AIMC Topic: Fingers

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Screening for Parkinson's disease using "computer vision".

PloS one
BACKGROUND: Identifying bradykinesia is crucial for diagnosing Parkinson's disease (PD). Traditionally, the finger-tapping test has been used, relying on subjective assessments by physicians. Computer vision offers a non-contact and cost-effective al...

Slip-actuated bionic tactile sensing system with dynamic DC generator integrated E-textile for dexterous robotic manipulation.

Nature communications
Dexterous manipulation in robotics requires coordinated sensing, signal processing, and actuation for real-time, precise object control. Despite advances, the current artificial tactile sensory system lacks the proficiency of the human sensory system...

Finger drawing on smartphone screens enables early Parkinson's disease detection through hybrid 1D-CNN and BiGRU deep learning architecture.

PloS one
BACKGROUND: Parkinson's disease (PD), a progressive neurodegenerative disorder prevalent in aging populations, manifests clinically through characteristic motor impairments including bradykinesia, rigidity, and resting tremor. Early detection and tim...

An ultralight, tiny, flexible six-axis force/torque sensor enables dexterous fingertip manipulations.

Nature communications
Multi-dimensional mechanoreceptors are crucial for both humans and robots, providing omnidirectional force/torque senses to ensure dexterous and precise manipulations. Current six-axis force/torque sensors are bulky, heavy, and rigid with complicated...

Trimodal machine learning based biometrics system.

Scientific reports
Biometrics-based authentication systems have recently been considered as one of the safest methods to secure our data or possessions. In the literature, the solutions based on one or two measurable traits are broadly described. There was also claim t...

Investigating the benefits of artificial neural networks over linear approaches to BMI decoding.

Journal of neural engineering
Brain-machine interfaces (BMI) aim to restore function to persons living with spinal cord injuries by 'decoding' neural signals into behavior. Recently, nonlinear BMI decoders have outperformed previous state-of-the-art linear decoders, but few studi...

Evaluating the impact of human expertise in human-centered AI: A case study on finger-tapping video analysis for dementia detection.

Computers in biology and medicine
PURPOSE: Human-centered artificial intelligence (AI) plays a crucial role in medical research. This paper evaluates the impact of human expertise in AI systems, using dementia prediction as a case study. Specifically, plasma phospho-tau181 (ptau181) ...

Enhanced Brain Functional Interaction Following BCI-Guided Supernumerary Robotic Finger Training Based on Sixth-Finger Motor Imagery.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Supernumerary robotic finger (SRF) has shown unique advantages in the field of motor augmentation and rehabilitation, while the development of brain computer interface (BCI) technology has provided the possibility for direct control of SRF. However, ...

Biomimetic rigid-soft finger design for highly dexterous and adaptive robotic hands.

Science advances
In dexterous robotic hand design, achieving high mobility and adaptability comparable to human hands remains an ongoing challenge. Biomimetic designs mimicking the musculoskeletal structure have shown promise yet face difficulties in preserving key k...

Design and Implementation of a Soft-Rigid Hybrid Gripper with Bionic Ligaments and Joint Capsule.

Soft robotics
Dealing with grasping tasks in unstructured environments, existing soft grippers often exhibit a lack of static stability, while rigid-soft hybrid grippers display limited compliance due to the fixed connections at the joints. To address the challeng...