Fitts’ Law in the Control of Isometric Grip Force With Naturalistic Targets
Fitts’ law models the relationship between amplitude, precision, and speed of rapid movements. It is widely used to quantify performance in pointing tasks, study human-computer interaction, and generally to understand perceptual-motor information processes, including research to model performance in...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2018-04-01
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| Series: | Frontiers in Psychology |
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| Online Access: | http://journal.frontiersin.org/article/10.3389/fpsyg.2018.00560/full |
| _version_ | 1828417785057771520 |
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| author | Zachary C. Thumser Zachary C. Thumser Andrew B. Slifkin Dylan T. Beckler Paul D. Marasco Paul D. Marasco |
| author_facet | Zachary C. Thumser Zachary C. Thumser Andrew B. Slifkin Dylan T. Beckler Paul D. Marasco Paul D. Marasco |
| author_sort | Zachary C. Thumser |
| collection | DOAJ |
| description | Fitts’ law models the relationship between amplitude, precision, and speed of rapid movements. It is widely used to quantify performance in pointing tasks, study human-computer interaction, and generally to understand perceptual-motor information processes, including research to model performance in isometric force production tasks. Applying Fitts’ law to an isometric grip force task would allow for quantifying grasp performance in rehabilitative medicine and may aid research on prosthetic control and design. We examined whether Fitts’ law would hold when participants attempted to accurately produce their intended force output while grasping a manipulandum when presented with images of various everyday objects (we termed this the implicit task). Although our main interest was the implicit task, to benchmark it and establish validity, we examined performance against a more standard visual feedback condition via a digital force-feedback meter on a video monitor (explicit task). Next, we progressed from visual force feedback with force meter targets to the same targets without visual force feedback (operating largely on feedforward control with tactile feedback). This provided an opportunity to see if Fitts’ law would hold without vision, and allowed us to progress toward the more naturalistic implicit task (which does not include visual feedback). Finally, we changed the nature of the targets from requiring explicit force values presented as arrows on a force-feedback meter (explicit targets) to the more naturalistic and intuitive target forces implied by images of objects (implicit targets). With visual force feedback the relation between task difficulty and the time to produce the target grip force was predicted by Fitts’ law (average r2 = 0.82). Without vision, average grip force scaled accurately although force variability was insensitive to the target presented. In contrast, images of everyday objects generated more reliable grip forces without the visualized force meter. In sum, population means were well-described by Fitts’ law for explicit targets with vision (r2 = 0.96) and implicit targets (r2 = 0.89), but not as well-described for explicit targets without vision (r2 = 0.54). Implicit targets should provide a realistic see-object-squeeze-object test using Fitts’ law to quantify the relative speed-accuracy relationship of any given grasper. |
| first_indexed | 2024-12-10T14:25:53Z |
| format | Article |
| id | doaj.art-411a31fd4a47459189bd2425155b3538 |
| institution | Directory Open Access Journal |
| issn | 1664-1078 |
| language | English |
| last_indexed | 2024-12-10T14:25:53Z |
| publishDate | 2018-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychology |
| spelling | doaj.art-411a31fd4a47459189bd2425155b35382022-12-22T01:45:04ZengFrontiers Media S.A.Frontiers in Psychology1664-10782018-04-01910.3389/fpsyg.2018.00560338434Fitts’ Law in the Control of Isometric Grip Force With Naturalistic TargetsZachary C. Thumser0Zachary C. Thumser1Andrew B. Slifkin2Dylan T. Beckler3Paul D. Marasco4Paul D. Marasco5Laboratory for Bionic Integration, Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United StatesResearch Service, Louis Stokes Cleveland VA Medical Center, Cleveland, OH, United StatesDepartment of Psychology, Cleveland State University, Cleveland, OH, United StatesLaboratory for Bionic Integration, Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United StatesLaboratory for Bionic Integration, Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United StatesAdvanced Platform Technology Center of Excellence, Louis Stokes Cleveland VA Medical Center, Cleveland, OH, United StatesFitts’ law models the relationship between amplitude, precision, and speed of rapid movements. It is widely used to quantify performance in pointing tasks, study human-computer interaction, and generally to understand perceptual-motor information processes, including research to model performance in isometric force production tasks. Applying Fitts’ law to an isometric grip force task would allow for quantifying grasp performance in rehabilitative medicine and may aid research on prosthetic control and design. We examined whether Fitts’ law would hold when participants attempted to accurately produce their intended force output while grasping a manipulandum when presented with images of various everyday objects (we termed this the implicit task). Although our main interest was the implicit task, to benchmark it and establish validity, we examined performance against a more standard visual feedback condition via a digital force-feedback meter on a video monitor (explicit task). Next, we progressed from visual force feedback with force meter targets to the same targets without visual force feedback (operating largely on feedforward control with tactile feedback). This provided an opportunity to see if Fitts’ law would hold without vision, and allowed us to progress toward the more naturalistic implicit task (which does not include visual feedback). Finally, we changed the nature of the targets from requiring explicit force values presented as arrows on a force-feedback meter (explicit targets) to the more naturalistic and intuitive target forces implied by images of objects (implicit targets). With visual force feedback the relation between task difficulty and the time to produce the target grip force was predicted by Fitts’ law (average r2 = 0.82). Without vision, average grip force scaled accurately although force variability was insensitive to the target presented. In contrast, images of everyday objects generated more reliable grip forces without the visualized force meter. In sum, population means were well-described by Fitts’ law for explicit targets with vision (r2 = 0.96) and implicit targets (r2 = 0.89), but not as well-described for explicit targets without vision (r2 = 0.54). Implicit targets should provide a realistic see-object-squeeze-object test using Fitts’ law to quantify the relative speed-accuracy relationship of any given grasper.http://journal.frontiersin.org/article/10.3389/fpsyg.2018.00560/fullFitts’ lawforcegripgraspisometricvision |
| spellingShingle | Zachary C. Thumser Zachary C. Thumser Andrew B. Slifkin Dylan T. Beckler Paul D. Marasco Paul D. Marasco Fitts’ Law in the Control of Isometric Grip Force With Naturalistic Targets Frontiers in Psychology Fitts’ law force grip grasp isometric vision |
| title | Fitts’ Law in the Control of Isometric Grip Force With Naturalistic Targets |
| title_full | Fitts’ Law in the Control of Isometric Grip Force With Naturalistic Targets |
| title_fullStr | Fitts’ Law in the Control of Isometric Grip Force With Naturalistic Targets |
| title_full_unstemmed | Fitts’ Law in the Control of Isometric Grip Force With Naturalistic Targets |
| title_short | Fitts’ Law in the Control of Isometric Grip Force With Naturalistic Targets |
| title_sort | fitts law in the control of isometric grip force with naturalistic targets |
| topic | Fitts’ law force grip grasp isometric vision |
| url | http://journal.frontiersin.org/article/10.3389/fpsyg.2018.00560/full |
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