Comparative analysis of features and classification techniques in breast cancer detection for Biglycan biomarker images.

Background: Breast cancer (BC) is considered the world's most prevalent cancer. Early diagnosis of BC enables patients to receive better care and treatment, hence lowering patient mortality rates. Breast lesion identification and classification are challenging even for experienced radiologists due to the complexity of breast tissue and variations in lesion presentations.

The association between mobile phone use and neuromusculoskeletal complaints.

Background: Mobile phones have become an essential component in our life. There are many concerns about the effects of prolonged mobile phone use on the upper extremity.

Objective: This research aims to investigate the effects of prolonged mobile phone use on the neuromusculoskeletal system of the upper extremity in young adults in Jordan.

The Effect of Inspiratory Muscle Training on The Pulmonary Function in Mixed Martial Arts and Kickboxing Athletes.

Inspiratory muscle training (IMT) has found its way into athletes' routine as a promising way of improving pulmonary function in combination with standard training. The objective of the study was to examine the effects of resistive IMT on the pulmonary function variables in athletes of two combat sports, i.e.

The Effect of Bilateral Anodal Transcranial Direct Current Stimulation versus Treadmill Training on Brain Activities, Gait Functions, Level of Participation and Enjoyment of Children with Cerebral Palsy: A Randomized Controlled Trial Protocol.

Background: Cerebral palsy (CP) possesses bilateral sensory-motor cortical excitability alterations. In past studies, researchers have applied unilateral anodal transcranial direct stimulation (tDCS) with inconsistent findings.

Objective: Examining the effects of treadmill training with either unilateral or bilateral anodal tDCS stimulation on brain activities, gait, and body functions of children with CP.

Low Vision Profile in Jordan: A Vision Rehabilitation Center-Based Study.

The aim of this paper is to study the profile of persons with low vision in Jordan based on the clinical records of service users who attended the Vision Rehabilitation Center (VRC) at the German Jordanian University (GJU). A retrospective study was conducted by reviewing the archived data for persons with low vision attending the VRC over the period September 2012 to December 2017. The information collected included age, gender, referral, geographical distribution, chief functional visual problems, and ocular pathology.

Awareness of Noise-Induced Hearing Loss and Use of Hearing Protection among Young Adults in Jordan.

Action to prevent noise-induced hearing loss is necessary, especially because many causes of permanent hearing loss are preventable. The aim of this study is to identify and raise awareness of the effect of loud sounds on hearing and effective ways to protect ears among young adults in Jordan. Using non-probability and convenience sampling, 245 students (113 female and 132 males, aged 21.

EEG-Based Brain-Computer Interface for Decoding Motor Imagery Tasks within the Same Hand Using Choi-Williams Time-Frequency Distribution.

This paper presents an EEG-based brain-computer interface system for classifying eleven motor imagery (MI) tasks within the same hand. The proposed system utilizes the Choi-Williams time-frequency distribution (CWD) to construct a time-frequency representation (TFR) of the EEG signals. The constructed TFR is used to extract five categories of time-frequency features (TFFs).

An ensemble-based regression approach for continuous estimation of wrist and fingers movements from surface electromyography.

Late development and evolution of high degree-of-freedom (DOF) robotic hands have seen great technological strides to enhance the quality of life for amputated people. A robust hand kinematic estimation mechanisms have shown promising results to control robotic hands that can mimic the human hand functions and perform daily life hand dexterous tasks. In this paper, we propose an ensemble-based regression approach for continuous estimation of wrist and fingers movements from surface Electromyography (sEMG) signals.