The aim of this pilot study was to investigate the feasibility of high-speed gait training with an exoskeleton robot hybrid assistive limb (HAL) in patients with chronic stroke, and to examine the efficacy of eight sessions (8 weeks) of gait training with a HAL compared with conventional physical therapy. Eighteen patients with chronic stroke were included in this study (nine each in the HAL and control groups). The HAL group underwent high-speed gait training with the HAL once a week for 8 weeks (20 min/session). The control group underwent conventional physical therapy for gait disturbance. Outcome measures were walking speed, number of steps, and cadence during a 10 m walking test, a timed up and go test, a functional reach test, and the Berg Balance Scale. Assessments were performed in the absence of the HAL before training and after the fourth and eighth training sessions. All patients in the HAL group completed the high-speed gait training without adverse events. The HAL group improved significantly in walking speed (55.9% increase, P<0.001), number of steps (17.6% decrease, P<0.01), and cadence (32.8% increase, P<0.001) during the 10 m walking test. The patients also exhibited significant improvements in the timed up and go test, the functional reach test, and the Berg Balance Scale after HAL training (P<0.01 in all). No statistical time-dependent changes were observed in any parameter in the control group. For chronic stroke patients, high-speed gait training with a HAL appears to be feasible and effective in improving gait and balance dysfunction despite the limitations of this nonrandomized pilot study.
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http://dx.doi.org/10.1097/MRR.0000000000000132 | DOI Listing |
Sensors (Basel)
December 2024
IRCCS Fondazione Don Carlo Gnocchi, 20148 Milan, Italy.
Background: Wearable powered exoskeletons could be used to provide robotic-assisted gait training (RAGT) in people with stroke (PwST) and walking disability. The study aims to compare the differences in cardiac function, fatigue, and workload during activities of daily living (ADLs), while wearing an exoskeleton.
Methods: Five PwST were recruited in this pilot cross-sectional study.
Sensors (Basel)
December 2024
Department of Neurology, College of Medicine, The Ohio State University, Columbus, OH 43210, USA.
Freezing of gait (FOG) is a debilitating symptom of Parkinson disease (PD). It is episodic and variable in nature, making assessment difficult. Wearable sensors used in conjunction with specialized algorithms, such as our group's pFOG algorithm, provide objective data to better understand this phenomenon.
View Article and Find Full Text PDFMaterials (Basel)
December 2024
Faculty of Mechanical Engineering, Poznan University of Technology, Piotrowo 3 Street, 61-138 Poznan, Poland.
This paper is dedicated to the analysis of a foot prosthesis optimization process, with a particular focus on the application of optimization algorithms and unconventional materials, such as auxetic materials. The study aims to enhance prosthesis performance by minimizing the difference between the ground reaction force generated by the prosthetic foot and that of a natural limb. In the initial part of the study, the basic topics concerning the parameterization of the foot prosthesis geometry and the preparation of a finite element model for human gait are discussed.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
School of Design, Shanghai Jiao Tong University, Shanghai, China.
Background: Alzheimer disease is incurable, but it is possible to intervene and slow down the progression of dementia during periods of mild cognitive impairment (MCI) through virtual reality (VR) technology.
Objective: This study aimed to analyze the effects of VR interventions on older adults with MCI. The examined outcomes include cognitive abilities, mood, quality of life, and physical fitness, including general cognitive function, memory performance, attention and information processing speed, executive function, language proficiency, visuospatial abilities, depression, daily mobility of individuals, muscle performance, and gait and balance.
Comput Biol Chem
December 2024
School of Computing and Information Technology, REVA University, Bengaluru, India.
Autism spectrum disorder (ASD) is the neuro-developmental disorder caused by various changes in the brain. It affects the life conditions with social interaction and communication. Most of the previous researches used the various techniques for the early detection to reduce the ASD, but it had been occurred several complications such as, time expenses, and low accessibility for diagnosis.
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