Nowadays the biofeedback devices can easily cooperate with desktop computer applications, however the use of smartphones’ capabilities are limited.
Biofeedback instruments are starting to be used to examine the evolvement of neural system. Until now, the phenomena based examinations were prevailing. However, the biofeedback based measurements can provide direct feedback of the patient’s physiological parameters, revealing new directions in medical diagnosis.
The reason behind the low market penetration was the high cost of these instruments and the costly time of the medical staff. The solution can be a highly automated and aided process, where the smartphones collect the desired physiological parameters via EEG devices and the data can be evaluated off-premise.
While working on my thesis, I participated in a joint research project founded by Stanford University, Budapest University of Technology and Economics and Semmelweis University. The goal of the research was to monitor the fetal nervous system in order to observe the probable factors of early childhood disorders (e.g., epilepsy, cerebral palsy, autism). With the proper identification of the factors, we can have the chance to prevent these disorders.
For the project we needed to develop a measurement framework based on biofeedback instruments. With the aid of this framework, the measurements can be performed even in home environment, without the help of any medical staff.