AIMC Topic: Hand Strength

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A comprehensive review of dexterous robotic hands: design, implementation, and evaluation.

Bioinspiration & biomimetics
Dexterous robotic hands have been a central focus in robotics research, aiming to replicate the versatility and functionality of the human hand. This review provides a comprehensive analysis of the latest advancements in the literature on dexterous r...

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...

[Research on multi-scale convolutional neural network hand muscle strength prediction model improved based on convolutional attention module].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
In order to realize the quantitative assessment of muscle strength in hand function rehabilitation and then formulate scientific and effective rehabilitation training strategies, this paper constructs a multi-scale convolutional neural network (MSCNN...

Robotically adjustable kinematics in a wrist-driven orthosis eases grasping across tasks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Without finger function, people with C5-7 spinal cord injury (SCI) regularly utilize wrist extension to passively close the fingers and thumb together for grasping. Wearable assistive grasping devices often focus on this familiar wrist-driven techniq...

Reconstruction of Continuous Hand Grasp Movement from EEG Using Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Brain-Computer Interface (BCI) is a promising neu-rotechnology offering non-muscular control of external devices, such as neuroprostheses and robotic exoskeletons. A new yet under-explored BCI control paradigm is Motion Trajectory Prediction (MTP). W...

Artificial touch feedback using microstimulation of human somatosensory cortex to convey grip force from a robotic hand.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Invasive brain-machine interfaces can help restore function through the control of external devices while the addition of intracortical microstimulation (ICMS) can elicit sensations of touch and help provide further benefits for individuals living wi...

Multi-Grasp Classification for the Control of Robot Hands Employing Transformers and Lightmyography Signals.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The increasing use of smart technical devices in our everyday lives has necessitated the use of muscle-machine interfaces (MuMI) that are intuitive and that can facilitate immersive interactions with these devices. The most common method to develop M...