i-CardiAx: Wearable IoT-Driven System for Early Sepsis Detection Through Long-Term Vital Sign Monitoring

Sepsis is a major cause of premature mortality, high healthcare costs, and disability-adjusted life years. Digital interventions such as continuous cardiac monitoring solutions can help to monitor the patient's status and provide valuable feedback to clinicians to detect early warning signs and provide effective interventions. This paper presents i-CardiAx, a wearable sensor based on low-power high-sensitivity accelerometers that measures vital signs essential for cardiovascular health monitoring, namely, heart rate (HR), blood pressure (BP), and respiratory rate (RR). A dataset has been collected from 10 healthy subjects with the i-CardiAx wearable chest patch to develop low-complexity, lightweight vital sign measurement algorithms and evaluate their performance. The experimental evaluation demonstrates high-performance vital sign measurement for RR (-0.11±0.77 breaths per minute), HR ( 0.82± 2.85 beats per minute), and systolic BP (-0.08 ± 6.245 mm of Hg). The proposed algorithms are embedded on the ARM Cortex-M33 processor supporting Bluetooth Low Energy (BLE). Estimation of HR and RR achieved an inference time of only 4.2 ms and 8.5 ms for BP. Moreover, a multi-channel quantized Temporal Convolutional Neural (TCN) Network has been proposed and trained on the open-source HiRID dataset to have a large number of patients with data for sepsis ground truth. The model has been trained and evaluated using only digitally acquired vital signs as input-data that could be collected by i- CardiAx to detect the onset of Sepsis in a real-time scenario. The TCN has been fully quantized to 8-bit integers and deployed on i-CardiAx.The network showed a median predicted time to sepsis of 8.2 hours with an energy per inference of 1.29mJ. i-CardiAx has a sleep power of 0.152 mW and an averages a power of 0.77 mW for always-on sensing and periodic on-board processing and BLE transmission. With a small 100 mAh battery, the operational longevity of the wearable has been estimated at two weeks (432 hours) for measuring the three cardiovascular parameters (HR, BP and RR) at a granularity of 30 measurements per hour per vital sign, running inference every 30 minutes. Thus, the wearable i-CardiAx system can provide a method to monitor the cardiovascular parameters of patients with energy-efficient, high- sensitivity sensors to provide predictive alerts for life-threatening adverse events of sepsis, over a long period of time.