Results 61 to 70 of about 1,837,819 (299)
FEBS Open Bio, EarlyView.This pilot study investigates the potential of Generative AI to provide formative feedback to students. ChatGPT was prompted to provide feedback on Year 1 Bioscience essays, which were evaluated against established good feedback practices. GenAI‐authored feedback had useful elements, but was limited in scope. GenAI may have potential to provide instant,
Annabel Court +3 more
wiley +1 more source
Emotion Recognition by Physiological Signals
Electronic Imaging, 2016 Recently, User’s effective state automatic recognition has become a popular research area. It has many applications ranging from health, education, and personalization. In this paper, emotional state arousal and valence induced by watching video clips are identified by physiological and electroencephalogram (EEG) signals by .
Naeem Ramzan +4 more
openaire +3 more sources
New Directions for Adult and Continuing Education, EarlyView.ABSTRACT Advancing artificial intelligence (AI) has transformed learning and work, yet higher education and professional development programs have not systematically equipped learners for AI‐prevalent environments. This lack of preparation creates uncertainty regarding control, responsibility, trust, and accountability.
Moon‐Heum Cho, Jerusalem Merkebu
wiley +1 more source
3477 Impaired emotion recognition accuracy after right-hemisphere stroke
Journal of Clinical and Translational Science, 2019 OBJECTIVES/SPECIFIC AIMS: Every year, approximately 800,000 Americans suffer a stroke. Supportive social environments are recognized as an important factor contributing to successful stroke recovery, yet, stroke lesions can affect brain areas important ...
Katherine OConnell +2 more
doaj +1 more source
Emotion recognition based on group phase locking value using convolutional neural network
Scientific Reports, 2023 Electroencephalography (EEG)-based emotion recognition is an important technology for human–computer interactions. In the field of neuromarketing, emotion recognition based on group EEG can be used to analyze the emotional states of multiple users ...
Gaochao Cui, Xueyuan Li, Hideaki Touyama
doaj +1 more source
Multimodal Emotion Recognition
, 2010 Recent advances in human-computer interaction technology go beyond the successful transfer of data between human and machine by seeking to improve the naturalness and friendliness of user interactions. An important augmentation, and potential source of feedback, comes from recognizing the user‘s expressed emotion or affect.
Haq, S, Jackson, PJB
openaire +5 more sources
Relationship Between Neurologic Symptoms and Signs and FMR1 Genotype in Premutation Carriers
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background and Objectives Fragile X‐associated Tremor/Ataxia Syndrome (FXTAS) is the most severe late‐onset condition caused by a premutation in the FMR1 gene, characterized by expanded CGG triplet repeats of 55–200. Clinical presentations of FXTAS, including gait ataxia, kinetic tremor, cognitive decline, and rare Parkinsonism, are linked to ...
Flora Tassone +8 more
wiley +1 more source
A Hybrid Speech Emotion Recognition System Based on Spectral and Prosodic Features [PDF]
, 2010 In this paper, we present a hybrid speech emotion recognition system exploiting both spectral and prosodic features in speech. For capturing the emotional information in the spectral domain, we propose a new spectral feature extraction method by applying
Yanqing SUN +11 more
core +1 more source
Revista CEFAC, 2019 Purpose: to investigate the use of softwares for emotion recognition in children and teenagers with Autism Spectrum Disorders (ASD). Methods: an integrative review of the literature with scientific papers published from 2012 to 2017 indexed in Periódico
Antonio Marcos Oliveira de Lima +3 more
doaj +1 more source
Enhancing Mouth-Based Emotion Recognition Using Transfer Learning
Sensors, 2020 This work concludes the first study on mouth-based emotion recognition while adopting a transfer learning approach. Transfer learning results are paramount for mouth-based emotion emotion recognition, because few datasets are available, and most of them ...
Valentina Franzoni +3 more
doaj +1 more source