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Robotic arms are increasingly being used in collaborative environments, requiring an accurate understanding of human intentions to ensure both effectiveness and safety. Electroencephalogram (EEG) signals, which measure brain activity,…

Signal Processing · Electrical Eng. & Systems 2024-11-20 Byeong-Hoo Lee , Kang Yin

This paper discusses the use of the scalp electric field to decode EEG-recorded brain processes. Instead of using bipolar measurements, the scalp electric field is described as a 3-vector field whose orthogonal components are obtained from…

Neurons and Cognition · Quantitative Biology 2013-07-11 C. G. Carvalhaes , J. Acacio de Barros , M. Perreau-Guimarães , P. Suppes

An Electroencephalogram (EEG) is a non-invasive exam that records the brain's electrical activity. This is used to help diagnose conditions such as different brain problems. EEG signals are taken for epilepsy detection, and with Discrete…

Machine Learning · Computer Science 2024-05-28 Rabel Guharoy , Nanda Dulal Jana , Suparna Biswas , Lalit Garg

During brain function, groups of neurons fire synchronously. When these groups are large enough, the resulting electrical signals can be measured on the scalp using Electroencephalography (EEG). The amplitude of these signals can be…

Neurons and Cognition · Quantitative Biology 2025-02-05 Jesus Acosta-Elias , Santiago Mendez-Moreno , Omar Vital-Ochoa , Ricardo Espinosa-Tanguma

Brain computer interface based assistive technology are currently promoted for motor rehabilitation of the neuromuscular ailed individuals. Recent studies indicate a high potential of utilising electroencephalography (EEG) to extract motor…

Signal Processing · Electrical Eng. & Systems 2019-03-26 Sutanu Bera , Rinku Roy , Debdeep Sikdar , Manjunatha Mahadevappa

Heart disease is one of the most common diseases causing morbidity and mortality. Electrocardiogram (ECG) has been widely used for diagnosing heart diseases for its simplicity and non-invasive property. Automatic ECG analyzing technologies…

Machine Learning · Computer Science 2019-08-28 Yang Liu , Runnan He , Kuanquan Wang , Qince Li , Qiang Sun , Na Zhao , Henggui Zhang

Eye-tracking is an accessible and non-invasive technology that provides information about a subject's motor and cognitive abilities. As such, it has proven to be a valuable resource in the study of neurodegenerative diseases such as…

Machine Learning · Computer Science 2023-11-29 Gonzalo Uribarri , Simon Ekman von Huth , Josefine Waldthaler , Per Svenningsson , Erik Fransén

Background: Mild cognitive impairment (MCI) is often considered a precursor to Alzheimer's disease (AD) due to the high rate of progression from MCI to AD. Sensitive neural biomarkers may provide a tool for an accurate MCI diagnosis,…

Neurons and Cognition · Quantitative Biology 2022-11-02 Adi Wijaya , Noor Akhmad Setiawan , Asma Hayati Ahmad , Rahimah Zakaria , Zahiruddin Othman

Brain Computer Interfaces (BCI) have become very popular with Electroencephalography (EEG) being one of the most commonly used signal acquisition techniques. A major challenge in BCI studies is the individualistic analysis required for each…

Signal Processing · Electrical Eng. & Systems 2019-11-28 Baani Leen Kaur Jolly , Palash Aggrawal , Surabhi S Nath , Viresh Gupta , Manraj Singh Grover , Rajiv Ratn Shah

The electroencephalogram (EEG) has been the gold standard for quantifying mental workload; however, due to its complexity and non-portability, it can be constraining. ECG signals, which are feasible on wearable equipment pieces such as…

Machine Learning · Computer Science 2026-01-13 Malavika Pradeep , Akshay Sasi , Nusaibah Farrukh , Rahul Venugopal , Elizabeth Sherly

Parkinsons Disease (PD) is a progressive neurological disorder that primarily affects motor functions and can lead to mild cognitive impairment (MCI) and dementia in its advanced stages. With approximately 10 million people diagnosed…

Image and Video Processing · Electrical Eng. & Systems 2025-05-02 Abu Saleh Musa Miah , taro Suzuki , Jungpil Shin

Electroencephalography signals allow to explore the functional activity of the brain cortex in a non-invasive way. However, the analysis of these signals is not straightforward due to the presence of different artifacts and the very low…

Neurons and Cognition · Quantitative Biology 2022-01-24 Nicolás Gallego-Molina , Marco Formoso , Andrés Ortiz , Francisco J. Martínez-Murcia , Juan L. Luque

Neurophysiological time series recordings like the electroencephalogram (EEG) or local field potentials are obtained from multiple sensors. They can be decoded by machine learning models in order to estimate the ongoing brain state of a…

Signal Processing · Electrical Eng. & Systems 2023-04-14 Pierre Guetschel , Théodore Papadopoulo , Michael Tangermann

In recent years, sensors from smart consumer devices have shown great diagnostic potential in movement disorders. In this context, data modalities such as electronic questionnaires, hand movement and voice captures have successfully…

Machine Learning · Computer Science 2022-05-13 Catharina Marie van Alen , Alexander Brenner , Tobias Warnecke , Julian Varghese

We explore whether neural networks can decode brain activity into speech by mapping EEG recordings to audio representations. Using EEG data recorded as subjects listened to natural speech, we train a model with a contrastive CLIP loss to…

Sound · Computer Science 2025-11-10 Quentin Auster , Kateryna Shapovalenko , Chuang Ma , Demaio Sun

Parkinson's disease (PD) is a highly heterogeneous disease, including which motor symptoms are dominating. Imaging biomarkers that support subtype stratification could also improve biological understanding and study design, and enable…

Electroencephalogram (EEG) is a prominent way to measure the brain activity for studying epilepsy, thereby helping in predicting seizures. Seizure prediction is an active research area with many deep learning based approaches dominating the…

Signal Processing · Electrical Eng. & Systems 2020-11-19 Zaid Bin Tariq , Arun Iyengar , Lara Marcuse , Hui Su , Bülent Yener

EGG recordings performed on 13 local white rabbits (O. cuniculus) which divided into 3 groups; acetosal 35 mg/kgBM receiver, reserpine 37.5 mg/kgBM receiver, and control group. A total of 72 EGG recordings obtained from them, which divided…

Quantitative Methods · Quantitative Biology 2014-12-09 Tyas Pandu Fiantoro , Lussya Eveline

The Guided Imagery technique is reported to be used by therapists all over the world in order to increase the comfort of patients suffering from a variety of disorders from mental to oncology ones and proved to be successful in numerous of…

Machine Learning · Computer Science 2024-05-29 Filip Postepski , Grzegorz M. Wojcik , Krzysztof Wrobel , Andrzej Kawiak , Katarzyna Zemla , Grzegorz Sedek

The electrocardiogram or ECG has been in use for over 100 years and remains the most widely performed diagnostic test to characterize cardiac structure and electrical activity. We hypothesized that parallel advances in computing power,…

Computer Vision and Pattern Recognition · Computer Science 2018-07-10 Geoffrey H. Tison , Jeffrey Zhang , Francesca N. Delling , Rahul C. Deo
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