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Recent advancements in powered lower limb prostheses have led to the development of neural-machine interfaces for natural control during bipedal locomotion. In particular, electromyography (EMG) patterns recorded from the amputated limb can be leveraged to infer the intended gait pattern of the user. However, the optimal control strategy for translating the EMG patterns to kinematic space remains...
This paper presents a framework for modeling neural decoding using electromyogram (EMG) and electrocorticogram (ECoG) signals to interpret human intent and control prosthetic arms. Specifically, the method of this paper employs Markov Decision Processes (MDP) for neural decoding, parameterizing the policy using an artificial neural network. The system is trained using a modification of the Dataset...
In recent years, a significant effort has been invested in the development of kinematics-decoding models from electromyographic (EMG) signals to achieve more natural control interfaces for rehabilitation therapies. However, the development of a dexterous EMG-based control interface including multiple degrees of freedom (DOFs) of the upper limb still remains a challenge. Another persistent issue in...
Motor cortical local field potentials (LFPs) have been successfully used to decode both kinematics and kinetics of arm movement. For future clinically viable prostheses, however, brain activity decoders will have to generalize well under a wide spectrum of behavioral conditions. This property has not yet been demonstrated clearly. Here, we provide evidence for the first time, that an LFP-based electromyogram...
Stroke remains a leading cause of disability, limiting independent ambulation in survivors, and consequently affecting quality of life (QOL). Recent technological advances in neural interfacing with robotic rehabilitation devices are promising in the context of gait rehabilitation. Here, the X1, NASA's powered robotic lower limb exoskeleton, is introduced as a potential diagnostic, assistive, and...
Brain-machine interfaces (BMIs) have the potential to restore movement to people with paralyzed limbs by controlling functional electrical stimulation (FES) of paralyzed muscles. This concept recently was put into practice in monkeys using spikes to control electrical stimulation of a set of wrist muscles [1–2]. However, the viability of spike-based BMIs is limited by the inability to record spikes...
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