Medical InformaticsIEEE EMBSIEEE EMBS//www.embs.org/wp-content/uploads/2024/06/ieee-embs-tag-tm-logo2x.png
In this issue, vol. 26, issue 5, May 2022, 5 papers are published related to the topic Medical Informatics. Please click here to view them, with link in IEEE XPLORE. read more
In this issue, vol. 26, issue 5, May 2022, 12 papers are published related to the topic Imaging Informatics. Please click here to view them, with link in IEEE XPLORE. read more
In this issue, vol. 26, issue 5, May 2022, 11 papers are published related to the topic Sensor Informatics. Please click here to view them, with link in IEEE XPLORE. read more
Special Issue on AI-driven Informatics, Sensing, Imaging and Big Data Analytics for Fighting the COVID-19 PandemicIEEE EMBSIEEE EMBS//www.embs.org/wp-content/uploads/2024/06/ieee-embs-tag-tm-logo2x.png
In this issue, vol. 26, issue 5, May 2022, 1 paper is published related to the Special Issue on AI-driven Informatics, Sensing, Imaging and Big Data Analytics for Fighting the COVID-19 Pandemic. Please click here to view it, with link in IEEE XPLORE. read more
Special Issue on A Secured and Privacy-preserved Smart Health Monitoring and Improvement SystemIEEE EMBSIEEE EMBS//www.embs.org/wp-content/uploads/2024/06/ieee-embs-tag-tm-logo2x.png
In this issue, vol. 26, issue 5, May 2022, 13 papers are published related to the Special Issue on A Secured and Privacy-preserved Smart Health Monitoring and Improvement System. Please click here to view them, with links in IEEE XPLORE. read more
Atrial Fibrillation Detection and Atrial Fibrillation Burden Estimation via WearablesIEEE EMBSIEEE EMBS//www.embs.org/wp-content/uploads/2024/06/ieee-embs-tag-tm-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/2024/06/ieee-embs-tag-tm-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. read more
Muscle-Specific High-Density Electromyography Arrays for Hand Gesture ClassificationIEEE EMBSIEEE EMBS//www.embs.org/wp-content/uploads/2024/06/ieee-embs-tag-tm-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. read more
Sleep Monitoring Using Ear-Centered Setups: Investigating the Influence From Electrode ConfigurationsIEEE EMBSIEEE EMBS//www.embs.org/wp-content/uploads/2024/06/ieee-embs-tag-tm-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. read more
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/2024/06/ieee-embs-tag-tm-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. read more
