Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges

S Qiu, H Zhao, N Jiang, Z Wang, L Liu, Y An, H Zhao… - Information …, 2022 - Elsevier
This paper firstly introduces common wearable sensors, smart wearable devices and the key
application areas. Since multi-sensor is defined by the presence of more than one model or …

Active upper limb prostheses: A review on current state and upcoming breakthroughs

A Marinelli, N Boccardo, F Tessari… - Progress in …, 2023 - iopscience.iop.org
The journey of a prosthetic user is characterized by the opportunities and the limitations of a
device that should enable activities of daily living (ADL). In particular, experiencing a bionic …

Human–robot interaction review and challenges on task planning and programming

P Tsarouchi, S Makris… - International Journal of …, 2016 - Taylor & Francis
The wide interest of research and industry in the human–robot interaction (HRI) related
topics is proportional to the increased productivity and flexibility of the production lines, as it …

Multiday EMG-based classification of hand motions with deep learning techniques

M Zia ur Rehman, A Waris, SO Gilani, M Jochumsen… - Sensors, 2018 - mdpi.com
Pattern recognition of electromyography (EMG) signals can potentially improve the
performance of myoelectric control for upper limb prostheses with respect to current clinical …

A framework for hand gesture recognition based on accelerometer and EMG sensors

X Zhang, X Chen, Y Li, V Lantz… - IEEE Transactions on …, 2011 - ieeexplore.ieee.org
This paper presents a framework for hand gesture recognition based on the information
fusion of a three-axis accelerometer (ACC) and multichannel electromyography (EMG) …

A wearable system for recognizing American sign language in real-time using IMU and surface EMG sensors

J Wu, L Sun, R Jafari - IEEE journal of biomedical and health …, 2016 - ieeexplore.ieee.org
A sign language recognition system translates signs performed by deaf individuals into
text/speech in real time. Inertial measurement unit and surface electromyography (sEMG) …

Electromyography-based gesture recognition: Is it time to change focus from the forearm to the wrist?

FS Botros, A Phinyomark… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Despite a historical focus on prosthetics, the incorporation of electromyography (EMG)
sensors into less obtrusive wearable designs has recently gained attention as a potential …

EMPress: Practical hand gesture classification with wrist-mounted EMG and pressure sensing

J McIntosh, C McNeill, M Fraser, F Kerber… - Proceedings of the …, 2016 - dl.acm.org
Practical wearable gesture tracking requires that sensors align with existing ergonomic
device forms. We show that combining EMG and pressure data sensed only at the wrist can …

[PDF][PDF] EMG signal classification for human computer interaction: a review

MR Ahsan, MI Ibrahimy, OO Khalifa - European Journal of …, 2009 - academia.edu
With the ever increasing role of computerized machines in society, Human Computer
Interaction (HCI) system has become an increasingly important part of our daily lives. HCI …

Ultragesture: Fine-grained gesture sensing and recognition

K Ling, H Dai, Y Liu, AX Liu, W Wang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
With the rising of AR/VR technology and miniaturization of mobile devices, gesture
recognition is becoming increasingly popular in the research area of human-computer …