Artificial intelligence (AI) applications have transformed healthcare. This study is based on a
general literature review uncovering the role of AI in healthcare and focuses on the following …

This paper dispenses an exhaustive review on deep learning techniques used in the
prognosis of eight different neuropsychiatric and neurological disorders such as stroke …

Many neurological and musculoskeletal diseases impair movement, which limits people's
function and social participation. Quantitative assessment of motion is critical to medical …

Advances in machine learning and contactless sensors have given rise to ambient
intelligence—physical spaces that are sensitive and responsive to the presence of humans …

Fast and accurate gait phase detection is essential to achieve effective powered lower-limb
prostheses and exoskeletons. As the versatility but also the complexity of these robotic …

Recent advancements in deep learning have produced significant progress in markerless
human pose estimation, making it possible to estimate human kinematics from single …

Many algorithms use 3D accelerometer and/or gyroscope data from inertial measurement
unit (IMU) sensors to detect gait events (ie, initial and final foot contact). However, these …

The ability to identify and temporally segment fine-grained actions in motion capture
sequences is crucial for applications in human movement analysis. Motion capture is …

For abnormal gait recognition, pattern-specific features indicating abnormalities are
interleaved with the subject-specific differences representing biometric traits. Deep …

The stance and swing phases of the gait cycle are defined by foot strike (FS) and foot off
(FO). Accurate determination of these events is thus an essential component of 3D motion …