Variable-length accelerometer features and electromyography to improve accuracy of fetal kicks detection during pregnancy using a single wearable device

Abstract

In this paper, we propose a method to improve accuracy of fetal kicks detection during pregnancy using a single wearable device placed on the abdomen. Monitoring fetal wellbeing is key in modern obstetrics as it is routinely used as a proxy to fetal movement. However, accurate, noninvasive, long-term monitoring of fetal movement is challenging, especially outside hospital environments. A few accelerometer-based systems have been developed in the past few years, to tackle common issues in ultrasound measurement and enable remote, self-administrated monitoring of fetal movement. These solutions typically consist in multi-accelerometer systems of limited practical applicability, relying on simple features such as the signal magnitude. In this paper, we propose two methods to improve accuracy of fetal kicks detection using a single wearable device, in particular aiming at reducing false positives and increasing positive predictive value (PPV) when lacking a reference accelerometer outside the abdominal area. Firstly, we propose variable-length accelerometer features. Secondly, we combine accelerometer data with electromyography (EMG). Both the proposed techniques aim at providing more contextual information related to maternal movement while still using a single wearable device. We compare our method to a system comprising 6 accelerometer sensors over a dataset including 22 recordings and reference maternal annotations, highlighting how kicks detection PPV can be improved by up to 10% when including variable-length features and up to 11% when including EMG features.