Atrial Fibrillation Detection and Atrial Fibrillation Burden Estimation via WearablesIEEE EMBSIEEE EMBS//www.embs.org/wp-content/uploads/2023/05/ieee-embs-tag-R-logo2x.png
Atrial Fibrillation (AF) is an important cardiac rhythm disorder, which if left untreated can lead to serious complications such as a stroke. AF can remain asymptomatic, and it can progressively…
Impedance Properties of Multi-Optrode Biopotential Sensing ArraysIEEE EMBSIEEE EMBS//www.embs.org/wp-content/uploads/2023/05/ieee-embs-tag-R-logo2x.png
This work demonstrates the advantage of using an optically inspired, liquid-crystal based biopotential recording technology over a conventional electrode and amplifier system. This optical electrode (optrode) system is favorable for its ability to adjust the input impedance levels in dense-array configurations. We conducted a benchtop experiment and circuit simulations to investigate the relationship between liquid-crystal transducer and interface impedances and the recording-site size in order to better understand the impedance properties of optrodes. This work is the starting point to optimize the layout and configuration of multi-optrode arrays to target various biomedical applications.
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Muscle-Specific High-Density Electromyography Arrays for Hand Gesture ClassificationIEEE EMBSIEEE EMBS//www.embs.org/wp-content/uploads/2023/05/ieee-embs-tag-R-logo2x.png
Muscle-specific, high-density, flexible electromyography (HD-EMG) electrode arrays were designed and applied to capture the myoelectric activity of key intrinsic hand muscles to classify motions and to allow individual analysis of each muscle. Myoelectric activity was displayed as spatio-temporal maps to visualize muscle activation. Time-domain and temporal-spatial HD-EMG features were extracted to train machine machine-learning classifiers to predict user motion, using data collected from intrinsic hand muscles. The muscle-specific electrode arrays can be combined with EMG decomposition techniques to assess motor unit activity and in applications involving the analysis of dexterous hand motions.
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Sleep Monitoring Using Ear-Centered Setups: Investigating the Influence From Electrode ConfigurationsIEEE EMBSIEEE EMBS//www.embs.org/wp-content/uploads/2023/05/ieee-embs-tag-R-logo2x.png
We combine ear-EEG sleep recordings with a state-of-the-art sleep scoring model, ‘seqsleepnet’, to investigate the upper limits of mobile sleep scoring. We manage to further improve on the state of the art in this field, and perform a detailed analysis of the influence of electrode positioning. From this, we find a general rule of thumb that as long a data set contain EOG information and electrode distance on the order of the width of the head, then good automatic sleep scoring is possible. We also find indications that the obtained automatic scoring may be more reliable than the manual scoring.
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Author(s)3: Yi Sun, Yu Qi, Yueming Wang, Cuntai Guan, Yu Sun
Design a Novel BCI for Neurorehabilitation Using Concurrent LFP and EEG Features: A Case Studyhttps://www.embs.org/wp-content/uploads/2022/05/students-laptop.jpg570428IEEE EMBSIEEE EMBS//www.embs.org/wp-content/uploads/2023/05/ieee-embs-tag-R-logo2x.png
This work introduced for the first time a novel BCI that incorporate both intracortical LFP and scalp EEG (named, LFP-EEG-BCI) for motor intention decoding during neurorehabilitation. Concurrent intracortical and scalp signals were collected from a paraplegic patient undergoing motor imagery (MI) neurorehabilitation training. A common spatial filter approach was adopted for feature extraction and a decision fusion strategy was further introduced to obtain the decoding results. Transfer learning approach was also utilized to reduce the calibration. The proposed novel LFP-EEG-BCI may lead to new directions for developing practical neurorehabilitation systems in clinical applications.
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Acoustic beam mapping for guiding HIFU therapy in vivo using sub-therapeutic sound pulse and passive beamforminghttps://www.embs.org/wp-content/uploads/2022/05/icon-med-embs-elections2x.png180180IEEE EMBSIEEE EMBS//www.embs.org/wp-content/uploads/2023/05/ieee-embs-tag-R-logo2x.png
This work aims at deriving the therapeutic energy distribution within the tissue at the pre-treatment stage to guide the HIFU procedure. A beamforming-based energy mapping technique was established to estimate in-situ beam path of the therapeutic energy in a non-invasive way, which is extremely useful in visualizing the sound beam, especially its focal region, for the HIFU surgery. Effectiveness of this technique has been validated with simulations, in-vitro experiments, ex-vivo experiments and in-vivo tests on a rabbit. The technique is safe, easy to be applied in clinical practices, and can potentially be adapted to other ultrasound-related beam manipulating applications.
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TLAs: Are Common These Dayshttps://www.embs.org/wp-content/themes/movedo/images/empty/thumbnail.jpg150150IEEE EMBSIEEE EMBS//www.embs.org/wp-content/uploads/2023/05/ieee-embs-tag-R-logo2x.png
Three-Letter Acronyms (TLAs) are very popular, and can be found in almost everything written or spoken these days. Why? Perhaps it is because we are busy, lazy, or maybe there is just a fascination with things that come in threes. Most likely, we write or speak in TLAs because it makes our language more efficient at conveying information with the least possible cost. TLAs transform largely redundant information into a more expeditious form.
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Advanced Mathematics for Engineering Students: The Essential Toolbox, 1st ed.https://www.embs.org/wp-content/themes/movedo/images/empty/thumbnail.jpg150150IEEE EMBSIEEE EMBS//www.embs.org/wp-content/uploads/2023/05/ieee-embs-tag-R-logo2x.png
The authors of this text have abstracted and summarized in this text their offering of a third-year two semester course in advanced mathematics in the Department of Chemistry and Chemical Engineering at the Royal Military College of Canada. Some applied mathematics matter from related engineering courses has also been added here. With these additions, the text is also purported also to be of value to most other engineers post-graduation. The text was selected for review here as it may be of value to you as a reference or as a foundation teaching text. Some knowledge of COMSOL and MAPLE is needed to fully utilize this text.
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Wearable Tech Marks a Breakthrough for Scanning the Brainhttps://www.embs.org/wp-content/uploads/2022/05/member-kristy-brock2x.jpg450450IEEE EMBSIEEE EMBS//www.embs.org/wp-content/uploads/2023/05/ieee-embs-tag-R-logo2x.png
Today, the World Health Organization (WHO) reports that one in four people are affected by mental or neurological disorders, 50 m suffer from epilepsy, and 50 m from Alzheimer’s disease. According to the Journal of Neurosurgery, 69 m globally have some type of traumatic brain injury. With these numbers rising daily, there is an urgent need to understand what is happening inside the brain. Brain scanning technology has advanced dramatically in recent decades, but it still faces significant limitations.
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Ambitious Climate Goals by the Numbers: Providence Health and Serviceshttps://www.embs.org/wp-content/uploads/2022/05/member-dr-yuanting-zhang.jpg225225IEEE EMBSIEEE EMBS//www.embs.org/wp-content/uploads/2023/05/ieee-embs-tag-R-logo2x.png
Health care systems account for about 10% of the carbon dioxide emitted annually in the USA. In fact, American hospitals produce approximately 6 million tons of waste each year and use approximately 7% of all water consumed in commercial and institutional settings. As climate change becomes a daily reality rather than just a future possibility, major hospital systems are actively pursuing ways to reduce their carbon footprint. In this series, IEEE Pulse explores what steps are being taken and what challenges remain in conversation with different health care systems. This feature focuses on the climate change goals of Providence Health and Services.
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