Early decoding of walking tasks with minimal set of EMG channels

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Related publications (31)

Investigating the roles of reflexes and central pattern generators in the control and modulation of human locomotion using a physiologically plausible neuromechanical model

Auke Ijspeert, Andrea Di Russo, Stéphane Armand, Dimitar Yuriev Stanev, Anushree Bapusaheb Sabnis

Objective. Studying the neural components regulating movement in human locomotion is obstructed by the inability to perform invasive experimental recording in the human neural circuits. Neuromechanical simulations can provide insights by modeling the locom ...

Iop Publishing Ltd2023

Understanding motor control and impairment: An upper-limb model for muscular assessment

Tristan Jean Robin Barjavel

The human upper limb is a complex musculoskeletal system that can still perform various tasks with impressive efficacy thanks to the ability of the central nervous system to control and modulate the activation of more than 40 muscles. Stroke is a leading ...

EPFL2023

Learnable latent embeddings for joint behavioural and neural analysis

Mackenzie Mathis, Steffen Schneider, Jin Hwa Lee

Mapping behavioural actions to neural activity is a fundamental goal of neuroscience. As our ability to record large neural and behavioural data increases, there is growing interest in modelling neural dynamics during adaptive behaviours to probe neural re ...

NATURE PORTFOLIO2023

Neuronal correlates of goal-directed sensorimotor transformation in sensory, motor and higher-order cortical areas

Anastasiia Oryshchuk

An important function of the brain is to interpret incoming sensory information from the outside world to guide adaptive behavior. Understanding how and where sensory information is transformed into motor commands in a context- and learning-dependent manne ...

EPFL2023

Identifying important sensory feedback for learning locomotion skills

Auke Ijspeert, Milad Shafiee Ashtiani, Guillaume Denis Antoine Bellegarda

Robot motor skills can be acquired by deep reinforcement learning as neural networks to reflect state-action mapping. The selection of states has been demonstrated to be crucial for successful robot motor learning. However, because of the complexity of neu ...

NATURE PORTFOLIO2023

Mechanisms underlying reinforcement learning of motor skills

Pierre Theopistos Vassiliadis

Motor learning allows animals, including human beings, to acquire skills that are es-sential for efficient interactions with the environment. This ability to learn new motor skills is of great practical relevance for daily-life activities (such as when lea ...

EPFL2023

Combining biophysical models and machine learning to optimize implant geometry and stimulation protocol for intraneural electrodes

Silvestro Micera, Simone Romeni, Elena Losanno, Luca Pierantoni

Objective. Peripheral nerve interfaces have the potential to restore sensory, motor, and visceral functions. In particular, intraneural interfaces allow targeting deep neural structures with high selectivity, even if their performance strongly depends upon ...

IOP Publishing Ltd2023

Noninvasive theta-burst stimulation of the human striatum enhances striatal activity and motor skill learning

Elena Beanato, Pablo Maceira Elvira, Esra Neufeld, Friedhelm Christoph Hummel, Takuya Morishita, Maximilian Jonas Wessel, Chang-Hyun Park, Traian Popa, Pierre Theopistos Vassiliadis, Pauline Menoud, Fabienne Windel

The stimulation of deep brain structures has thus far only been possible with invasive methods. Transcranial electrical temporal interference stimulation (tTIS) is a novel, noninvasive technology that might overcome this limitation. The initial proof-of-co ...

Nature Portfolio2023

Puppeteer and Marionette: Learning Anticipatory Quadrupedal Locomotion Based on Interactions of a Central Pattern Generator and Supraspinal Drive

Auke Ijspeert, Milad Shafiee Ashtiani, Guillaume Denis Antoine Bellegarda

Quadruped animal locomotion emerges from the interactions between the spinal central pattern generator (CPG), sensory feedback, and supraspinal drive signals from the brain. Computational models of CPGs have been widely used for investigating the spinal co ...

IEEE2023

Automatic Body Segment and Side Recognition of an Inertial Measurement Unit Sensor during Gait

Kamiar Aminian, Xavier Crevoisier, Robin Martin

Inertial measurement unit (IMU) sensors are widely used for motion analysis in sports and rehabilitation. The attachment of IMU sensors to predefined body segments and sides (left/right) is complex, time-consuming, and error-prone. Methods for solving the ...

MDPI2023

Early motor skill acquisition in healthy older adults: brain correlates of the learning process

Manon Chloé Durand-Ruel, Pablo Maceira Elvira, Friedhelm Christoph Hummel, Takuya Morishita, Maeva Moyne, Chang-Hyun Park

Motor skill learning is a crucial process at all ages. However, healthy aging is often accompanied by a reduction in motor learning capabilities. This study characterized the brain dynamics of healthy older adults during motor skill acquisition and identif ...

OXFORD UNIV PRESS INC2023

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