Real-time hand gesture recognition using surface electromyography and machine learning: A systematic literature review
A Jaramillo-Yánez, ME Benalcázar… - Sensors, 2020 - mdpi.com
Today, daily life is composed of many computing systems, therefore interacting with them in
a natural way makes the communication process more comfortable. Human–Computer …
a natural way makes the communication process more comfortable. Human–Computer …
Adversarial auto-encoder domain adaptation for cold-start recommendation with positive and negative hypergraphs
This article presents a novel model named Adversarial Auto-encoder Domain Adaptation to
handle the recommendation problem under cold-start settings. Specifically, we divide the …
handle the recommendation problem under cold-start settings. Specifically, we divide the …
A novel surface electromyographic signal-based hand gesture prediction using a recurrent neural network
Z Zhang, C He, K Yang - Sensors, 2020 - mdpi.com
Surface electromyographic signal (sEMG) is a kind of bioelectrical signal, which records the
data of muscle activity intensity. Most sEMG-based hand gesture recognition, which uses …
data of muscle activity intensity. Most sEMG-based hand gesture recognition, which uses …
Supervised myoelectrical hand gesture recognition in post-acute stroke patients with upper limb paresis on affected and non-affected sides
A Anastasiev, H Kadone, A Marushima, H Watanabe… - Sensors, 2022 - mdpi.com
In clinical practice, acute post-stroke paresis of the extremities fundamentally complicates
timely rehabilitation of motor functions; however, recently, residual and distorted …
timely rehabilitation of motor functions; however, recently, residual and distorted …
A novel PPG-FMG-ACC wristband for hand gesture recognition
Wrist-based hand gesture recognition has the potential to unlock naturalistic human-
computer interaction for a vast array of virtual and augmented reality applications …
computer interaction for a vast array of virtual and augmented reality applications …
Dynamic gesture recognition based on deep learning in human-to-computer interfaces
Currently, gesture recognition provides a faster, simpler, convenient, effective and more
natural way for human-computer interaction, which has been widely concerned. Gesture …
natural way for human-computer interaction, which has been widely concerned. Gesture …
Is-Net: automatic ischemic stroke lesion segmentation on CT images
Ischemic stroke is an acute cerebral vascular disease and makes up about 80% of all stroke
cases. Noncontrast computed tomography (NCCT) is a widely applied imaging technique for …
cases. Noncontrast computed tomography (NCCT) is a widely applied imaging technique for …
Performance comparison of gesture recognition system based on different classifiers
Y Yang, F Duan, J Ren, J Xue, Y Lv… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The hand plays a very important role in our daily life, and the amputees suffer a lot from the
loss of hands or upper limbs. Hence, assisting devices are desired urgently. Today, the …
loss of hands or upper limbs. Hence, assisting devices are desired urgently. Today, the …
Post-stroke hand gesture recognition via one-shot transfer learning using prototypical networks
Background In-home rehabilitation systems are a promising, potential alternative to
conventional therapy for stroke survivors. Unfortunately, physiological differences between …
conventional therapy for stroke survivors. Unfortunately, physiological differences between …
Temporal frequency joint sparse optimization and fuzzy fusion for motor imagery-based brain-computer interfaces
Background Motor imagery (MI) related features are typically extracted from a fixed
frequency band and time window of EEG signal. Meanwhile, the time when the brain activity …
frequency band and time window of EEG signal. Meanwhile, the time when the brain activity …