Enhancing two-dimensional control via single-channel haptic feedback: A multi-dimensional encoding strategy
Data files
Jul 26, 2025 version files 47.66 MB
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_X_Contiunous_D_Summary.csv
3.55 MB
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_Y_Contiunous_D_Summary.csv
3.53 MB
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BottomLContiunous_D_Summary.csv
7.43 MB
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BottomRContiunous_D_Summary.csv
6.97 MB
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Corners_Summary.csv
2.44 KB
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DiagonalContiunous_D_Summary.csv
11.18 MB
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Discreet_Summary.csv
2.85 MB
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IntensityDiscreet_Summary.csv
2.33 MB
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README.md
5.24 KB
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TimingDiscreet_Summary.csv
2.55 MB
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TopLContiunous_D_Summary.csv
7.25 MB
Abstract
Haptic feedback elicits sensations of touch to communicate information to the user. Recent developments in virtual reality and sensory prostheses have demonstrated the need for systems that can provide more information than the simple vibrotactor in your phone. A novel multidimensional encoding approach allows for percepts of signal intensity and flutter frequency in a single distal location using transcutaneous neural stimulation. In this study, we aimed to determine if these percepts are able to convey useful information to participants performing motor control tasks and if they perform better than a typical intensity-only modulation approach. Eleven participants performed three types of tasks to assess the efficacy of multidimensional stimulation. The first set included discrete matching tasks, where participants had to differentiate between thirteen combinations of flutter frequency and intensity. In the other two sets, participants had to differentiate between simultaneous changes in the percepts. Participants in this study could correctly identify all discrete percept combinations and follow the changes in the percepts better than chance. Performance in the discrete task using a multidimensional approach showed increased information transfer compared to the individual modulation of intensity or flutter frequency. These results suggest that multidimensional encoding is a promising approach for increasing information throughput in sensory feedback systems. Hence, such an approach might improve upon conventional methods of providing graded percepts, creating more informative tactile percepts for haptic feedback through peripheral nerve stimulation.
Dataset DOI: 10.5061/dryad.1rn8pk12q
Description of the data and file structure
A novel multidimensional encoding approach allows for percepts of signal intensity and flutter frequency in a single distal location using transcutaneous neural stimulation. In this study we aimed to determine if these percepts are able to convey useful information to participants performing motor control tasks and if they perform better than a typical intensity-only modulation approach. Eleven participants performed three types of tasks to assess the efficacy of multidimensional stimulation. The first set included discrete matching tasks, where participants had to differentiate between thirteen combinations of flutter frequency and intensity. In the other two sets, participants had to differentiate between simultaneous changes in the percepts.
Files and variables
Corners_Summary.csv
Description: Data from a center-out task, likely involving reaching or pointing to targets from a central location.
Variables:
- Correct: Number of correct responses.
- Total: Total number of trials.
- Wrong: Number of incorrect responses.
- Time_to_respond: Time taken to respond per trial.
- rsquare: Goodness-of-fit measure, possibly for trajectory or response model.
- Type: Type of trial or stimulus.
- Correct rate: Percentage of correct responses.
- max_deviation: Maximum deviation from the ideal path or target.
- subject_id: Identifier for the participant.
Files: _X_Contiunous_D_Summary.csv, _Y_Contiunous_D_Summary.csv, BottomLContiunous_D_Summary.csv, BottomRContiunous_D_Summary.csv, DiagonalContiunous_D_Summary.csv, TopLContiunous_D_Summary.csv
Description: summary data sheets of each of the extremes-in and, center out task, with the *x, *y and diagonal files containing the center out data, and the other files containing data for the extremes-in task
Variables:
- PA, PW_track, PF_Track, ACR_Track: Parameters related to stimulus or tracking (e.g., amplitude, pulse width, frequency, after-current response).
- PA -µA (micro Amperage)
- PW- µs (micro seconds)
- PF= HZ (hertz)
- ACR = µC/s (micro Coulomb per second)
- Burst_Count: Number of bursts in the stimulus.
- Burst Enabled: Whether burst stimulation was used.
- Burst Duration / Gap: Timing parameters of bursts.
- both are in ms (millisecond)
- X_Trace / Y_Trace: Raw trace of movement in X and Y.
- X_drawing / Y_drawing: Drawing data in X and Y.
- Trial Number: Trial index.
- response_x / response_y: Initial response coordinates.
- Response_x / Response_y: Possibly corrected or final response coordinates.
- final_response_x / final_response_y: Final response location.
- drawing_list_x / drawing_list_y: List of drawing points.
- final_drawing_x / final_drawing_y: Final drawing coordinates.
- Time_to_respond: Time taken to respond.
- r_square: Fit quality of response trajectory.
- subject_id: Participant ID.
- max_deviation: Maximum deviation from expected path.
- Target_reached: Whether the target was successfully reached.
- Correct_Response_Percent: Accuracy percentage.
- Target_Group / Response_Group: Grouping of targets and responses (e.g., by location or type).
- Type: Trial or stimulus type.
Discreet_Summary.csv, IntensityDiscreet_Summary.csv, TimingDiscreet_Summary.csv
Description: Discrete response tasks data sheets with a seperate file for each iteration of the response task.
Variables:
- PA, PW_Target, PF_Target, ACR_Target: Stimulus parameters for target.
- PA -µA (micro Amperage)
- PW- µs (micro seconds)
- PF= HZ (hertz)
- ACR = µC/s (micro Coulomb per second)
- Burst Count / BE (Burst Enabled): Burst stimulation details.
- intesity posistion: level of stimulus intensity.
- Burst_Gap / Burst_Duration: Timing parameters.
- both are in ms (millisecond)
- ACR_Position / BG_Position: ACR and BG are mapped to a linear range that the participants had to respond to.
- Response / Response_x / Response_y: Participant's response and coordinates.
- Optimal_x / Optimal_y: Ideal response coordinates.
- subject_id: Participant ID.
- Type: Trial or stimulus type.
- Target_reached: Whether the target was reached.
- Correct_Response_Percent: Accuracy percentage.
- Target_Group / Response_Group: Grouping of targets and responses.
Code/software
Data analysis and visualization can be run through the Aim_2_Analysis_code.R code. R and Rstudios are needed to run this analysis code.
Human subjects data
Ethical approval for the study protocol was obtained through the University of Arkansas Institutional Review Board (IRB # 2201379281). Participants were recruited for a single three-hour data collection session. Informed consent was obtained to publish the information/image(s) in an online open access publication. Information was de-identified using Subject-IDs in all published works and data files