Gait disorders represent one of the most disabling aspects in multiple sclerosis (MS) that strongly influence patient quality of life. The improvement of walking ability is a primary goal for rehabilitation treatment. The aim of this study is to eva...
Ubiquitous health management (UHM) is vital in the aging society. The UHM services with artificial intelligence of things (AIoT) can assist home-isolated healthcare in tracking rehabilitation exercises for clinical diagnosis. This study combined a pe...
PURPOSE: To identify the short-term effects of robotic-assisted gait training (RAGT) on walking distance, gait speed and functionality of cerebral palsy (CP) patients, and to verify if the effects of RAGT are maintained in the long term.
Passive movement is an important mean of rehabilitation for stroke survivors in the early stage or with greater paralysis. The upper extremity robot is required to assist therapists with passive movement during clinical rehabilitation, while customiz...
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
May 15, 2021
Robot-assisted gait training using a voluntary-driven wearable cyborg, Hybrid Assistive Limb (HAL), has been shown to improve the mobility of patients with neurological disorders; however, its effect on the quality of life (QOL) of patients is not cl...
In the aging world population, the occurrence of neuromotor deficits arising from stroke and other medical conditions is expected to grow, demanding the design of new and more effective approaches to rehabilitation. In this paper, we show how the com...
Journal of neuroengineering and rehabilitation
Apr 21, 2021
BACKGROUND: Manual treadmill training is used for rehabilitating locomotor impairments but can be physically demanding for trainers. This has been addressed by enlisting robots, but in doing so, the ability of trainers to use their experience and jud...
Archives of physical medicine and rehabilitation
Apr 9, 2021
OBJECTIVE: To describe the effect of robotic locomotor training (RLT) and activity-based training (ABT) on cardiovascular indices during various physiological positions in individuals with spinal cord injury.
Out-of-distribution (OOD) in the context of Human Activity Recognition (HAR) refers to data from activity classes that are not represented in the training data of a Machine Learning (ML) algorithm. OOD data are a challenge to classify accurately for ...
Journal of neuroengineering and rehabilitation
Feb 23, 2021
BACKGROUND: Neuroscience and neurotechnology are transforming stroke rehabilitation. Robotic devices, in addition to telerehabilitation, are increasingly being used to train the upper limbs after stroke, and their use at home allows us to extend inst...