MyndTec AI
At MyndTec, we are committed to advancing neurotechnology by exploring the potential of artificial intelligence. Our MyndTec AI platform is being developed as a powerful tool in our ongoing research to understand the complexities of the brain and develop innovative treatments for neurological conditions.
MyndTec AI: Our Platform
MyndTec AI, our proprietary AI-driven system, is being developed to leverage multiple brain imaging models and sophisticated machine learning algorithms to study neural patterns and pathways. This platform is designed to enable us to:
- Transform complex brain images into functional models
- Identify cross-patient neural similarities and differences
- Uncover novel, widely applicable treatment approaches
- Analyze intricate brain activation patterns and neural connections
We are focused on exploring several areas using MyndTec AI, including:
- Mapping neural pathways and identifying alternative routes
- Characterizing brain patterns associated with various conditions
- Developing targeted treatments for affected brain regions
MyndTec AI Mobility: Our First Model
Our EEG-based MyndTec AI Mobility model is designed to offer insights into mobility issues through the precise study of brain activity utilizing patented temporal-spectral decomposition, which the company has licensed through the University Health Network.
- Correlates brain signals with movement patterns using advanced AI algorithms
- Enables personalized treatment planning and progress tracking
Our AI model is being developed to use EEG for the detection of brain signals by measuring electrical activities via electrodes placed on the scalp, which are then amplified, recorded, and analyzed as waveforms. Similar to being able to isolate the sound of each individual instrument at different points in the performance of a symphony orchestra playing a complex piece of music, temporal-spectral decomposition of the signal forms a series of frequency values that are matched to a predetermined function that depicts a neurological signal. These values form a table of coefficients that collectively represent a brain electrical signal. By connecting brain signals to movements and utilizing AI, we gain valuable insights into mobility issues and movement patterns to identify correlations and patterns indicative of specific challenges, which can ultimately be used to diagnose conditions, track progress, and tailor treatment plans.
MyndTec AI Future Models
Through our initial work on MyndTec AI Mobility, we would look to enhance the foundational MyndTec AI platform for its broader use, including:
- Identify additional brain tracts for new treatments and therapies, such as personalized pain management
- Explore new neural pathways and brain regions
- Broaden the spectrum of interpretable brain signals