Driving Assistance System for Ambulances to Minimise the Vibrations in Patient Cabin

TL;DR

This paper presents a system that uses sensors and neural networks to select ambulance routes minimizing patient cabin vibrations, potentially improving patient outcomes during transport.

Contribution

It introduces a novel sensor-based system with ANN classification to compare routes based on vibrations and travel time, optimizing ambulance route selection.

Findings

The system achieves 97% accuracy in classifying vibration levels.

It prefers routes with less vibration when travel time differences are minimal.

The shortest route is chosen when time differences exceed 20%, despite higher vibrations.

Abstract

The ambulance service is the main transport for diseased or injured people which suffers the same acceleration forces as regular vehicles. These accelerations, caused by the movement of the vehicle, impact the performance of tasks executed by sanitary personnel, which can affect patient survival or recovery time. In this paper, we have trained, validated, and tested a system to assess driving in ambulance services. The proposed system is composed of a sensor node which measures the vehicle vibrations using an accelerometer. It also includes a GPS sensor, a battery, a display, and a speaker. When two possible routes reach the same destination point, the system compares the two routes based on previously classified data and calculates an index and a score. Thus, the index balances the possible routes in terms of time to reach the destination and the vibrations suffered in the patient cabin to recommend the route that minimises those vibrations. Three datasets are used to train, validate, and test the system. Based on an Artificial Neural network (ANN), the classification model is trained with tagged data classified as low, medium, and high vibrations, and 97% accuracy is achieved. Then, the obtained model is validated using data from three routes of another region. Finally, the system is tested in two new scenarios with two possible routes to reach the destination. The results indicate that the route with less vibration is preferred when there are low time differences (less than 6%) between the two possible routes. Nonetheless, with the current weighting factors, the shortest route is preferred when time differences between routes are higher than 20%, regardless of the higher vibrations in the shortest route.