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Machine learning algorithms applied to a prediction of personal overall thermal comfort using skin temperatures and occupants' heating behavior.

Applied ergonomics
Thermal comfort modeling has been of interest in built environment research for decades. Mostly the modeling approaches focused on an average response of a large group of building occupants. Recently, the focus has been shifted towards personal comfo...

Measuring the impact of age, gender and dementia on communication-robot interventions in residential care homes.

Geriatrics & gerontology international
AIM: The primary aim of this study was to examine the impact of age, gender and the stage of dementia on the results of an assistive technology intervention that make use of communication robots (com-robots). The intervention was designed to improve ...

A Framework for Applying Natural Language Processing in Digital Health Interventions.

Journal of medical Internet research
BACKGROUND: Digital health interventions (DHIs) are poised to reduce target symptoms in a scalable, affordable, and empirically supported way. DHIs that involve coaching or clinical support often collect text data from 2 sources: (1) open corresponde...

fNIRS-GANs: data augmentation using generative adversarial networks for classifying motor tasks from functional near-infrared spectroscopy.

Journal of neural engineering
OBJECTIVE: Functional near-infrared spectroscopy (fNIRS) is expected to be applied to brain-computer interface (BCI) technologies. Since lengthy fNIRS measurements are uncomfortable for participants, it is difficult to obtain enough data to train cla...

Virtual reality operating room with AI guidance: design and validation of a fire scenario.

Surgical endoscopy
BACKGROUND: Operating room (OR) fires are uncommon but disastrous events. Inappropriate handling of OR fires can result in injuries, even death. Aiming to simulate OR fire emergencies and effectively train clinicians to react appropriately, we have d...

Automatic Recognition of Laryngoscopic Images Using a Deep-Learning Technique.

The Laryngoscope
OBJECTIVES/HYPOTHESIS: To develop a deep-learning-based computer-aided diagnosis system for distinguishing laryngeal neoplasms (benign, precancerous lesions, and cancer) and improve the clinician-based accuracy of diagnostic assessments of laryngosco...

Numerosity discrimination in deep neural networks: Initial competence, developmental refinement and experience statistics.

Developmental science
Both humans and non-human animals exhibit sensitivity to the approximate number of items in a visual array, as indexed by their performance in numerosity discrimination tasks, and even neonates can detect changes in numerosity. These findings are oft...

Initial classification of low back and leg pain based on objective functional testing: a pilot study of machine learning applied to diagnostics.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
OBJECTIVE: The five-repetition sit-to-stand (5R-STS) test was designed to capture objective functional impairment and thus provided an adjunctive dimension in patient assessment. The clinical interpretability and confounders of the 5R-STS remain poor...

The averaged inter-brain coherence between the audience and a violinist predicts the popularity of violin performance.

NeuroImage
Why is some music well-received whereas other music is not? Previous research has indicated the close temporal dependencies of neural activity among performers and among audiences. However, it is unknown whether similar neural contingencies exist bet...

A comparison of fMRI and behavioral models for predicting inter-temporal choices.

NeuroImage
In an inter-temporal choice (IteCh) task, subjects are offered a smaller amount of money immediately or a larger amount at a later time point. Here, we are using trial-by-trial fMRI data from 363 recording sessions and machine learning in an attempt ...