Gesture recognition for transhumeral prosthesis control using EMG and NIR E Nsugbe, C Phillips, M Fraser, J McIntosh IET Cyber‐Systems and Robotics 2 (3), 122-131, 2020 | 76 | 2020 |
Toward a self-supervised architecture for semen quality prediction using environmental and lifestyle factors E Nsugbe Artificial Intelligence and Applications 1 (1), 35-42, 2023 | 52 | 2023 |
Contrast of multi‐resolution analysis approach to transhumeral phantom motion decoding E Nsugbe, O William Samuel, MG Asogbon, G Li CAAI Transactions on Intelligence Technology 6 (3), 360-375, 2021 | 39 | 2021 |
Phantom motion intent decoding for transhumeral prosthesis control with fused neuromuscular and brain wave signals E Nsugbe, OW Samuel, MG Asogbon, G Li IET Cyber‐Systems and Robotics 3 (1), 77-88, 2021 | 36 | 2021 |
Estimation of fine and oversize particle ratio in a heterogeneous compound with acoustic emissions E Nsugbe, C Ruiz-Carcel, A Starr, I Jennions Sensors 18 (3), 851, 2018 | 34 | 2018 |
Brain-machine and muscle-machine bio-sensing methods for gesture intent acquisition in upper-limb prosthesis control: A review E Nsugbe Journal of Medical Engineering & Technology 45 (2), 115-128, 2021 | 31 | 2021 |
Estimation of powder mass flow rate in a screw feeder using acoustic emissions C Ruiz-Carcel, A Starr, E Nsugbe Powder technology 336, 122-130, 2018 | 27 | 2018 |
Particle size distribution estimation of a mixture of regular and irregular sized particles using acoustic emissions E Nsugbe, A Starr, I Jennions, CR Carcel Procedia Manufacturing 11, 2252-2259, 2017 | 26 | 2017 |
Size differentiation of a continuous stream of particles using acoustic emissions E Nsugbe, A Starr, P Foote, C Ruiz-Carcel, I Jennions IOP Conference Series: Materials Science and Engineering 161 (1), 012090, 2016 | 26 | 2016 |
Particle size distribution estimation of a powder agglomeration process using acoustic emissions E Nsugbe | 25 | 2017 |
Enhancing care strategies for preterm pregnancies by using a prediction machine to aid clinical care decisions E Nsugbe, O Obajemu, OW Samuel, I Sanusi Machine Learning with Applications 6, 100110, 2021 | 24 | 2021 |
Towards an affordable magnetomyography instrumentation and low model complexity approach for labour imminency prediction using a novel multiresolution analysis E Nsugbe, I Sanusi Applied AI Letters 2 (3), e34, 2021 | 22 | 2021 |
Multiscale depth of anaesthesia prediction for surgery using frontal cortex electroencephalography E Nsugbe, S Connelly Healthcare Technology Letters 9 (3), 43-53, 2022 | 20 | 2022 |
An artificial intelligence-based decision support system for early diagnosis of polycystic ovaries syndrome E Nsugbe Healthcare Analytics 3, 100164, 2023 | 18 | 2023 |
Intelligence combiner: a combination of deep learning and handcrafted features for an adolescent psychosis prediction using EEG signals E Nsugbe, OW Samuel, MG Asogbon, G Li 2022 IEEE International Workshop on Metrology for Industry 4.0 & IoT …, 2022 | 17 | 2022 |
Application of noninvasive magnetomyography in labour imminency prediction for term and preterm pregnancies and ethnicity specific labour prediction E Nsugbe, O Obajemu, OW Samuel, I Sanusi Machine Learning with Applications 5, 100066, 2021 | 17 | 2021 |
Shoulder girdle recognition using electrophysiological and low frequency anatomical contraction signals for prosthesis control E Nsugbe, AH Al‐Timemy CAAI Transactions on Intelligence Technology 7 (1), 81-94, 2022 | 16 | 2022 |
A self-learning and adaptive control scheme for phantom prosthesis control using combined neuromuscular and brain-wave bio-signals E Nsugbe, OW Samuel, MG Asogbon, G Li Engineering Proceedings 2 (1), 59, 2020 | 16 | 2020 |
Monitoring the particle size distribution of a powder mixing process with acoustic emissions: a review E Nsugbe, A Starr, C Ruiz Carcel Engineering & Technology Reference, 2016 | 16 | 2016 |
A pilot exploration on the use of NIR monitored haemodynamics in gesture recognition for transradial prosthesis control E Nsugbe Intelligent Systems with Applications 9, 200045, 2021 | 15 | 2021 |