相关论文: MindArm: Mechanized Intelligent Non-Invasive Neuro…
This paper presents a sensorized vision-enabled prosthetic hand aimed at replicating a natural hand's performance, functionality, appearance, and comfort. The design goal was to create an accessible substitution with a user-friendly…
Postoperative upper limb dysfunction is prevalent among breast cancer survivors, yet their adherence to at-home rehabilitation exercises is low amidst limited nursing resources. The hardware overhead of commonly adopted VR-based mHealth…
Beyond providing accurate movements, achieving smooth motion trajectories is a long-standing goal of robotics control theory for arms aiming to replicate natural human movements. Drawing inspiration from biological agents, whose reaching…
Epilepsy is one of the most occurring neurological disease globally emerged back in 4000 BC. It is affecting around 50 million people of all ages these days. The trait of this disease is recurrent seizures. In the past few decades, the…
According to the World Health Organization (WHO), 30 million people are in need of prosthetic and orthotic devices. Some people are born with this limb loss, while others lose limbs due to diseases such as Cancer, diabetes, and work…
When it is tried to control drones, there are many different ways through various devices, using either motions like facial motion, special gloves with sensors, red, green, blue cameras on the laptop or even using smartwatches by performing…
The dexterity of conventional myoelectric prostheses is limited in part by the small datasets used to train the control algorithms. Variations in surface electrode positioning make it difficult to collect consistent data and to estimate…
Advancements in neurosurgical robotics have improved medical procedures, particularly deep brain stimulation, where robots combine human and machine intelligence to precisely implant electrodes in the brain. While effective, this procedure…
Deployment complexity and specialized hardware requirements hinder the adoption of deep learning models in neuroimaging. We present MindGrab, a lightweight, fully convolutional model for volumetric skull stripping across all imaging…
We design a gesture-recognition pipeline for networks of distributed, resource constrained devices utilising Einsum Networks. Einsum Networks are probabilistic circuits that feature a tractable inference, explainability, and energy…
High-density electromyography (HD-EMG) has emerged as a powerful modality for decoding fine-grained neuromuscular activity, enabling real-time neural-machine interfaces (NMIs) for applications such as prosthetic control, rehabilitation, and…
This paper presents the design, control, and applications of a multi-segment soft robotic arm. In order to design a soft arm with large load capacity, several design principles are proposed by analyzing two kinds of buckling issues, under…
The anthropomorphism of grasping process significantly benefits the experience and grasping efficiency of prosthetic hand wearers. Currently, prosthetic hands controlled by signals such as brain-computer interfaces (BCI) and…
The memory demands of large-scale deep neural networks (DNNs) require synaptic weight values to be stored and updated in off-chip memory like dynamic random-access memory, which reduces energy efficiency and increases training time.…
A brain-machine interface (BMI) based on electroencephalography (EEG) can overcome the movement deficits for patients and real-world applications for healthy people. Ideally, the BMI system detects user movement intentions transforms them…
With the development of deep learning processors and accelerators, deep learning models have been widely deployed on edge devices as part of the Internet of Things. Edge device models are generally considered as valuable intellectual…
Cardiac anatomy segmentation is useful for clinical assessment of cardiac morphology to inform diagnosis and intervention. Deep learning (DL), especially with motion information, has improved segmentation accuracy. However, existing…
Brain-machine interfaces (BMIs), particularly those based on electroencephalography (EEG), offer promising solutions for assisting individuals with motor disabilities. However, challenges in reliably interpreting EEG signals for specific…
The aim of this paper is to design and construct an electroencephalograph (EEG) based brain-controlled wheelchair to provide a communication bridge from the nervous system to the external technical device for people of determination or…
This paper will try to delineate the making of a Humanoid prototype intended to assist people with disability (PWD). The assistance that this prototype will offer is rather rudimentary. However, our key focus is to make the prototype…