Digital Assistant for Ventilators Using SVM Algorithm and Speech Recognition

Many health care assists had been developed to help the clinicians in treating the patient. A single monitor for managing an instrument seems very expensive. The transferring of data from the single setup also requires high communication costs. The personal assistant developed has many drawbacks due to the changes in prosodic cues according to the people’s language slang and the trouble in analysing the paralinguistic information. The network data and energy consumption required for the transfer of information from the health care devices becomes quite large. The project, involves an easy transmission module and assisting method to avoid these issues. This project is involved in assisting a practitioner, physician or respiratory therapists in proper handling of a ventilator, in accordance with patient’s health state and parameter. On providing ventilation, it is important to notice the ventilator readings such as iPEEP, Ppeak, Pplat (developed values in the patient’s respiratory system) which are the response of the patient etc.,. On observation of these readings, the parameters such as e-PEEP, VT, RR and FiO2 (values to be set by the clinician) have to be adjusted for better ventilation and for the purpose of weaning of patient in a short period. The preliminary work involved is the data acquisition and logging. The SVM algorithm has been developed with many data points as the parameters obtained from data. The protruding idea is to analyse the patient’s age, gender, weight, disorder, type of surgery and its duration. Thus, the value of the parameter that has to be adjusted can be determined intricately with the protruding idea of digital assist.