EMG pattern recognition in the era of big data and deep learning

A Phinyomark, E Scheme - Big Data and Cognitive Computing, 2018 - mdpi.com
The increasing amount of data in electromyographic (EMG) signal research has greatly
increased the importance of develo** advanced data analysis and machine learning …

Machine learning methods, databases and tools for drug combination prediction

L Wu, Y Wen, D Leng, Q Zhang, C Dai… - Briefings in …, 2022 - academic.oup.com
Combination therapy has shown an obvious efficacy on complex diseases and can greatly
reduce the development of drug resistance. However, even with high-throughput screens …

Assessment of punching shear strength of FRP-RC slab-column connections using machine learning algorithms

GT Truong, HJ Hwang, CS Kim - Engineering Structures, 2022 - Elsevier
Recently, the use of fiber-reinforced polymer (FRP) bars replacing steel reinforcement has
been widely applied to overcome the corrosion issue, particularly concrete slab-column …

Artificial intelligence in drug combination therapy

IF Tsigelny - Briefings in bioinformatics, 2019 - academic.oup.com
Currently, the development of medicines for complex diseases requires the development of
combination drug therapies. It is necessary because in many cases, one drug cannot target …

Golf swing segmentation from a single IMU using machine learning

M Kim, S Park - Sensors, 2020 - mdpi.com
Golf swing segmentation with inertial measurement units (IMUs) is an essential process for
swing analysis using wearables. However, no attempt has been made to apply machine …

A review of dynamic models and measurements in golf

J McPhee - Sports Engineering, 2022 - Springer
A narrative review of dynamic models of golf phenomena is presented, as well as current
technologies for measuring the motions of a golfer, club, and ball. Kinematic and dynamic …

Sock-type wearable sensor for estimating lower leg muscle activity using distal EMG signals

T Isezaki, H Kadone, A Niijima, R Aoki, T Watanabe… - Sensors, 2019 - mdpi.com
Lower leg muscle activity contributes to body control; thus, monitoring lower leg muscle
activity is beneficial to understand the body condition and prevent accidents such as falls …

Comparing the performance of machine learning methods in estimating the shear wave transit time in one of the reservoirs in southwest of Iran

MR Dehghani, S Jahani, A Ranjbar - Scientific Reports, 2024 - nature.com
Shear wave transit time is a crucial parameter in petroleum engineering and geomechanical
modeling with significant implications for reservoir performance and rock behavior …

Dimensionality reduction for classification of object weight from electromyography

E Lashgari, U Maoz - Plos one, 2021 - journals.plos.org
Electromyography (EMG) is a simple, non-invasive, and cost-effective technology for
measuring muscle activity. However, multi-muscle EMG is also a noisy, complex, and high …