Early decoding of walking tasks with minimal set of EMG channels

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Deep learning has brought incredible progress in areas where traditional algorithms struggle. It can be because they need rules that are sometimes hard to conceptualize, it can also be that the number and manner of combining these rules are too complex to ...

Background :Sensory reafferents are crucial to correct our posture and movements, both reflexively and in a cognitively driven manner. They are also integral to developing and maintaining a sense of agency for our actions. In cases of compromised reafferen ...

Determining whether a molecule can be synthesized is crucial in chemistry and drug discovery, as it guides experimental prioritization and molecule ranking in de novo design tasks. Existing scoring approaches to assess synthetic feasibility struggle to ext ...

Objective: We predicted that accelerometry would be a viable alternative to electromyography (EMG) for assessing fundamental Transcranial Magnetic Stimulation (TMS) measurements (e.g. Resting Motor Threshold (RMT), recruitment curves, latencies). New Metho ...

Reinforcement feedback can improve motor learning, but the underlying brain mechanisms remain underexplored. In particular, the causal contribution of specific patterns of oscillatory activity within the human striatum is unknown. To address this question, ...

IntroductionThe current assessment and standardization of microsurgical skills are subjective, posing challenges in reliable skill evaluation. We aim to address these limitations by developing a quantitative and objective framework for accurately assessing ...

Electrical stimulation of the nervous system has emerged as a promising assistive technology in case of many injuries and illnesses across various parts of the nervous system. In particular, the invasive neuromodulation of the peripheral nervous system see ...

Recently, cutting-edge brain-machine interfaces (BMIs) have revealed the potential of decoders such as recurrent neural networks (RNNs) in predicting attempted handwriting [1] or speech [2], enabling rapid communication recovery after paralysis. However, c ...

Nodal properties are of particular importance when investigating patterns in brain networks. Nodal information is usually studied by comparing a few nodal measurements (up to three), resulting in analyses in three-dimensional spaces, at maximum. We offer a ...

This manuscript is the lecture notes of B. Barak’s course in the Les Houches ‘Statistical Physics and Machine Learning’ summer school in 2022. It surveys various proxies for computational hardness in random planted problems, from the low-degree likelihood ...

The decline of motor ability is a hallmark feature of aging and is accompanied by degeneration of motor synaptic terminals. Consistent with this, Drosophila motor synapses undergo characteristic age -dependent structural fragmentation co -incident with dim ...

Recent advancements in deep learning have found compelling applications in the image-based inspection of infrastructure systems. However, the efficacy of these models hinges significantly on the quality and diversity of the input data used for training. In ...

Animals, including humans, exhibit a remarkable variety of complex behaviours. How the nervous system controls all these behaviours ranging from simple, stereotyped movements to flexible, adaptive actions is a central questions of neuroscience. One of the ...

Non-Bayesian social learning is a framework for distributed hypothesis testing aimed at learning the true state of the environment. Traditionally, the agents are assumed to receive observations conditioned on the same true state, although it is also possib ...

The hands, our silent performers in daily life, face overwhelming challenges when neurological impairments disrupt the simple tasks that compose our daily symphony. This thesis unveils a comprehensive framework for the objective monitoring of upper-limb re ...

The rise of robotic body augmentation brings forth new developments that will transform robotics, human-machine interaction, and wearable electronics. Extra robotic limbs, although building upon restorative technologies, bring their own set of challenges i ...

Neuroprostheses have been used clinically for decades, to help restore or preserve brain functions, when pharmaceutical treatments are inefficient. Although great progress in the field has been made over the years to interface with the nervous system, surf ...

Neural decoding of the visual system is a subject of research interest, both to understand how the visual system works and to be able to use this knowledge in areas, such as computer vision or brain-computer interfaces. Spike-based decoding is often used, ...

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

Subcortical brain structures such as the basal ganglia or the thalamus are involved in regulating motor and cognitive behavior. However, their contribution to perceptual consciousness is still unclear, due to the inherent difficulties of recording subcorti ...

Early decoding of walking tasks with minimal set of EMG channels

Chat with Graph Search

Extending Capabilities of Attention-based Models

Augmenting locomotor perception by remapping tactile foot sensation to the back

FSscore: A Personalized Machine Learning-Based Synthetic Feasibility Score

Accelerometry as a tool for measuring the effects of transcranial magnetic stimulation

Non-invasive stimulation of the human striatum disrupts reinforcement learning of motor skills

An objective skill assessment framework for microsurgical anastomosis based on ALI scores

Biophysically accurate and machine learning-based surrogate models to optimize neuroprosthesis design and operation

33.3 MiBMI: A 192/512-Channel 2.46mm² Miniaturized Brain-Machine Interface Chipset Enabling 31-Class Brain-to-Text Conversion Through Distinctive Neural Codes

Connectome embedding in multidimensional graph spaces

Computational complexity of deep learning: fundamental limitations and empirical phenomena

Trio preserves motor synapses and prolongs motor ability during aging

Uncertainty quantification for a deep learning models for image-based crack segmentation

Uncovering interactions between Descending Neurons as a functional principle of behavioural control

Detection of Malicious Agents in Social Learning

Context-Aware Monitoring of Hand Motor Primitives in Daily Life Activities: A Pathway to Objectively Assess Rehabilitation of Patients with Upper-Limb Neurological Impairment

Investigating neural resource allocation in the sensorimotor control of extra limbs

Unraveling behavior and cortical signals to guide the development of soft neuroprostheses for auditory restoration and spreading depolarization

Predicting Visual Stimuli From Cortical Response Recorded With Wide-Field Imaging in a Mouse

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Subcortical correlates of consciousness with human single neuron recordings