In recent years, there has been a significant increase in research activity on electroencephalography (EEG)-based motor imagery brain-computer interfaces (MI-BCI) in the field of deep learning. However, despite achieving high accuracy, the size of mo...
Studying locomotor activity in animal models is crucial for understanding physiological, behavioral, and pathological processes. This study aimed to develop an artificial intelligence-based tracking system called Goblotrop, designed to localize roden...
International journal of neural systems
Oct 18, 2025
Decoding electroencephalographic (EEG) signals is of key importance in the development of brain-computer interface (BCI) systems. However, high inter-subject variability in EEG signals requires user-specific calibration, which can be time-consuming a...
Using machine learning, we developed models that rigorously detect and classify larval zebrafish spontaneous and stimulus-evoked behaviors in various well plate formats. Zebrafish are an ideal model system for investigating the neural substrates unde...
Digital measures derived from wearable sensors are a promising approach for assessing motor impairment in clinical trials. Submovements, which are velocity curves extracted from time series data, have been successful in characterizing impaired moveme...
BACKGROUND: The majority of individuals with chronic stroke have residual upper extremity (UE) disability which they cite as their greatest barrier to recovery. Using orthoses, robotic devices, and functional electrical stimulation (FES) represent re...
BACKGROUND: Stroke-induced upper limb dysfunction requires functional assessment and rehabilitation. The intelligent rehabilitation assessment and virtual reality training system for upper limb motor function in stroke can accurately and objectively ...
Buprenorphine is an opioid approved for medication-assisted treatment of opioid use disorder. Used off-label, buprenorphine has been reported to contribute to the clinical management of anxiety. Although human anxiety is a highly prevalent disorder, ...
BACKGROUND: Body weight unloaded treadmill training has shown limited efficacy in further improving functional capacity after subacute rehabilitation of ischemic stroke patients. Dynamic robot assisted bodyweight unloading is a novel technology that ...
BACKGROUND: In the pursuit of finer Brain-Computer Interface commands, research focus has shifted towards classifying EEG signals for multiple tasks. While single-joint multitasking motor imagery provides support, distinguishing between EEG signals f...
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