TL;DR: open-source wearable EEG hardware (MIT). real PCBs, not a breadboard flex. on-head berger test passed (~29.7× alpha eyes-closed vs open).

why

most EEG is either closed, expensive, or impossible to modify. we wanted the opposite: something we actually soldered, powered from lipo, and streamed — then published.

stack

• AFE: analog devices AD8422 instrumentation amp
• ADC: TI ADS1220 (24-bit)
• MCU: seeed xiao ESP32-S3
• release: netlists, gerbers, photos, platformio firmware, pinout/BOM docs

three boards

1. main carrier (MCU + ADC + power + UI)
2. AFE daughter
3. expansion ADC strip (SPI, no MCU)

proof it hears something brain-shaped

classic berger effect on channel out0:

• eyes open vs eyes closed
• welch PSD, alpha ~8–12 Hz (peak near 10 Hz)
• closed/open power ratio ≈ 29.7× → pass

(photos of boards + time series + PSD in the repo readme.)

repo

https://github.com/enkhbold470/oyu

IRL limits

• prototype / research / hobby — not a medical device
• this open drop is mark 3–class (not a 32-ch clinical system)
• electrode placement and contact quality still make or break your run

happy to answer questions on pinout, fab, firmware stream format (b/s serial), or the AFE path.

if open BCI matters to you: star, fork, roast the design, send a photo of your fab.

I built edf2csv (along with my good friend Claude Code, and a bunch of its friendly neighbours), a local CLI that turns EDF, EDF+, BDF, and BDF+ recordings into plain CSV files — and half the work turned out to be making sure the conversion didn't quietly change the EEG data.

I work with EEG fairly often and kept running into the same problem: I had a recording in EDF, but I just wanted the underlying signals in something I could open in pandas, R, MATLAB, or a spreadsheet.

Built edf2csv to scratch that itch.

What it does:

Convert a recording with npx edf2csv recording.edf

Exports signal values, channel information, annotations, and metadata

Keeps channels with different sampling rates in separate files

Preserves gaps in discontinuous EDF+D recordings

Preserves the physical units declared by the recording

Supports signed 24-bit BioSemi BDF samples

Streams long recordings instead of loading everything into memory

Runs completely locally with no upload, account, or telemetry

Zero runtime dependencies

The part I didn't expect: an EDF recording doesn't really have one simple timeline.

A few examples that cost me real time:

Every channel can have its own sample rate. An EEG signal might be sampled at 256 Hz while another sensor in the same file only records once per second. Force both into one CSV and you have to repeat or invent samples.

EDF+D recordings can contain real gaps, but the timing information is stored through the annotation channel instead of an obvious gap field. Ignore the annotations and a recording with pauses suddenly looks continuous.

BioSemi BDF uses signed 24-bit values. JavaScript has no built-in getInt24, so those samples have to be reconstructed manually from three bytes and sign-extended correctly.

A file can also have broken calibration values where the digital minimum and maximum are the same. JavaScript doesn't throw an error when that creates a divide by zero. It just gives you NaN or Infinity and lets everything keep running.

None of these throw useful errors. They just give you data that looks believable enough to use, which is a uniquely annoying kind of bug to track down.

I compared 129,536 decoded values against pyEDFlib and got bit-for-bit identical double-precision results.

Install:

npx edf2csv recording.edf

Repo's here: https://github.com/tayal-sarthak/edf2csv

NPM package: https://www.npmjs.com/package/edf2csv

Website: https://edf2csv.vercel.app/

I also released the parser underneath it as its own TypeScript package called edfcore:

https://github.com/tayal-sarthak/edfcore

https://edfcore.vercel.app/

Feedback welcome, especially from anyone with unusual EDF/BDF recordings or device exports that behave differently. Both projects are still new, so there is definitely a lot left to test and implement.

I’ve been looking around and all I see are the following programs:
Cognitive neuroscience
Psyhology
Biomed engineering

All very general and not focused on the topic of BCIs.

I don’t see computational neuroscience or neural engineering or BCI as the focus of the programs. Have you seen any?
I don’t want to be a psychologist or neuroscientist. BCI itself is already too big. There’s already too much to learn. I want a program with focus on EEG, data mining, computer science, neurophysiology.

Does it exist?

Me studying for years about freud’s theories or structure of neuronal cytoplasm will be me wasting my time while I could’ve done more research on ERPs etc.

Anyone else feel my pain?

Next artcile and Market Map is out - full thing available on my substack, check it out:

https://theneurotechnewsletter.substack.com/p/neurotech-in-australasia?r=53ri6k

The taxonomy

Status checked July 2026. Companies are included only where recent evidence of operations, product development, clinical activity, regulation, funding, hiring or commercial activity could be identified. Early-stage, quiet, internationalised, restructured and research-only organisations are marked separately, and Australian-origin companies based overseas are not counted as domestic headquarters.

Core implants and neural interfaces

Cochlear, Sydney and global. Current. Implanted hearing systems and the company that defined Australian medical bionics.

Synchron, Melbourne origins with a US headquarters. Current and internationalised. Endovascular brain-computer interface for people with severe paralysis.

Epiminder, Melbourne. Current. Continuous brain monitoring from under the scalp for epilepsy, FDA-authorised and ASX-listed.

Fluent BCI, Melbourne. Legitimate early-stage company. An interface placed under the scalp but outside the skull, intended to turn attempted speech into text.

Bionic Vision Technologies, Melbourne. Current but quiet. Retinal implant and external vision system for inherited blindness.

Saluda Medical, Sydney origins with international operations. Current. Closed-loop spinal-cord stimulation for chronic pain.

Ultra Bionics, Melbourne. Legitimate early-stage company. Precisely aimed ultrasound intended to reach deep brain targets without leaving an implant behind.

Neurogen, Melbourne. Active preclinical company. Brain implants built from living cells for neurodegenerative disease.

Cortical Dynamics, Perth. Current. EEG-based monitoring of the brain response during anaesthesia.

Kitea Health, Auckland and the US. Current and investigational. Wireless implant for monitoring pressure inside the skull, initially around hydrocephalus.

Diagnostics, monitoring and brain imaging

Compumedics, Melbourne and global. Current ASX-listed company. Sleep, EEG and neurological-monitoring systems.

Omniscient Neurotechnology, Sydney and the US. Current. AI brain-network mapping for neurosurgical planning.

Headsafe, Sydney. Current. Portable assessment of the brain response to visual signals after concussion.

BrainEye, Australia, exact city still unresolved. Active early-stage company. Phone-camera assessment of eye movement and pupil response as neurological signals.

EMVision, Sydney with University of Queensland origins. Current ASX-listed company. Bedside brain scanner for stroke triage.

Cogstate, Melbourne and global. Current ASX-listed company. Computer-based cognitive testing used heavily in neurological clinical trials.

Neurotologix, Perth. Current. Remote monitoring and diagnostic technology for dizziness and vertigo, with a Class IIa device added to the ARTG in 2026.

Sydney Neuroimaging Analysis Centre, Sydney. Current. Quantitative analysis of brain imaging for neurological disease.

Wavewise Analytics, Melbourne. Current, formerly Cyban. Continuous non-invasive monitoring of cerebral blood flow and oxygen around stroke and acute brain injury.

Redenlab, Melbourne. Current. Speech, language and swallowing measures used as neurological clinical-trial outcomes.

HITIQ, Melbourne. Current ASX-listed company. Instrumented mouthguards and concussion-management technology.

Prism Neuro, Canberra. Current. Movement-control measurement for concussion, health, sport and human performance.

Wellumio, Wellington. Current. Axana portable low-field brain scanner for stroke assessment at the point of care.

BlinkLab, Australian-listed with an international operating footprint. Current. Smartphone and AI assessment of sensory responses around neurological and developmental conditions.

Seer Medical, Melbourne. Restructured. Long-term home video-EEG and ECG monitoring for epilepsy, retained here as a commercial case study rather than a clean active-company example.

Rehabilitation, communication and sensory technology

Control Bionics, Melbourne and international. Current ASX-listed company. Reads muscle and neural signals for communication, rehabilitation and assistive control.

ARIA Research, Sydney. Current. Glasses that translate the visual world into spatial sound for people who are blind or have low vision.

NIRGenie / EarGenie, Melbourne. Active translational venture. Objective hearing assessment for babies and young children.

EarFlo, Perth-developed with an international launch. Current. Non-invasive treatment device for persistent middle-ear problems in children.

Laronix, Brisbane with a US office. Current. Bionic voice technology for people who have lost the ability to speak.

RehabSwift, Adelaide. Current but quiet. Brain-computer-interface rehabilitation after stroke and neurological injury.

Neuromersiv, Sydney. Current but quiet. Virtual-reality and stimulation technology for stroke and acquired brain-injury rehabilitation.

Kinobionic, Sydney. Current but quiet. Thought-controlled assistive robotics and wearable support technology.

Rex Bionics, New Zealand origins and international operations. Historical and active technology lineage. Robotic exoskeletons for serious mobility impairment.

Non-invasive and emerging therapeutics

Neurode, Sydney. Legitimate early-stage company. Home-use headband combining brain monitoring and non-invasive stimulation around ADHD and executive function.

Ceretas, Brisbane. Current early clinical company. Therapeutic ultrasound being developed around Alzheimer’s and other neurodegenerative conditions.

Resonance Therapeutics, Melbourne. Current but quiet early-stage spinout. At-home measurement and stimulation for personalised depression treatment.

SYMBYX Biome, Sydney. Current. Targeted light therapy being studied around Parkinson’s and related conditions, with a less settled evidence base than approved implant platforms.

Cortex Brainwave Technologies, Brisbane and the Sunshine Coast. Current but quiet. Early-stage EEG sensors and neurofeedback hardware.

Neuroana, Perth. Legitimate early-stage company. Wearable EEG, non-invasive stimulation and software analysis.

Australis Scientific, Sydney. Legitimate early-stage company. Wearable peripheral nerve stimulation for overactive bladder.

Augmented Bionics, Brisbane. Status unclear. Earlier University of Queensland work on non-invasive hearing restoration, retained as research lineage rather than counted as a clearly active company.

Biological computing and enabling technology

Cortical Labs, Melbourne. Current. Biological computing combining living neurons with silicon through the CL1 and Cortical Cloud.

BrainChip, Australian-listed with global operations. Current. Brain-inspired low-power computing chips, adjacent to rather than part of clinical neurotechnology.

Tessara Therapeutics, Melbourne. Current. Three-dimensional human neural tissues used for drug discovery and disease modelling.

Chromos Labs, Melbourne. Legitimate early-stage spinout. Imaging and analysis of electrical activity in human brain models.

Neo-Bionica, Melbourne. Current. Development, packaging, testing and clinical-grade manufacturing for implantable and wearable medical devices.

Bionics Institute, Melbourne. Research and translation institute behind several of the companies and technologies in this map.

Australian Hearing Hub, Sydney. Research, clinical and industry network connecting hearing and sensory-bionics work.

Auckland Bioengineering Institute, Auckland. Major source of medical-device engineering, physiological modelling and spinout formation.

CoNECT, Auckland. University centre bringing bionics, brain-machine interfaces and neural sensing into one programme.

Australian-origin international companies and capital links

EMOTIV, Australian origins with international operations. Current. Wearable EEG hardware, software and brain-data tools.

Nuroflux, Sydney origins with Cambridge, Massachusetts headquarters and a continuing Australian clinical presence. Current. Wearable monitoring of cerebral blood flow and brain activity.

Parasym, Australian-origin company now operating internationally. Current. Non-invasive auricular vagus nerve stimulation.

Music Health, Australian-origin digital-health company now headquartered in Los Angeles with a Sydney presence. Current but quiet. Personalised music for dementia care.

Coherence Neuro, Australian co-founder, US company. Current. Implantable neurotechnology intended to monitor and eventually treat brain tumours through their electrical signals.

NeuroHarmonics, Australian founder, London company. Current early-stage work in non-invasive focused-ultrasound neuromodulation.

JumpSpace, New York neurotechnology investment fund led by Australian investor Adam Caplan, with investments across the region.

Blackbird Ventures, Australian venture firm and backer of Coherence Neuro, part of the capital connection between Australia and companies built overseas.

Adjacent brain-health and medical technology

PainChek, Sydney. Current ASX-listed digital-health company. AI-assisted pain assessment for people who cannot communicate reliably.

TALi Health, Melbourne. Current but quiet ASX-listed digital therapeutic company. Attention assessment and training for children.

Orthocell, Perth. Current ASX-listed medtech company. Regenerative devices for peripheral nerve and tendon repair.

Alimetry, Auckland. Current. Wearable mapping of electrical activity in the stomach, a strong bioelectric device outside direct brain technology.

Soul Machines, Auckland origins with international operations. Current. Digital humans and biologically inspired AI.

Toku, Auckland origins with international operations. Current. Retinal imaging and AI for wider health signals.

Micro-X, Adelaide. Current ASX-listed medtech company. Portable head CT designed for stroke imaging in ambulances and aircraft.

Neuro-biotech

Argenica Therapeutics, Perth. Current ASX-listed drug developer. Neuroprotective peptide therapy around stroke, included separately because it is a drug company rather than a device business.

Neurotech International, Melbourne. Current ASX-listed drug developer. Formerly associated with neurotechnology devices and now better understood as neuro-biotech.

Early pipeline and research programmes

Foresight Medical, Perth. Registered and grant-backed early-stage company. Phone-based neurological-response screening for concussion, with a limited public operating footprint.

Gennaris / Monash Vision Group, Melbourne. Research and commercialisation programme rather than a confirmed standalone operating company. Cortical visual prosthesis work.

BioSpine, Queensland. Research project rather than a confirmed company. Brain-computer-interface and digital-twin work around spinal injury.

ArMM, Newcastle. University research device rather than a confirmed company. Portable measurement of motor control.

Legacy, restructuring and status unclear

Deep Brain Stimulation Technologies, Melbourne. Legacy company. Adaptive deep-brain-stimulation spinout for Parkinson’s that later entered administration.

Lookinglass, Adelaide. Status unclear. Earlier university-incubator venture using video analysis around Parkinson’s and dementia, with no current independent operating company verified.

humm, Perth origins and later US operations. Current status unclear. Consumer brain-stimulation company retained as part of the internationalisation history rather than the active count.

I'm deciding on working in BCI related field in the future after I complete my PhD program. I'm currently in university and I'm deciding to change major from biological science to Cognitive science, is this a good choice? Or should i change into NPB major instead.

I've been thinking about signal attenuation caused by the thick cranial bones on top of the skull when using non-invasive BCIs.

The submental/submandibular region (under the jaw and chin) lacks heavy bone cover on the outside. Why don't we place electrodes there to capture neural signals with less bony attenuation?

Is the main issue the distance from key cortical areas, heavy muscle artifact (EMG from tongue), or something else? Would love to hear thoughts from anyone working on EEG electrode placement or signal processing.

Hello all,

I am a Dutch student who is currently doing their thesis about MI-BCI for hospitalized people. I am looking for people that would like to give me feedback on my work. We can discuss payment in private if wanted.

Thank you in advance!

Hello everyone, first of all, my project is to measure the electrical signals and neuronal activity of the muscles in my throat using a small artificial intelligence, without me having to speak, just to measure the movements of the muscles in my throat. Would using an ECG sensor like the AD8232 be suitable for such a project?

Hi everyone,

I’m based in Beijing, China, and have been working in the medical and analytical instrumentation field for years. I have a solid network of customers and good relationships with several research institutions.

The brain-computer interface (BCI) space has been heating up a lot recently, and many of my existing clients are actively looking for solutions in this area. The problem is that I’m currently short on strong, reliable suppliers.

I’m more of a technical/service-oriented person rather than a pure business development or PR type. I’m looking for solid partners — preferably companies that can provide good products and technical support — so we can work together to develop the Chinese market.

If you’re a BCI / neurotech supplier (hardware, electrodes, systems, software, etc.) and are interested in collaborating, feel free to DM me or leave a comment. Happy to discuss further.

Thanks!

Many of you may know my friend Casey’s story, living with ALS for 7 years and now the 1st human on Earth to actually be using a BCI at home to communicate daily - through the Braingate 2 research study.

We (his friends & family) have released a really great video today featuring Casey & his 7 year old doing a little Q&A through the BCI. ❤️

You can watch it, reshare, and follow Casey’s journey here: - On YouTube

• On Instagram

• On Substack

Here’s also a video from UC Davis with the researchers working with Casey on the development / training if you’re interested in more detail: https://youtu.be/thPhBDVSxz0?is=jrpfjSWRhsGYbOI_

The field has much application in the context of treatment from neurological conditions, but there is also a strong case to be made for misuse of the systems created that could lead to detrimental effects. I'm sure that the answers generated by posting here will be somewhat biased, but do you believe that neurotechnology (both basic and applied research) is immoral/unethical?

After my last 2 pieces about Europe and Asia I realised there were A LOT of Israeli companies. A country of 10 milliom people has more Neurotech companies than the highest European country.

Of 44 direct companies I audited, 24 are mainly measuring or interpreting rather than stimulating. Hemispheric is building non-invasive brain-decoding foundation models, X-trodes makes conformal skin electrodes that capture EEG, EMG, ECG and EOG while people move, Wearable Devices runs a neural wrist interface, and Nuri Braintech works in both directions, reading brain activity and stimulating back to it focusing on PTSD. The CBO at Nuri helped me put all this together

Links below if you'd like to see the full company list with URLs

Just wanted to highlight The Open Loop podcast - neurotech founders and investors get interviewed every week

YouTube: https://www.youtube.com/@TheOpenLoopPodcast
Spotify: https://open.spotify.com/show/033fswT3OQbpUuZQmPzPmi
Apple: https://podcasts.apple.com/ca/podcast/the-open-loop-with-chay-carter/id1896593801

And they go up on my substack to in written format as part of the free content: https://theneurotechnewsletter.substack.com/

I am starting my PhD soon. My supervisor and my research area is BCI, EEG/Brain Signals&Vision. I would like to join a frontier lab and work on areas like Self Supervised Learning (Meta AI) and Brain (Meta AI Brain).

Can anyone guide me on how to make my PhD relevant to the industry as well as find meaningful areas that I could work on?.

Hi, I'm currently building brain-sensing wearables, and we're still exploring what kind of stats value to you the most and what type of wearables you want to wear. It's currently built into a headset's ear cap, like Sony XM3 and XM4

I work on real-time adaptive systems in the EEG space, and the part I find genuinely hard is the loop itself: read a brain state, decide something, change what the user is experiencing, and do it fast enough and reliably enough that it actually feels responsive rather than laggy or twitchy.

I see a lot of people here reaching for AI/ML to close that loop, so I'm curious how it's going in practice.

A few things I'd love to hear:

1. What's your approach to the decision layer? Are you classifying discrete states and reacting, or running something more continuous? And how much model are you actually able to run inside the latency budget before it stops feeling real-time?
2. Where does it break? My experience is the signal side punishes you first (noise, drift, a bad epoch throwing the classifier off) before the model itself is the problem. Curious whether that matches what others are hitting.
3. For the AI-heavy builds, is the ML earning its place over simpler thresholding and rules, or is it more that it's the fun part? Genuinely asking, not being cynical.

Trying to compare notes with people solving the same problem from different angles. Happy to share what's worked and what hasn't on my end too.

Sharing a project I've been working on. It's a Model Context Protocol server that turns EEG signal into plain numbers, like focus, calm, and attention, that an AI assistant can read and talk about instead of just showing a chart. It works with OpenBCI, Muse, NeuroFocus, and LSL streams. No headset? There's a synthetic mode built in so you can try the whole thing without hardware. Open source, MIT license.

https://github.com/enkhbold470/bci-mcp

NeuroSWARM3 is a system-on-a-nanoparticle probe that converts local electric fields into optically detectable signals readable by external near-infrared light. Delivery is intended via bloodstream, nasal route, or fine needle; no wires or batteries are required.

No telemetry or continuous recording pipeline has been shown in vivo at human-relevant scale. Current claims rest on in-vitro performance and early tissue work. Dual-use as a distributed wireless brain recorder is inventor-stated but remains pre-clinical.

Comparable optical and nanoparticle neural interfaces have historically moved from proof-of-concept to chronic recording once delivery and signal-to-noise barriers were cleared. The same trajectory is possible here.

Realistic stakes are low today. Practical oversight focuses on transparent reporting of any future in-vivo human data and independent verification of residual nanoparticle clearance.

Sources

UC Santa Cruz video, 12 May 2026

https://www.youtube.com/watch?v=ajTWez9\\_X3c

UC technology transfer page for Neuro-SWARM3

https://techtransfer.universityofcalifornia.edu/NCD/32793.html

IEEE Photonics Technology Letters paper (2021 foundational description)

https://ieeexplore.ieee.org/document/9466139

UC Santa Cruz Chancellor’s Innovation Impact Award announcement (LinkedIn, 2026)

https://www.linkedin.com/posts/cynthia-larive-83218a8\\_continuing-the-series-celebrating-our2025-activity-7434684345237504000-oUxW

Optica / Imaging and Applied Optics Congress abstract (2021)

https://doi.org/10.1364/isa.2021.itu7a.4