Core Module
Omconsole Core
Central fusion engine that unifies EEG, EMG, gesture, tone and external sensors into a single, AI-tuned control profile. Runs directly on the Omconsole chip or host device.
Unified Neural–Machine Control Layer
Omconsole Neural Control Console
one interface for mind, muscle, gesture, tone & robotics.
Developed by IonCore Energy, the Omconsole Neural Control Console lets users communicate with different mind, muscle and gesture controllers through a single control stack. Early adopters help train the AI, shape node-based updates, and prove the hardware in real environments.
Built onto a custom Omconsole chip for AR, portability, and transferability between devices.
EEG / EMG / Gesture / Voice
Custom Omconsole chip for AR
Node-based AI updates & learning
Signal Fusion
Omconsole Core
Ingests EEG, EMG, gesture & tone from multiple controllers into one control profile.
Custom Chip
Omconsole Node ASIC
On-device processing, AR-ready routing, and transferable control states between hosts.
Mind & Muscle
MindLink & MuscleLink
Adapter layers for different EEG and EMG controllers, normalized into Omconsole events.
Node Updates
Omconsole Node Grid
Early adopters feed back usage data to improve AI models and firmware revisions.
An IonCore Energy system • Custom chip • AR overlay & cross-device transfer
The Omconsole Product Line
A modular, chip-backed stack that talks to different mind, muscle and gesture controllers,
and routes them into robotics, dashboards, AR systems and energy-aware automation.
Mind Interface
MindLink EEG Hub
Interface layer for supported EEG headsets and mind-driven controllers, converting intent patterns into Omconsole events and AI training signals.
Muscle Interface
MuscleLink EMG Bands
Multi-zone EMG interface that reads muscle activity from different bands or armbands and normalizes that activity across supported controllers.
Vision Module
GestureDeck Vision Hub
Camera and AR-friendly interface for hand, eye and body gestures, used for cursor, UI navigation and robotic motion in mixed reality setups.
Audio Module
ToneGate Voice & Tone
Short-form voice and tone interface for wake words, simple commands, hums and beeps – mapped directly into Omconsole actions, even in AR views.
Robotics I/O
RoboBridge I/O Bay
Output bay that binds Omconsole events to robotic arms, mobile bases, relays, heavy equipment and industrial controllers – locally or over a node network.
Where Omconsole Fits
Built for real jobs first: independence rigs, heavy equipment, robotics labs, AR-driven control rooms,
and energy-aware automation under IonCore Energy.
Assistive & Independence Systems
Combine mind, muscle and gesture controllers so users can operate screens, tools and robots
without relying on traditional mouse/keyboard setups.
Mind, muscle & tone combined
Robotics & Automation Labs
Prototype node-based control schemes for robotic arms, mobile platforms and toolheads – your lab
becomes part of the AI training loop.
RoboBridge I/O & Omconsole Core
Industrial Dashboards & Sites
Use AR and dashboards to watch machines, issue commands, and switch control modes
using gestures, EMG or voice when hands are busy.
Control rooms & heavy equipment
Media, Labs & R&D
Explore how different mind, muscle and gesture controllers behave in the same stack
and feed that data into node-based AI updates.
Experiment-ready API & signals
Core Technical Snapshot
Reference Omconsole Stack
| Signal Inputs | EEG, EMG, camera, mic, external sensors |
| Controller Support | Multiple mind / muscle / gesture devices via adapters |
| Latency Target | < 40 ms end-to-end (pipeline-dependent) |
| Output Interfaces | GPIO, serial, CAN, USB, network events, AR overlays |
| Core Hardware | Custom Omconsole chip + host integrations |
| Update Model | Node-based firmware & AI model updates |
Note: the Omconsole chip and software stack are tuned per deployment. Early adopters help
refine controller mappings, safety thresholds and AI behaviours through node-based updates.
How Omconsole Technology Works
Omconsole is designed as a living control layer – every deployment becomes part of the learning network.
Step 01
Connect Controllers
Attach supported mind, muscle and gesture controllers into MindLink, MuscleLink and GestureDeck.
The Omconsole chip and Core normalize their signals.
Step 02
Fuse & Tune
Use tuners and dashboards to set thresholds, modes, dead-zones and safety logic. Signals are fused
into a single Omconsole profile on the chip or host.
Step 03
Map to Robots & AR
Route outputs to robots, tools, or AR UIs via RoboBridge I/O and AR overlays. Control can move with you
between devices without retraining.
Step 04
Learn & Update Nodes
With permission, anonymized usage informs AI and firmware updates. Nodes receive refined mappings
and improvements over time.
Early Adopters & Node-Based Updates
Early Omconsole deployments are not just “beta users” – they are founding nodes in the control network.
Your rigs, labs, and independence setups help teach the AI how real people, real machines, and real sites behave.
Node-based firmware updates
AI mapping improvements
Multi-controller feedback
- • Co-design control schemes for mind, muscle, gesture and tone.
- • Influence how the chip handles AR overlays and cross-device transfer.
- • Get early access to new controller adapters and robotics bindings.
- • Receive node-level updates tuned from real-world usage, not just lab simulations.
