ETNA™-MS
The Eye-Tracking Neurological Assessment for Multiple Sclerosis (ETNA™-MS) is a software as a medical device (SaMD) intended to administer a non-invasive test and provide an Expanded Disability Status Scale (EDSS) score in the range between 1.0 and 4.5 for use in tracking the disease progression in MS patients.
Pigio™
Our patented eye-tracking technology was first embodied in Pigio™: a mobile consumer health App with Gaze-to-Speech™ to help voiceless patients communicate using only eye movements. It launched as an iOS iPad App called Pigio™ ICU, allowing Intensive Care Unit patients (conscious but intubated or paralyzed) to communicate through eye movements. By gazing at a particular image for a few seconds on the tablet’s screen, its content is activated, and the chosen audible message is heard. The Pigio™ Pro version includes additional features and screens including media & entertainment access to news and YouTube.
Our Technology
Innodem, a company led by a team of neurologists, neuroscientists, AI experts, data scientists, and software engineers, has patented its newly developed technology in North America, Europe, and Asia. The company’s ongoing pipeline of clinical trials in various neurodegenerative disorders provides well-phenotyped patient data that is ingested by various machine learning algorithms to train them to improve predictability models.
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A gaze mapping biomarker, or GMB, is a quantitative measure of human cognition that analyzes the gaze patterns produced while performing short visual tasks. GMBs can help assess cognitive function such as attention, processing speed, working memory, and response inhibition. GMBs have shown that they can aid in disease tracking.
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An eye movement biomarker, or EMB, is a quantitative measure of eye movements that can assist to diagnose or monitor various neurological disorders. Some examples of EMBs are saccades, anti-saccades, pursuit, velocity, latency and amplitude.
Read moreClinical Trials
This study aims to develop and validate a sensitive and non-invasive eye-tracking software application.
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This study aims to develop and validate a sensitive and non-invasive eye-tracking software application.
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This study aims to develop and validate a sensitive and non-invasive eye-tracking software application.
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The overarching goal of this research protocol is to acquire eye-tracking, cognitive, and disease-severity metrics in multiple sclerosis (MS) patients to further build up a database of MS patients and train a machine learning classifying algorithms to identify which eye-tracking metrics-or combination thereof-can serve as reliable markers of MS disease severity and cognitive status.
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This study aims to develop and validate a sensitive and non-invasive eye-tracking software application.
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