Sports Medicine

Assistive Sliding Mode Control of a Rehabilitation Robot with Automatic Weight Adjustment.

There are approximately 13 million new stroke cases worldwide each year. Research has shown that robotics can provide practical and efficient solutions for expediting post-stroke patient recovery. This simulation study aimed to design a sliding mode controller (SMC) for an end-effector-based rehabilitation robot. A genetic algorithm (GA) was designed for automatic controller weight adjustment. The...

Assessing Vision Quality in Retinal Prosthesis Implantees through Deep Learning: Current Progress and Improvements by Optimizing Hardware Design Parameters and Rehabilitation.

Retinal prosthesis (RP) is used to partially restore vision in patients with degenerative retinal diseases. Assessing the quality of RP-acquired (i.e., prosthetic) vision is needed to evaluate RP impact and prospects. Spatial distortions caused by electrical stimulation of the retina in RP, and the low number of electrodes, have limited the prosthetic vision: patients mostly localize shapes and sh...

Investigation of Machine Learning and Deep Learning Approaches for Detection of Mild Traumatic Brain Injury from Human Sleep Electroencephalogram.

Traumatic Brain Injury (TBI) is a highly prevalent and serious public health concern. Most cases of TBI are mild in nature, yet some individuals may d...

Towards a Gaze-Informed Movement Intention Model for Robot-Assisted Upper-Limb Rehabilitation.

Gaze-based intention detection has been explored for robotic-assisted neuro-rehabilitation in recent years. As eye movements often precede hand moveme...

Adaptive Cooperative Control for Hybrid FES-Robotic Upper Limb Devices: a Simulation Study.

Robotic systems and Functional Electrical Stimulation (FES) are common technologies exploited in motor rehabilitation. However, they present some limi...

Proprioceptive Gaming: Making Finger Sensation Training Intense and Engaging with the P-Pong Game and PINKIE Robot.

Proprioceptive deficits are common after a stroke and are thought to negatively impact motor learning. Despite this, there is a lack of practical robo...

Instantaneous Brain Strain Estimation for Automotive Head Impacts via Deep Learning.

Efficient brain strain estimation is critical for routine application of a head injury model. Lately, a convolutional neural network (CNN) has been su...

[Research Progress on the Application of Artificial Intelligence in Rehabilitation Medicine in China].

The development of science and technology and the increasing demand of rehabilitation have driven the integration between artificial intelligence and ...

Effect of robotic-assisted gait training on functional status, walking and quality of life in complete spinal cord injury.

The purpose of this study was to investigate the effect of robotic-assisted gait training (RAGT) on functional status and the quality of life in patie...

A Bayesian optimization approach for rapidly mapping residual network function in stroke.

Post-stroke cognitive and linguistic impairments are debilitating conditions, with limited therapeutic options. Domain-general brain networks play an ...

The structural connectome and motor recovery after stroke: predicting natural recovery.

Stroke patients vary considerably in terms of outcomes: some patients present 'natural' recovery proportional to their initial impairment (fitters), w...

Learning hidden elasticity with deep neural networks.

Elastography is an imaging technique to reconstruct elasticity distributions of heterogeneous objects. Since cancerous tissues are stiffer than health...

[Interactions between radical prostatovesiculectomy and diagnosis of prostate cancer : A medical-historical inventory on the occasion of 20 years of robot-assisted treatment].

The question of what came first-in this case the diagnosis of prostate cancer or its therapy-seems absurd at first glance and is reminiscent of the cl...

Machine Learning Algorithms Predict Functional Improvement After Hip Arthroscopy for Femoroacetabular Impingement Syndrome in Athletes.

BACKGROUND: Despite previous reports of improvements for athletes following hip arthroscopy for femoroacetabular impingement syndrome (FAIS), many do ...

Data Vizualization Dashboards in Robotic Rehabilitation.

Robotic rehabilitation can offer effective solutions, facilitating physiotherapist work, and helping patients regain their strength. Visualizing resul...

Comparisons between Locomat and Walkbot robotic gait training regarding balance and lower extremity function among non-ambulatory chronic acquired brain injury survivors.

Lower limb rehabilitation exoskeleton robots connect with the human body in a wearable way and control the movement of joints in the gait rehabilitati...

Intelligent body behavior feature extraction based on convolution neural network in patients with craniocerebral injury.

Patients with craniocerebral injury are in serious condition and inconvenient to take care of. This paper proposes a method of extracting the patient'...

[Mirror-type rehabilitation training with dynamic adjustment and assistance for shoulder joint].

The real physical image of the affected limb, which is difficult to move in the traditional mirror training, can be realized easily by the rehabilitat...

[Effect of rehabilitation robot rehabilitation training synchronizing acupuncture exercise therapy on postoperative rehabilitation with hip fracture].

OBJECTIVE: To compare the therapeutic effect between rehabilitation robot rehabilitation training synchronizing acupuncture exercise therapy and simpl...

Effects of passive and active training modes of upper-limb rehabilitation robot on cortical activation: a functional near-infrared spectroscopy study.

OBJECTIVE: The purpose of this study is to investigate the cortical activation during passive and active training modes under different speeds of uppe...