psychtracker-react v1.0.2

PsychTracker-React

A custom framework-based ReactJS library offering a suite of reusable components and hooks tailored for online experiments and flexible experimental designs.

Software Development Overview

PsychTracker-React is a custom ReactJS library designed to build online mouse-tracking experimental studies using the React js framework. It provides a set of reusable components and hooks that simplify the implementation of complex experimental designs, including multiplayer and multi-stimuli experiments.

Library Highlights

This library integrates with the ReactJS framework and supports both dynamic and static procedures. Button sizes follow standardized guidelines and are fully customizable. Our components offer:

• Flexibility: Support dynamic and static procedures.
• Delay Function: Restart processes if needed.
• Standardized Buttons: Based on target area guidelines.

The development of these tools is the foundation for future research.

Available Exports

export {
  Button, ButtonIcon, ButtonMT, Checkbox, Dialog, Radio, RangeNumber, RangeSlider, Slider,
  TextArea, Typography, Select, useDeadlines, useMouseTracker, useMouseTrackerFixedRate, useWindowDimensions,
  MTcalibration, MTdefault, MTdynamic, MTstatic
};

Insall

npm install psychtracker-react

Usage Example

import { Button, useMouseTracker } from 'psychtracker-react';

function App() {
  const [x, y] = useMouseTracker();

  return (
    <div>
      <Button label="Click Me!" onClick={() => alert('Hello!')} />
      <p>Mouse Position: ({x}, {y})</p>
    </div>
  );
}

Components & Hooks

Components:

• Button
• ButtonIcon
• ButtonMT
• Checkbox
• Dialog
• Radio
• RangeNumber
• RangeSlider
• Slider
• TextArea
• Typography
• Select

Hooks:

• useDeadlines
• useMouseTracker
• useMouseTrackerFixedRate
• useWindowDimensions

Experimental MT Components:

• MTcalibration
• MTdefault
• MTdynamic
• MTstatic

Contribution

Contributions are welcome! Please open issues and submit pull requests on GitHub.

Cite

Chaigneau, Amine. (2024). Decoding Movement as Insight into Embodied Decision-Making: Developing a Methodological Toolkit for Investigating Value-Based Choice. University of Rouen; University of Chieti-Pescara.