Human Arm Reaching Intentions Under Force Disturbances

This dataset supports research on determining motor intent from targeted reaching motions disturbed by unexpected forces. It includes data from a study with eight human subjects, analyzing intended trajectories derived from feedforward and feedback controls. The modeling approach inverts control signals to estimate intent, with sensitivity to parameter uncertainties examined.

Use Cases

• Model the inversion of feedforward and feedback controls to derive intended trajectories from disturbed reaching motions.
• Analyze the sensitivity of intent estimation to parameter uncertainties, particularly joint stiffnesses, across subjects.
• Test the hypothesis of straight-line intent persistence for at least 120 milliseconds post-disturbance onset using temporal trajectory data.
• Examine changes in intent signals in subjects even when the hand is near the target, applicable to human-machine interaction studies.

Strengths

• Data is derived from a study involving eight human subjects, providing a basis for individual variability analysis.
• The modeling approach mathematically inverts both feedforward and feedback controls, a novel method for intent determination.
• Dataset is licensed under CC0-1.0, allowing for unrestricted use and sharing.

Limitations

• The sample size is limited to eight subjects, which may restrict the generalizability of findings.
• Specific data dimensions such as row count, column names, and file formats are unknown, complicating immediate usability.
• Data collection details and potential measurement noise from force disturbances are not fully specified.

Provenance

Source

Dryad digital repository.

Collection Method

Derived from experimental study on human arm reaching under force disturbances, using mathematical modeling to invert control signals.

Freshness

Last updated on 2020-06-24.