How Accurate are ECG Parameters from Wearable Single-lead ECG System for 24-hours Monitoring

In this work, we propose a wireless wearable system for the acquisition of multiple biopotentials through charge transfer electrostatic sensors realized in MEMS technology. The system is designed for low power consumption and low invasiveness, and thus candidates for long-time monitoring in free-living conditions, with data recording on an SD or wireless transmission to an external elaborator. Thanks to the wide horizon of applications, research is very active in this field, and in the last few years, some devices have been introduced on the market. The main problem with those devices is that their operation is time-limited, so they do not match the growing demand for long monitoring, which is a must-have feature in diagnosing specific diseases. Furthermore, their versatility is hampered by the fact that they have been designed to record just one type of signal. Using ST-Qvar sensors, we acquired an electrocardiogram trace and single-channel scalp electroencephalogram from the frontal lobes, together with an electrooculogram. Excellent results from all three types of acquisition tests were obtained. The power consumption is very low, demonstrating that, thanks to the MEMS technology, a continuous acquisition is feasible for several days.

Section: Tests and Discussionmentioning

confidence: 99%

Long-Term Polygraphic Monitoring through MEMS and Charge Transfer for Low-Power Wearable Applications

Manoni

Gumiero

Zampogna

et al. 2022

“…However, the R-peak period and, consequently, the length of the RR intervals remain independent of the chosen derivation. Accordingly, the HR measurement derived from the RR intervals is derivation-independent [ 38 ].…”

Section: Methods: Biopotential Acquisition By Qvar Sensorsmentioning

confidence: 99%

Multisensor Integrated Platform Based on MEMS Charge Variation Sensing Technology for Biopotential Acquisition

Irrera,

Gumiero,

Zampogna

et al. 2024

We propose a new methodology for long-term biopotential recording based on an MEMS multisensor integrated platform featuring a commercial electrostatic charge-transfer sensor. This family of sensors was originally intended for presence tracking in the automotive industry, so the existing setup was engineered for the acquisition of electrocardiograms, electroencephalograms, electrooculograms, and electromyography, designing a dedicated front-end and writing proper firmware for the specific application. Systematic tests on controls and nocturnal acquisitions from patients in a domestic environment will be discussed in detail. The excellent results indicate that this technology can provide a low-power, unexplored solution to biopotential acquisition. The technological breakthrough is in that it enables adding this type of functionality to existing MEMS boards at near-zero additional power consumption. For these reasons, it opens up additional possibilities for wearable sensors and strengthens the role of MEMS technology in medical wearables for the long-term synchronous acquisition of a wide range of signals.

“…Signal quality monitoring is a paramount initial step for ECG analysis and cardiac markers or event detection. Currently, different metrics can be used for ECG signal quality assessment: signal-to-artifact ratio [ 13 ], signal-to-noise ratio [ 30 ], beats per minute (BPM) [ 31 ], and other derived features such as the slowest, the average, and the fastest heart rate (HR) [ 32 ]. However, previous studies did not assess the change in signal quality over time, which is an important factor in characterizing single-lead patches and possibly improving the materials used and the design.…”

Section: Introductionmentioning

confidence: 99%

Signal Quality Analysis for Long-Term ECG Monitoring Using a Health Patch in Cardiac Patients

Jurado

Lorato

Morales

et al. 2023

Cardiovascular diseases (CVD) represent a serious health problem worldwide, of which atrial fibrillation (AF) is one of the most common conditions. Early and timely diagnosis of CVD is essential for successful treatment. When implemented in the healthcare system this can ease the existing socio-economic burden on health institutions and government. Therefore, developing technologies and tools to diagnose CVD in a timely way and detect AF is an important research topic. ECG monitoring patches allowing ambulatory patient monitoring over several days represent a novel technology, while we witness a significant proliferation of ECG monitoring patches on the market and in the research labs, their performance over a long period of time is not fully characterized. This paper analyzes the signal quality of ECG signals obtained using a single-lead ECG patch featuring self-adhesive dry electrode technology collected from six cardiac patients for 5 days. In particular, we provide insights into signal quality degradation over time, while changes in the average ECG quality per day were present, these changes were not statistically significant. It was observed that the quality was higher during the nights, confirming the link with motion artifacts. These results can improve CVD diagnosis and AF detection in real-world scenarios.