CNN

LoCoMo-Net: A Low-Complex Deep Learning Framework for sEMG Based Hand Movement Recognition for Prosthetic Control
Author(s)3: Arvind Gautam, Madhuri Panwar, Archana Wankhede, Sridhar Arjunan, Ganesh Naik, Amit Charyya, Dinesh Kumar
LoCoMo-Net: A Low-Complex Deep Learning Framework for sEMG Based Hand Movement Recognition for Prosthetic Control 150 150 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

Background: The enhancement in the performance of the myoelectric pattern recognition techniques based on deep learning algorithm possess computationally expensive and exhibit extensive memory behavior. Therefore, in this paper we…

read more

MyoNet: A Transfer-learning based LRCN for Lower Limb Movement Recognition and Knee Joint Angle Prediction for Remote Monitoring of Rehabilitation Progress from sEMG
Author(s)3: Amit Charyya, Arvind Gautam, Dwaipayan Biswas, Madhuri Panwar
MyoNet: A Transfer-learning based LRCN for Lower Limb Movement Recognition and Knee Joint Angle Prediction for Remote Monitoring of Rehabilitation Progress from sEMG 2138 1075 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

The clinical assessment technology such as remote monitoring of rehabilitation progress for lower limb related ailments rely on the automatic evaluation of movement performed along with an estimation of joint…

read more
The overview of our proposed RegressionCNN. RegressionCNN integrates convolutional feature extraction and holistic regression segmentation model into a unified framework. The cardiac MR images input to the framework directly, and get desired RV boundary.

Correlated Regression Feature Learning for Automated Right Ventricle Segmentation
Author(s)3: Jun Chen, Heye Zhang, Weiwei Zhang, Xiuquan Du, Yanping Zhang, Shuo Li
Correlated Regression Feature Learning for Automated Right Ventricle Segmentation 780 349 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

      Abstract: Accurate segmentation of right ventricle (RV) from cardiac magnetic resonance (MR) images can help doctor to robustly quantify the clinical indices including ejection fraction. In this paper, we…

read more
Search this website