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- Weekly Signal: 11
Weekly Signal: 11
Cognixion and Blackrock Neurotech expand global access to a wearable brain-computer interface that blends EEG, AR, and neurofeedback into one research-ready device.

Table of Contents
🧠 Weekly Signal
Neurotechnology News | June 7 – 13, 2025
Let's cut through the noise this week!
👁️ Smartphone AI Tool for Nystagmus Diagnosis
Published: June 5, 2025
Source: Original Article
Researchers have developed a deep learning-powered smartphone system capable of diagnosing nystagmus—a neurological eye movement disorder—using standard video recordings and a cloud-based processing pipeline.
🔬 Key Details:
The system uses video of a patient’s eyes captured via smartphone.
A deep learning algorithm analyzes fast-phase eye movements to distinguish normal from pathological patterns.
Tested against lab-grade videonystagmography (VNG), the system demonstrated comparable accuracy, especially in identifying horizontal jerk nystagmus.
It leverages temporal and spatial features extracted from video frames to track eye velocity, direction, and frequency.
🔹 Why it matters:
This AI tool drastically lowers the barrier to diagnosing vestibular and neurological disorders—especially in emergency rooms, remote clinics, and underserved communities without access to expensive VNG equipment. It's a leap forward in portable, real-time neurodiagnostics with telemedicine potential.
🏥 Endovascular Oculomotor BCI in ALS Patient
Published: June 9, 2025
Source: Cornell University
Researchers successfully demonstrated a minimally invasive brain-computer interface (BCI) that decodes saccadic eye movements using a Stentrode™ endovascular neural implant in a late-stage ALS patient. Unlike traditional BCIs that require open-brain surgery, the Stentrode was inserted via the jugular vein and positioned near brain regions responsible for planning eye movements.
🔬 Key Findings:
The participant, completely paralyzed except for eye movement, performed gaze-based tasks while neural signals were recorded.
Using machine learning, the system could distinguish between eye movement (saccade) and fixation with AUC scores >0.85.
Direction classification (e.g. left vs. up) showed promising results, achieving up to 76% accuracy in some conditions.
Crucially, pre-saccade signals were decodable, indicating the interface taps into cognitive planning, not just muscle movement.
🔹 Why it matters:
This is the first-ever demonstration of decoding oculomotor intent in a human using an endovascular BCI—bridging clinical safety, accuracy, and accessibility. It lays the foundation for future eye-movement-driven communication tools for individuals with severe paralysis or even complete locked-in syndrome, without needing open brain surgery.
🧠 Cognixion and Blackrock Expand Non-Invasive BCI Research with Axon‑R
Published: May 14, 2025
Source: BioSpace
Neurotech companies Cognixion and Blackrock Neurotech have partnered to expand access to Axon‑R, a non-invasive, multimodal BCI and augmented reality (AR) headset, for academic and clinical researchers. Axon‑R integrates brain signal acquisition, neurofeedback, and AR overlays into a single, wearable platform.
🔬 Key Features:
Combines EEG, eye-tracking, and biosensors with AR interaction capabilities.
Supports research into cognition, emotion, motor intent, and adaptive neurofeedback.
Enables researchers to develop and test hands-free interfaces for users with communication or mobility impairments.
🧪 Who Can Use It:
Distributed to academic institutions, hospitals, and clinics globally.
Targeting use in ALS, autism, cerebral palsy, and rehabilitation populations.
🔹 Why it matters:
This collaboration unlocks new potential for low-barrier BCI research by offering a sophisticated, non-surgical platform with real-time neuroadaptive feedback. It empowers more labs to explore neural interaction in naturalistic settings, bridging the gap between clinical neurotechnology and consumer-grade assistive tools.
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