Neuroscience
This is the supplementary document for the review paper titled “Comprehensive and Data-Driven Literature Review of Supernumerary Robotic Limbs,” which presents a comprehensive and data-driven review that offers a quantitative analysis of Supernumerary Robotic Limbs (SRLs), covering application areas, structural designs, control strategies, embodiments, and their interconnections.
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Finger Scanning Experiments: Participants conducted experiments while seated and wearing an eye mask to eliminate visual information. They were instructed to horizontally scan the surface back-and-forth eight times with one of their fingers to assess surface roughness. The finger's motion was optically captured at a frame rate of 60 fps. Scanning speed was determined by measuring finger positions at each frame and dividing them by the frame length. Image analysis was performed using OpenCV, where the finger outline was extracted from the video.
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Resilience is an important indicator of our defence mechanism against mental illness. Its assessment is conventionally done using psychological questionnaires and has also been recently investigated using neuroimaging modalities. These modalities provide objective and physiological-based assessment of resilience for prognosis and training purposes such as in the neurofeedback and behavioural therapies. This study investigates the use of electroencephalogram (EEG) to assess mental resilience in 2-Class, 3-Class and 4-Class models during resting and task conditions.
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This data set consists of EEG data from 9 subjects. The cue-based BCI paradigm consisted of four di erent motor imagery tasks, namely the imag ination of movement of the left hand (class 1), right hand (class 2), both feet (class 3), and tongue (class 4). Two sessions on di erent days were recorded for each subject. Each session is comprised of 6 runs separated by short breaks. One run consists of 48 trials (12 for each of the four possible classes), yielding a total of 288 trials per session.
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Faces and bodies provide critical cues for social interaction and communication. Their structural encoding depends on configural processing, as suggested by the detrimental effect of stimulus inversion for both faces (i.e., face inversion effect - FIE) and bodies (body inversion effect - BIE). An occipito-temporal negative event-related potential (ERP) component peaking around 170 ms after stimulus onset (N170) is consistently elicited by human faces and bodies and it is affected by the inversion of these stimuli.
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In today’s context, it is essential to develop technologies to help older patients with neurocognitive disorders communicate better with their caregivers. Research in Brain Computer Interface, especially in thought-to-text translation has been carried out in several languages like Chinese, Japanese and others. However, research of this nature has been hindered in India due to scarcity of datasets in vernacular languages, including Malayalam. Malayalam is a South Indian language, spoken primarily in the state of Kerala by bout 34 million people.
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This dataset comprises data from six experimental participants, each undergoing nine walking trials. Each participant engaged in three trials of low-speed walking, three trials of medium-speed walking, and three trials of high-speed walking. The dataset includes multi-channel electromyography (EMG) data and center of pressure/ground reaction force (COP/GRF) data. Specifically, EMG data is utilized to extract muscle coordination activation time coefficients during human walking, and a deep learning model is established based on these coefficients to predict COP/GRF parameters.
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Calcium imaging visualizes specific activity of neurons through active sensors, which makes it easy to study the neuronal behavior of animals' learning processes and cognition and helps to promote the use of animal models for neuroscience research. However, motion artifacts and background noise can affect calcium imaging, especially when watching awake animals while they are exposed to low-dose laser irradiation. This makes it impossible to fully understand how neural circuits work. As a result, imaging results are often warped and contain significant random noise.
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Autism spectrum disorder (ASD) is characterized by qualitative impairment in social reciprocity, and by repetitive, restricted, and stereotyped behaviors/interests. Previously considered rare, ASD is now recognized to occur in more than 1% of children. Despite continuing research advances, their pace and clinical impact have not kept up with the urgency to identify ways of determining the diagnosis at earlier ages, selecting optimal treatments, and predicting outcomes. For the most part this is due to the complexity and heterogeneity of ASD.
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We conducted a randomized controlled clinical trial to evaluate the efficacy of a brain-computer interface ( BCI ) -based visual and motor feedback motor imagery therapy system on cognitive, psychological and limb movement in hemiplegic stroke patients. We recruited more than 100 patients and randomly divided them into three groups : conventional treatment group, MI group and MI group based on brain-computer interface. The data set contains the evaluation data of these three groups of patients before and after treatment.
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341 Views