VR/AR, Machine Learning, Computer Vision and Big Data Analytics for Healthcare.
The group of biomedical signals includes:
Using this data, automatic analysis systems can predict in advance the onset of epileptic seizures, fibrillation of the heart, detect hidden pathologies. Based on several data sources, it is possible to automatically evaluate the psychoemotional state of a person with high accuracy.
Imaging methods are:
All the opportunities of using systems for automatic analysis of such data can be hardly enumerated. Some of them are: diagnosis and detection of lesions of internal and external organs, classification and measurement of objects on histological images or, for example, automatic segmentation and classification of damaged teeth on X-ray images.
VR immerses a user in an imagined or replicated world (like video games or medical simulations) or simulates presence in a real world. VR allows to interact with it by simulating his physical presence while the 3D environment he sees is virtual. Examples of hardware in VR: Oculus, Sony PlayStation VR, HTC Vive, Samsung Gear VR. Additional devices like suits, gloves and special cameras provide tracking of hands or full body to allow deeper interaction with the virtual world. They also allow to create team based VR attractions adding physical interaction with real world objects. Contact us to learn how to do that.
AR technology overlays computer-generated information onto a live view of a real environment augmenting the user’s real world with virtual content. It enhances the view and allows the user to manipulate the information. Examples of hardware in AR: Microsoft HoloLens, Google Glass, Magic Leap, Sony SmartEyeglass. Advanced AR requires creating systems capable of understanding the real world around you: the space and the objects, what are they and how you can interact. The strong side of our expertise at Ocutri is that we are capable of building such advanced AR software and middleware. Let`s get in touch!