Applied Neural Diagnosis is a system of software and hardware components aimed at collecting and analyzing neuropsychological data. The final solution will consists of the following:
1) Wireless gyro sensors. These are placed on the patient's joints, and then used to capture streams of motion data. For prototyping sensors are available at major electronics stores.
2) Client application. Doctors use this to connect to sensors, run tests, capture readings from sensors, send data to the cloud, receive diagnosis details from the cloud neural nets, visualize and compare to other similar records.
3) Cloud. This provides central storage of anonymized patient records, runs neural net training tasks, responds to client requests for diagnosis.
Wireless sensors are placed on a patient's body, one sensor per joint, partially of fully covering all the limbs.
Heuristic part consists of mixing data overlays from certain historic periods, filtering raw data, training neural nets to recognize and diagnose certain conditions. With this system doctors can make more robust medical decisions, augment their traditional analysis with our system, incorporate artificial intelligence into their tedious and monotonous review process.
We do not claim that this system is mission critical, it cannot be solely relied on. But we believe it can be certified in the future after passing trials, just like any other medical system.
Heuristic Clinic builds a medical system with a set of software and hardware components for early diagnosis of neuropsychological disorders, such as Parkinson's and Alzheimer's diseases.
We venture into a hard topic of collecting and analyzing physiological information of patients with intent to apply artificial intelligence techniques to historic data records and uncover useful traits. Over the course of studying, experimenting, and prototyping we have arrived at a working solution. This included building a working prototype of a data-collecting hardware-software subsystem. Our vision goes far beyond current achievement.