Motion artifact removal based on ICA for ambulatory ECG monitoring

Tian, Shudong; Han, Jun; Yang, Jianwei; Zhou, Lijun; Zeng, Xiaoyang

doi:10.1109/asicon.2015.7516923

Cited by 6 publications

(3 citation statements)

References 7 publications

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“…The motions of the human body produce some further noises, such as noises linked to the physical motions or breathing. An investigation done by Tian et al 134 showed that raw ECG signals may be misled by various kinds of artifacts, including baseline wandering, power-line interference, and motion. They can result in errors degrading the ECG signal quality and decreasing the precision in estimating cardiac anomalies.…”

Section: Types Of Wearable Sensors and Their Weaknessesmentioning

confidence: 99%

Challenges and limitation of wearable sensors used in firefighters’ protective clothing

Shakeriaski

Ghodrat

2022

Journal of Fire Sciences

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This review aims to present recent improvements and existing challenges in the design of wearable sensors used in the firefighters’ protective clothing. Wearable sensors are generally used directly on the body or placed on wearable items to monitor data for the safety of firefighters. Recently, wearable sensors have attracted much attention from researchers and experts. Most investigations have addressed novel designs for wearable sensors to enhance firefighters’ safety measures and reduce the risk of exposure to fires. This article is an attempt to review design limitations of wearable sensors for future developments and improve existing shortcomings. The growing body of knowledge focused on the application of wearable technology to monitor firefighters’ activity, health, and body temperature. In the following, we have discussed the trials of the design of the existing sensors. Finally, moisture and radiation as common exterior parameters in fire events are discussed which received less attention and have major impact on the performance of firefighters’ wearable sensors.

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Section: Types Of Wearable Sensors and Their Weaknessesmentioning

confidence: 99%

Challenges and limitation of wearable sensors used in firefighters’ protective clothing

Shakeriaski

Ghodrat

2022

Journal of Fire Sciences

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“…In terms of sensor improvement methods, two different principles have been proposed: cancellation of de-noising with a capacitive sensor [27] and de-noising motion bias with an accelerator and gyroscope sensor [28]. In addition, some papers discuss filters for removing motion bias, such as Wavelet [29], ICA [30] and feed-forward combined adaptive [31] filters, which use software-only algorithms to remove noise artifacts.…”

Section: Introductionmentioning

confidence: 99%

Robust Multistage ECG Identification for Astronaut Spacesuits With IoT Applications

et al. 2019

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Today, the Internet of Things (IOT) concept is gaining much attention and popularity; The related technologies as spacesuits and embedded ECG acquisition device is already existed. However, there are important issues to be resolved when an application is in a space environment. The ECG signal may be measured by different mobile conditions when embedded in spacesuits, requiring a more robust algorithm to remove exercise and noise issues. Thus, we propose a more complete architecture with a new storing polymorphic average template (SPAT) and a multistage identification algorithm (MIA) to improve the robustness of ECG identification in motion. In addition, we select better combinations of de-noising and feature extractions to create a better and more complete architecture. According to our experimental results, our proposed architecture offers better performance than previous adaptive boosting (AdaBoost) methods; thus, it is also suitable for application in astronaut spacesuits.

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“…The purpose of ICA is to recover individual sources from a set of observations which are assumed to be a linear mixture of sources. In this application, it is assumed that there are two sources, ECG and the motion artifact, and ICA is performed to separate the two components and recover ECG [19]. Ideally, the number of sensors (observations) should be the same as the number of sources, so this method will work if there are at least two ECG leads.…”

Section: Motion Artifactsmentioning

confidence: 99%

Heart Rate and Heart Rate Variability Estimation in the Presence of Motion Artifacts

Nikolic-Popovic¹

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Vital signs such as heart rate and heart rate variability can be acquired using a variety of equipment, such as ECG, pulse oximeter and even video camera. ECG using wet electrodes is considered the gold standard, but it is not suitable for long-term patient monitoring. Dry electrodes (e.g. a wearable chest-strap) could solve this problem, but the motion of the sensor relative to the skin affects measurements. Non-contact modalities (e.g. heart rate detected from a video of patient's face) could offer further advancements in patient care, but again motion artifacts, caused by changing illumination conditions, affect measurements. Mainstream processing techniques typically assume ideal conditions and fail under realistic conditions. This thesis pinpoints the failure mechanisms of a few commonly used heart rate estimation methods under realistic conditions and proposes mitigation techniques, hoping to contribute to the effort of increasing adoption rate of modern and convenient sensor technologies for patient care.iii

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Motion artifact removal based on ICA for ambulatory ECG monitoring

Cited by 6 publications

References 7 publications

Challenges and limitation of wearable sensors used in firefighters’ protective clothing

Challenges and limitation of wearable sensors used in firefighters’ protective clothing

Robust Multistage ECG Identification for Astronaut Spacesuits With IoT Applications

Heart Rate and Heart Rate Variability Estimation in the Presence of Motion Artifacts

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