ArticleIEEE transactions on bio-medical engineering2021
Functional Brain Imaging Reliably Predicts Bimanual Motor Skill Performance in a Standardized Surgical Task.
Article in IEEE transactions on bio-medical engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.
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Who cites it
15 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Using neuroimaging to assess brain activity and areas associated with surgical skills: a systematic review.Surgical endoscopy · 2024Pooled it
- Technical skill assessment in minimally invasive surgery using artificial intelligence: a systematic review.Surgical endoscopy · 2023Pooled it
- Evaluating and Classifying Gentleness in VR-Based Surgical Simulation: A VR + fNIRS Study.Sensors (Basel, Switzerland) · 2026Article
- Cross-Disease Classification of Depression, Bipolar Disorder, and Schizophrenia Using Multiscale Spatiotemporal Network Fusion Features From fNIRS.Depression and anxiety · 2026Article
- Artificial intelligence in clinical practice: a cross-sectional survey of paediatric surgery residents' perspectives.BMJ health & care informatics · 2025Article
- Effects of different AI-driven Chatbot feedback on learning outcomes and brain activity.NPJ science of learning · 2025Article
- Evaluation of the learning state of online video courses based on functional near infrared spectroscopy.Biomedical optics express · 2024Article
- Assessment of Surgical Tasks Using Neuroimaging Dataset (ASTaUND).Scientific data · 2023Article
- Brain-behavior analysis of transcranial direct current stimulation effects on a complex surgical motor task.Frontiers in neuroergonomics · 2023Article
- Optical neuroimaging and neurostimulation in surgical training and assessment: A state-of-the-art review.Frontiers in neuroergonomics · 2023Review
- Error-related brain state analysis using electroencephalography in conjunction with functional near-infrared spectroscopy during a complex surgical motor task.Brain informatics · 2022Article
- Deep learning in fNIRS: a review.Neurophotonics · 2022Review
- Deep learning-based motion artifact removal in functional near-infrared spectroscopy.Neurophotonics · 2022Article
- Directed information flow during laparoscopic surgical skill acquisition dissociated skill level and medical simulation technology.NPJ science of learning · 2022Article
- Priming Engineers to Think About Sustainability: Cognitive and Neuro-Cognitive Evidence to Support the Adoption of Green Stormwater Design.Frontiers in neuroscience · 2022Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Currently, there is a dearth of objective metrics for assessing bi-manual motor skills, which are critical for high-stakes professions such as surgery. Recently, functional near-infrared spectroscopy (fNIRS) has been shown to be effective at classifying motor task types, which can be potentially used for assessing motor performance level. In this work, we use fNIRS data for predicting the performance scores in a standardized bi-manual motor task used in surgical certification and propose a deep-learning framework 'Brain-NET' to extract features from the fNIRS data. Our results demonstrate that the Brain-NET is able to predict bi-manual surgical motor skills based on neuroimaging data accurately ( R
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