AIMC Topic: Hand Strength

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A study on a robot arm driven by three-dimensional trajectories predicted from non-invasive neural signals.

Biomedical engineering online
BACKGROUND: A brain-machine interface (BMI) should be able to help people with disabilities by replacing their lost motor functions. To replace lost functions, robot arms have been developed that are controlled by invasive neural signals. Although in...

Robot-supported upper limb training in a virtual learning environment : a pilot randomized controlled trial in persons with MS.

Journal of neuroengineering and rehabilitation
BACKGROUND: Despite the functional impact of upper limb dysfunction in multiple sclerosis (MS), effects of intensive exercise programs and specifically robot-supported training have been rarely investigated in persons with advanced MS.

Design and Fabrication of a Six Degree-of-Freedom Open Source Hand.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Currently, most externally powered prostheses are controlled using electromyography (or EMG), which is the measure of the electrical signals that are produced when voluntary muscle is contracted. One of the major problems is that there are a limited ...

Bioinspired locomotion and grasping in water: the soft eight-arm OCTOPUS robot.

Bioinspiration & biomimetics
The octopus is an interesting model for the development of soft robotics, due to its high deformability, dexterity and rich behavioural repertoire. To investigate the principles of octopus dexterity, we designed an eight-arm soft robot and evaluated ...

An EMG-Controlled Robotic Hand Exoskeleton for Bilateral Rehabilitation.

IEEE transactions on haptics
This paper presents a novel electromyography (EMG)-driven hand exoskeleton for bilateral rehabilitation of grasping in stroke. The developed hand exoskeleton was designed with two distinctive features: (a) kinematics with intrinsic adaptability to pa...

Extrinsic finger and thumb muscles command a virtual hand to allow individual finger and grasp control.

IEEE transactions on bio-medical engineering
Fine-wire intramuscular electrodes were used to obtain electromyogram (EMG) signals from six extrinsic hand muscles associated with the thumb, index, and middle fingers. Subjects' EMG activity was used to control a virtual three-degree-of-freedom (DO...

Artificial hand for minimally invasive surgery: design and testing of initial prototype.

Surgical endoscopy
BACKGROUND: Compared with traditional open surgery, minimally invasive surgery may improve recovery and patient satisfaction while maintaining surgical principles. Laparoscopic, single incision, natural orifice, and robotic approaches hold their own ...

Interpretable machine learning models to predict decline in intrinsic capacity among older adults in China: a prospective cohort study.

Maturitas
BACKGROUND: Monitoring intrinsic capacity and implementing appropriate interventions can support healthy aging. There are, though, few tools available for predicting decline in intrinsic capacity among older adults. This study aimed to develop and va...

Development and Validation of Quantile Regression Forests for Prediction of Reference Quantiles in Handgrip and Chair-Stand Test.

Journal of cachexia, sarcopenia and muscle
BACKGROUND: Muscle strength is one of the key components in the diagnosis of sarcopenia. The aim of this study was to train a machine learning model to predict reference values and percentiles for handgrip strength and chair-stand test (CST), in a la...

Rapid identification of tumor patients with PG-SGA ≥ 4 based on machine learning: a prospective study.

BMC cancer
BACKGROUND: Malnutrition is common in cancer patients and worsens treatment and prognosis. The Patient-Generated Subjective Global Assessment (PG-SGA) is the best tool to evaluate malnutrition, but it is complicated has limited its routine clinical u...