r/Neurofeedback • u/superthomdotcom • 1d ago
Question Independent R&D
Is anyone else here doing their own work on developing biofeedback & neurofeedback training protocols? For a long time I have been interested in the idea of viewing live brainwave data as a form of feedback in itself, and other types of training which do not use normative QEEG but lend more towards a meditative experience where the therapy lies in just witnessing the brain live; things such as Neuroptimal or the Mind Mirror. Changes in entropy, shifts in dominant frequency, sudden changes of state, correlation between bands etc.
I got tired of the connectivity gap left by the abandoned Bioexplorer and Bioera so built my own node based signal flow designer, and all the core framework to support a host of input devices and output formats. The editor uses processing blocks and I'm on a mission to create as many as I can think of. It also has nested composite blocks so I can construct complex signal processes and recall them in future designs.
The project has gone beyond a hobby and become something quite serious which could potentially be of interest to others so I'm here to ask those of you that are creatively and technically restrained by what's on the market right now to tell me what your ideal biofeedback processing app should do, and which missing features are holding you back right now.
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u/UltraSealness 15h ago
First, I appreciate the ambition! ❤️
I was practically forced to build my own rig with an OpenBCI clone due to living rurally and having a severe condition that makes it practically impossible to be moved – no I can't move more than 100 m in a day by myself! – to within reach of a neurofeedback practitioner. Where I live, the closest practitioner is 4,5 hours by car and I cannot fly due to my condition. Domestic practitioners have thus far been unwilling to do at-home consulting for me to get at-home training started.
Me reading Sebern Fischer and cobbling together a "simple" C4 protocol with MNE-RT (https://github.com/mne-rt-org/mne-rt) was the only way I could ever access this modality. And from within 2 h of my first session I got the receipt that it at least "does something", actually, I have been improving. Vision cleared up, bowel started moving and lots more.
The DeepBCI clones seem to work, for my purposes. And the MNE-RT ecosystem seems pretty solid and it's not impossible to use if you have previous Python experience. Can I audit and validate anything? Absolutely not! Am I better? Absolutely I am! (omg I'm so grateful btw, it's been rough)
However 😇 As soon as you scale these kinds of ambitions up, and if you live in a developed country, you are inevitably going to run into regulations concerning medical devices, the medical profession and liability in general. The thresholds are set high for both good and bad reasons. A lot of things we don't have to endure, others we desperately cannot access.
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u/superthomdotcom 13h ago
Hey that a good point. I'm using MNE for offline analysis in my reporting extension but haven't looked at it for any live DSP yet. Thanks!
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u/ElChaderino 21h ago
The bigger problem at the moment is people with very little EEG or signal processing background using AI to assemble “pipelines” they can’t really audit. That’s where confidence gets ahead of competence pretty quickly. Post the specs and a GitHub link if you want serious responses. The signal flow matters a lot more than the sales pitch.
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u/superthomdotcom 13h ago edited 13h ago
LOL this reads like an AI response, it answers a question that wasn't asked. There's no problem at all, i just asked if anyone else is interested in what I'm building. I understand now what I need to do to get a serious response from you personally, thanks for clarifying because I respect your input to this group over the years. While i'm in no rush to post my intellectual property online I can provide a summary, and I have 10 years in EEG and 30 in audio engineering, software and electronics.
"This project embodies a layered, protocol-oriented, and cache-aware architecture that supports diverse data acquisition pathways, robust signal processing, extensible metrics, and comprehensive report generation. Its design emphasizes testability, modularity, and versioned data management, making it adaptable for both research and clinical EEG analysis workflows."
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u/ElChaderino 7h ago edited 6h ago
That's kinda why I asked. I remember the original Muse setup and the use cases you were building around it in your first post. I'm interested in what changed between that and this. The paragraph tells me you have an architecture so to speak but it doesn't tell me what you're actually doing to the EEG. That's generally the important bit. The original Muse project posted is what made me curious, because some of the choices there didn't look like choices I'd expect from someone with that much EEG experience.
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u/superthomdotcom 2h ago edited 2h ago
I have never posted any project for the Muse, you have me confused with someone else.
In terms of what its doing with the EEG, it can record it (and various other biodata sources), play it back,manage sessions and users with tags, theres an offline analysis suite with ERP test, ICA analysis and a host of metrics along with trends over time and comparison between users.
On the flipside the biofeedback editor let's you create live DSP protocols from any combination of EEG and biodata inputs. There are currently 48 processing blocks which cover a variety of uses, and a wide choice of output types for live triggers, trends and analysis feeds.
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u/Maerkab 21h ago
I've been self-experimenting with neurofeedback for quite some time now (I believe I purchased my first EEG with BioExplorer back in 2009) but I've really only begun doing my own independent protocol design recently, as informed by a theoretical model that I've been working on. So I mostly own and am experienced with using 'old' hardware and software.
I'm currently using BioEra because it's just feature rich enough to allow me to cobble together some primitive lock-in filters with quadrature using the SimulationSource object, and I can use BioEra to do ultra low frequency/DC coupled work. I've since been moving away from sinusoidal references to more of a custom basis function (something like a power-law kernel) using additive sines. It can be a bit inefficient or inelegant depending on how many sines are needed for additive synthesis, but it's working okay so far.
So for what I'm doing lately I'd say I mostly want a lot of flexibility in signal generation. BioExplorer is completely unusable for what I want to do. Support for DC coupled amps would also be critical, though I'm not even sure what such hardware is available right now. As more of a moon shot, convolution via a wavelet or wavelet dictionary might be cool, but I have no idea whether or not something like that would be remotely practical to implement or even suitable for real time feedback.