IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
38814776
This paper introduces a lightweight bilateral underactuated upper limb exoskeleton (UULE) designed to assist chronic stroke patients with distal joint (Elbow-Wrist) impairments during bimanual activities of daily living (ADL). The UULE aims to assist...
Journal of bodywork and movement therapies
38876658
INTRODUCTION: Loss of hand function causes severe limitations in activity in daily living. The hand-soft robot is one of the methods that has recently been growing to increase the patient's independence. The purpose of the present systematic review w...
Accurately estimating knee joint angle during walking from surface electromyography (sEMG) signals can enable more natural control of wearable robotics like exoskeletons. However, challenges exist due to variability across individuals and sessions. T...
The use of wearable sensors, such as inertial measurement units (IMUs), and machine learning for human intent recognition in health-related areas has grown considerably. However, there is limited research exploring how IMU quantity and placement affe...
Repetitive overhead tasks during factory work can cause shoulder injuries resulting in impaired health and productivity loss. Soft wearable upper extremity robots have the potential to be effective injury prevention tools with minimal restrictions us...
The Journal of hand surgery, European volume
38861544
Although goniometric measurement is considered the gold standard for the measurement of digital range of motion, visual estimation is often employed due to its simplicity despite being inconsistent with recommended guidelines. We evaluated the Rennes...
BACKGROUND: Improving walking ability is a key objective in the treatment of children and adolescents with cerebral palsy, since it directly affects their activity and participation. In recent years, robotic technology has been implemented in gait tr...
This paper presents an analysis of trunk movement in women with postnatal low back pain using machine learning techniques. The study aims to identify the most important features related to low back pain and to develop accurate models for predicting l...
OpenPose-based motion analysis (OpenPose-MA), utilizing deep learning methods, has emerged as a compelling technique for estimating human motion. It addresses the drawbacks associated with conventional three-dimensional motion analysis (3D-MA) and hu...