Application of an Emergency Alarm System for Physiological Sensors Utilizing Smart Devices

Abstract

Since innovative smart devices and body sensors including wearables have become prevalent with health informatics such as in Mobile Health (mHealth), we proposed to infer sensed data in sensor nodes to reduce the battery power consumption and bandwidth usage in wireless body area networks. It is critical to raise an alarm when the user is in an urgent situation, which can be done by analysing the sensed data against the user’s activity status utilizing accelerometer sensors. However, when the activity changes frequently, there may be an increase in false alarms, which increases sensing and transferring of data, resulting in higher resource consumption. To reduce and mitigate the problem, we propose verifying the alarm and sending a user feedback using a smart device or smartwatch application so that a user can respond to whether the alarm is true or false. This paper presents a user-feedback system for use in activity recognition to mitigate and improve possible false alarm situations, which will consequently result in helping sensors to reduce the frequency of transactions and transmissions in wireless body area networks. As a contribution, the alarm determination can not only improve the accuracy of the alarm by utilising mobile app screen and speech recognition but can also reduce possible false alarms. It may also communicate with their physician in real-time who can assess the status with health data provided by the sensors.