DiagnaMed Holdings Acquires Exclusive Rights to a Virtual Reality and Artificial Intelligence-based Neurodiagnostic System
DiagnaMed Holdings Corp. an artificial intelligence-driven digital diagnostics and therapeutics company for brain health, is pleased to announce that it has entered into an exclusive worldwide license agreement with KU Center for Technology Commercialization, Inc., a non-profit corporation of the University of Kansas, for the development and commercialization of intellectual property of a novel virtual reality and artificial intelligence neurodiagnostic system (“VR/AI Neuro”) for the evaluation, diagnosis and monitoring of neurodegenerative diseases, such as Parkinson’s disease.
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The VR/AI Neuro system complements and strengthens DiagnaMed’s proposed full-spectrum digital diagnostics brain health solutions, which include BRAIN AGE™ and BrainTremor™, for mental health and neurological disorders. Early and accurate diagnosis is still difficult for neurodegenerative conditions like Parkinson’s disease. Evaluations can be time-consuming, patients must often travel to metropolitan areas or different cities to see experts, and misdiagnosis can result in improper treatment. Only a handful of assistive or remote methods exist to help physicians evaluate patients with suspected neurological diseases conveniently and consistently. The VR/AI Neuro system aims to enable clinical and remote neurological diagnosis on a low-cost, portable virtual reality device that can visualize eye movements in videos and interface with the physician who is in a different location than the patient, which may result in more accurate diagnoses, less time spent on making a correct diagnosis for the physician, and lower transportation costs for patients.
The VR/AI Neuro system has been in research and co-development for some time by Kansas University Medical Center, Osaka University and Augusta University. It is designed to support the evaluation and diagnosis of neurodegenerative disease and test its use in a clinical setting. Using a commercially available VR display with an infrared camera integrated into the lens, researchers have constructed a 3D virtual environment designed to emulate common tasks used to evaluate patients, such as fixating on a point, conducting smooth pursuit of an object, or executing saccades. These virtual tasks are designed to elicit eye movements commonly associated with neurodegenerative diseases, such as abnormal saccades, square wave jerks, and ocular tremors. Researchers then conducted experiments with 9 patients diagnosed with Parkinson’s disease and 7 healthy controls to test the VR/AI Neuro system’s potential to emulate tasks for clinical diagnosis. Researchers then applied eye-tracking algorithms and image enhancement to the eye recordings taken during the experiment and conducted a short follow-up study with two physicians for evaluation. Results showed that the VR/AI Neuro system interface could elicit five common types of movements usable for evaluation, physicians could confirm three out of four abnormalities, and visualizations were rated as potentially useful for diagnosis. [1]
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With the success of the proof-of-concept study, the next development stage is to re-implement the tests created in the original research using the updated VR/AI Neuro system and integrate it into a clinical setting with Parkinson’s disease patients with top-line results from the pilot study by mid-2023.
“We are excited to advance the development of a novel virtual reality and artificial intelligence neurodiagnostic system that will aim to change the way neurodegenerative diseases are diagnosed and managed,” said Fabio Chianelli, Chairman of the Board of DiagnaMed. “We are focused on developing and commercializing next-generation digital diagnostic tools for brain health in mental health and neurological disorders. The VR/AI Neuro system complements our product development programs, including BRAIN AGE™ and BrainTremor™, to ensure a full suite of evaluation solutions for healthcare providers to manage their patient’s conditions effectively.”
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