893184 |
|---|---|
| author | Moullet, Etienne Bailly, François Carpentier, Justin Coste, Christine Azevedo |
| author_facet | Moullet, Etienne Bailly, François Carpentier, Justin Coste, Christine Azevedo |
| contents | This study introduces i-GRIP, an innovative movement goal estimator designed to facilitate the control of assistive devices for grasping tasks in individuals with upperlimb impairments. The algorithm operates within a collaborative control paradigm, eliminating the need for specific user actions apart from naturally moving their hand toward a desired object. i-GRIP analyzes the hand's movement in an object-populated scene to determine its target and select an appropriate grip. In an experimental study involving 11 healthy participants, i-GRIP showed promising goal estimation performances and responsiveness and the potential to facilitate the daily use of assistive devices for individuals with upper-limb impairments in the future. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_16692 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Grasping Movement Intention Estimator for Intuitive Control of Assistive Devices Moullet, Etienne Bailly, François Carpentier, Justin Coste, Christine Azevedo Quantitative Methods This study introduces i-GRIP, an innovative movement goal estimator designed to facilitate the control of assistive devices for grasping tasks in individuals with upperlimb impairments. The algorithm operates within a collaborative control paradigm, eliminating the need for specific user actions apart from naturally moving their hand toward a desired object. i-GRIP analyzes the hand's movement in an object-populated scene to determine its target and select an appropriate grip. In an experimental study involving 11 healthy participants, i-GRIP showed promising goal estimation performances and responsiveness and the potential to facilitate the daily use of assistive devices for individuals with upper-limb impairments in the future. |
| title | A Grasping Movement Intention Estimator for Intuitive Control of Assistive Devices |
| topic | Quantitative Methods |
| url | https://arxiv.org/abs/2409.16692 |