A one-handed, temporal input system designed for fast, intuitive text entry using predictive scanning and context-aware phrase selection.
This project explores a new approach to text input that replaces traditional spatial typing with sequential scanning and prediction.
Instead of pressing individual keys, the user selects from a dynamically ordered stream of predicted words and phrases. The system prioritizes likely continuations based on context, reducing the number of selections required to construct full sentences.
- Input is based on timing, not position.
- Operates with a single input action (button, touch, or dwell).
- Enables efficient one-handed use.
- Focus on likely next inputs, not raw characters.
- Primary interaction is phrase-level, not letter-level.
- Letters and symbols are fallback only.
- Tracks recent input (last 1–3 words).
- Predicts:
- next words
- common phrases
- grammatical connectors
Example: Input: I want Suggestions: to, a, the, to build
- Outputs multi-word chunks (e.g. "want to", "build a").
- Reduces total selections required.
- Matches natural language thinking.
- No fixed scan order.
- Predictions are:
- shown earlier
- displayed larger
- held longer (dwell bias)
- Less relevant options appear later.
- No manual switching between:
- letters
- words
- functions
- Context determines what is shown.
- Prediction replaces modes.
- Slower scanning, but fewer decisions.
- Visual hierarchy:
- current item (highlighted)
- next predicted item (emphasized)
- Designed for anticipation and reduced mental load.
- Single or minimal input source
- button
- capacitive touch
- dwell detection
- Context tracking
- Prediction engine (rule-based or adaptive)
- Dynamic scan ordering
- Text generation (phrases, words, characters)
- Optional: HID keyboard output
- Temporal input vs spatial typing
- Phrase prediction vs character entry
- Adaptive scanning vs fixed layouts
- Implicit modes vs manual switching
- Speed achieved by reducing choices, not increasing input rate
To enable fast, low-effort sentence construction by aligning input with natural language flow, rather than traditional keyboard structures.
Prototype stage:
- Python (Tkinter) scanning interface
- Context-based prediction in development
- Hardware integration (touch sensors / microcontrollers) planned
- Predictive phrase expansion
- Adaptive learning (user-specific patterns)
- Hardware integration (capacitive touch / embedded systems)
- HID keyboard implementation
- UI refinement and visualization improvements
TBD
======
The system is designed to operate on a minimal, keyless touch surface, rather than a traditional mechanical keyboard.
- No physical keys
- Flat or slightly contoured surface
- Input via:
- capacitive touch
- pressure / force sensing (optional)
- single or multiple touch zones
- Can be implemented as:
- standalone device
- embedded surface (e.g. desk, armrest, wearable)
- hybrid with existing hardware
Traditional keyboards:
- Require precise spatial targeting
- Depend on finger positioning and travel
- Scale poorly for one-handed use
- Introduce mechanical complexity
This system replaces spatial accuracy with:
- timing-based selection
- predictive ordering
- context-aware input
- No need to locate or press specific keys
- Works with minimal movement or a single contact point
- Fewer moving parts
- Lower mechanical wear
- Potentially lower manufacturing complexity
- Can be:
- compact
- wearable
- integrated into other surfaces
- Not constrained by key layout geometry
- Same system works with:
- one touch point
- multiple zones
- larger touch panels
- Physical interface does not need to encode meaning
- All complexity handled in software (prediction + scanning)
- No physical key press confirmation
- May require visual or haptic feedback alternatives
- Users must adapt to:
- scanning timing
- predictive selection
- Different from conventional typing habits
- System efficiency relies heavily on:
- accuracy of predictions
- relevance of suggested phrases
- If prediction fails, fallback (letters/functions) is slower than a keyboard
- Requires user attention on display
- Not suitable for fully blind typing without additional feedback systems
This is not a direct replacement for a mechanical keyboard in all contexts.
Instead, it represents:
- a software-driven input layer
- decoupled from physical key constraints
- optimized for low-effort, predictive sentence construction
The physical surface is intentionally simplified so that:
intelligence is moved from hardware into the interaction model