Intelligent bell facial paralysis assessment: a facial recognition model using improved SSD network.

With the continuous progress of technology, the subject of life science plays an increasingly important role, among which the application of artificial intelligence in the medical field has attracted more and more attention. Bell facial palsy, a neurological ailment characterized by facial muscle weakness or paralysis, exerts a profound impact on patients' facial expressions and masticatory abilities, thereby inflicting considerable distress upon their overall quality of life and mental well-being. In this study, we designed a facial attribute recognition model specifically for individuals with Bell's facial palsy. The model utilizes an enhanced SSD network and scientific computing to perform a graded assessment of the patients' condition. By replacing the VGG network with a more efficient backbone, we improved the model's accuracy and significantly reduced its computational burden. The results show that the improved SSD network has an average precision of 87.9% in the classification of light, middle and severe facial palsy, and effectively performs the classification of patients with facial palsy, where scientific calculations also increase the precision of the classification. This is also one of the most significant contributions of this article, which provides intelligent means and objective data for future research on intelligent diagnosis and treatment as well as progressive rehabilitation.

Everyday amnesia: Residual memory for high confidence misses and implications for decision models of recognition.

Despite studying a list of items only minutes earlier, when reencountered in a recognition memory test, undergraduate participants often say with total confidence that they have not studied some of the items before. Such high confidence miss (HCM) responses have been taken as evidence of rapid and complete forgetting and of everyday amnesia (Roediger & Tekin, 2020). We investigated (a) if memory for HCMs is completely lost or whether a residual memory effect exists and (b) whether dominant decision models predict the effect. Participants studied faces (Experiments 1a, 2, and 3) or words (Experiment 1b), then completed a single-item recognition memory task, followed by either (a) a two-alternative forced-choice recognition task, in which the studied and nonstudied alternatives on each trial were matched for their previous old/new decision and confidence rating (Experiments 1 and 2) or (b) a second single-item recognition task in which the targets and foils were HCMs and high confidence correct rejections, respectively (Experiment 3). In each experiment, participants reliably distinguished HCMs from high-confidence correct rejections. The unequal variance signal detection and dual-process signal detection models were fit to the single-item recognition data, and the parameter estimates were used to predict the memory effect for HCMs. The dual-process signal detection model predicted the residual memory effect (as did another popular model, the mixture signal detection theory model). However, the unequal variance signal detection model incorrectly predicted a negative, or no, effect, invalidating this model. The residual memory effect for HCMs demonstrates that everyday amnesia is not associated with complete memory loss and distinguishes between decision models. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Pain assessment tools in adults with communication disorders: systematic review and meta-analysis.

BACKGROUND: Verbal communication is the "gold standard" for assessing pain. Consequently, individuals with communication disorders are particularly vulnerable to incomplete pain management. This review aims at identifying the current pain assessment instruments for adult patients with communication disorders. METHODS: A systematic review with meta-analysis was conducted on PubMed, PEDRO, EBSCOhost, VHL and Cochrane databases from 2011 to 2023 using MeSH terms "pain assessment, "nonverbal communication" and "communication disorders" in conjunction with additional inclusion criteria: studies limited to humans, interventions involving adult patients, and empirical investigations. RESULTS: Fifty articles were included in the review. Seven studies report sufficient data to perform the meta-analysis. Observational scales are the most common instruments to evaluate pain in individuals with communication disorders followed by physiological measures and facial recognition systems. While most pain assessments rely on observational scales, current evidence does not strongly endorse one scale over others for clinical practice. However, specific observational scales appear to be particularly suitable for identifying pain during certain potentially painful procedures, such as suctioning and mobilization, in these populations. Additionally, specific observational scales appear to be well-suited for certain conditions, such as mechanically ventilated patients. CONCLUSIONS: While observational scales dominate pain assessment, no universal tool exists for adults with communication disorders. Specific scales exhibit promise for distinct populations, yet the diverse landscape of tools hampers a one-size-fits-all solution. Crucially, further high-quality research, offering quantitative data like reliability findings, is needed to identify optimal tools for various contexts. Clinicians should be informed to select tools judiciously, recognizing the nuanced appropriateness of each in diverse clinical situations. TRIAL REGISTRATION: This systematic review is registered in PROSPERO (International prospective register of systematic reviews) with the ID: CRD42022323655 .

An assessment of dynamic facial emotion recognition and theory of mind in children with ADHD: An eye-tracking study.

Deficits in social cognition in attention deficit hyperactivity disorder (ADHD) have been associated with difficulties in functioning. Since recognizing emotional facial expressions is essential for developing the perceptual components of the theory of mind (ToM), it is important to assess this relationship in children with ADHD. This study therefore compared the recognition of emotional stimuli and gaze patterns between children with ADHD and healthy children using eye-tracking with dynamic facial images. It also examined the relationship between facial emotion recognition accuracy, gaze patterns, ToM scores, and ADHD symptoms. Children with ADHD aged 8-13 (n = 47) and a control group (n = 38) completed a facial emotion recognition test, ToM tests, and the Conners' Parent Rating Scale. Participants' gaze patterns in response to dynamic facial emotion expressions were recorded using eye-tracking technology. Children with ADHD exhibited significantly lower accuracy in the recognition of the facial expressions of disgust and anger. The percentage fixation in the eye region was also significantly lower for happy, angry, sad, disgusted, and neutral emotions in the children with ADHD compared to the control group. No relationship was determined between the percentage of fixations on facial areas of interests and ADHD symptoms or ToM tests. This study provides evidence that children with ADHD experience deficits in visual attention to emotional cues. In addition, it suggests that facial emotion recognition deficits in children with ADHD represent a separate domain of social cognition that develops independently of ToM skills and core symptoms. Understanding and treating the social difficulties of individuals with ADHD may help improve their social functioning.

Social class perception is driven by stereotype-related facial features.

Social class is a powerful hierarchy that determines many privileges and disadvantages. People form impressions of others' social class (like other important social attributes) from facial appearance, and these impressions correlate with stereotype judgments. However, what drives these related subjective judgments remains unknown. That is, what makes someone look like they are of higher or lower social class standing (e.g., rich or poor), and how does this relate to harmful or advantageous stereotypes? We addressed these questions using a perception-based data-driven method to model the specific three-dimensional facial features that drive social class judgments and compared them to those of stereotype-related judgments (competence, warmth, dominance, and trustworthiness), based on White Western culture participants and face stimuli. Using a complementary data-reduction analysis and machine learning approach, we show that social class judgments are driven by a unique constellation of facial features that reflect multiple embedded stereotypes: poor-looking (vs. rich-looking) faces are wider, shorter, and flatter with downturned mouths and darker, cooler complexions, mirroring features of incompetent, cold, and untrustworthy-looking (vs. competent, warm, and trustworthy-looking) faces. Our results reveal the specific facial features that underlie the connection between impressions of social class and stereotype-related social traits, with implications for central social perception theories, including understanding the causal links between stereotype knowledge and social class judgments. We anticipate that our results will inform future interventions designed to interrupt biased perception and social inequalities. (PsycInfo Database Record (c) 2024 APA, all rights reserved).