A CONCEPTUAL STUDY ON INTERNET OF THINGS IMPLEMENTATION TO IMPROVE ACCURACY OF PRE-HOSPITAL CARE USING SMART STETHOSCOPES

Ever-evolving Pre-Hospital Care and Emergency Medical Services comes with great challenges. This paper provides a fundamental leap towards collaboration of Medicine and ICT, benefiting mankind There were three major issues faced by pre-hospital care staff from the emergency department which are lack of sound interpretation accuracy due to the interference of noise during transfer, lack of acoustic performance accuracy during transfer and lack of resource and resource management. These issues lead to delay in patient transfer to the hospital or even delay in diagnosis as the sound is not accurately interpreted by the medical practitioners due to the interference of noise and unfavourable situations during transfer. This is also imposing on the overcrowding of emergency departments and increase of waiting time due to shortage of authorised medical personnel to be on the floor for clinical. Based on the literature, the use of hybrid neural networks with bio-inspired methods to improve the efficiency in detection and classification of sounds and enables searching of similar sounds to direct towards accurate diagnostic and management pathways. This solution might benefit largely in the improvement of clinical decision making and health care provided in terms of accuracy and limiting waiting time. Besides that, data collected will be able to serve as important evidence in court for medicolegal cases in enforcing jurisdiction and stature.