For tumor tracking therapy, precise knowledge of tumor position in real-time is very important. A technique using single x-ray projection based on a convolutional neural network (CNN) was recently developed which can achieve accurate tumor localizati...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Mar 18, 2020
Brain-machine interfaces (BMIs) can be used to decode brain activity into commands to control external devices. This paper presents the decoding of intuitive upper extremity imagery for multi-directional arm reaching tasks in three-dimensional (3D) e...
Individuals with tetraplegia, typically attributed to spinal cord injuries (SCI) at the cervical level, experience significant health care costs and loss of independence due to their limited reaching and grasping capabilities. Neuromuscular electrica...
Deriving accurate structural maps for attenuation correction (AC) of whole-body positron emission tomography (PET) remains challenging. Common problems include truncation, inter-scan motion, and erroneous transformation of structural voxel-intensitie...
BACKGROUND: Application of machine learning for classifying human behavior is increasingly common as access to raw accelerometer data improves. The aims of this scoping review are (1) to examine if machine-learning techniques can accurately identify ...
OBJECTIVE: For real-time markerless tumour tracking in stereotactic lung radiotherapy, we propose a different approach which uses patient-specific deep learning (DL) using a personalised data generation strategy, avoiding the need for collection of a...
OBJECTIVE: Functional near-infrared spectroscopy (fNIRS) is expected to be applied to brain-computer interface (BCI) technologies. Since lengthy fNIRS measurements are uncomfortable for participants, it is difficult to obtain enough data to train cla...
Human activity recognition is an important and difficult topic to study because of the important variability between tasks repeated several times by a subject and between subjects. This work is motivated by providing time-series signal classification...
Skilled forelimb behaviors are among the most important for studying motor learning in multiple species including humans. This protocol describes learned forelimb tasks for mice using a two-axis robotic manipulandum. Our device provides a highly comp...
Localization of odors is essential to animal survival, and thus animals are adept at odor navigation. In natural conditions animals encounter odor sources in which odor is carried by air flow varying in complexity. We sought to identify potential min...