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Tag: Facial Expressions

  • New System Improves Machine Recognition of Facial Expressions

    New System Improves Machine Recognition of Facial Expressions

    Edith Cowan University (ECU) researchers are developing a new method to help machines better recognize human facial expressions and become more emotionally aware.
    Image Credits: Pixabay

    Edith Cowan University (ECU) researchers are developing a new method to help machines better recognize human facial expressions and become more emotionally aware.

    “As digital systems like virtual assistants and wellness apps interact more with people, it’s crucial they understand human emotions,” said ECU Ph.D. student Sharjeel Tahir.

    A More Human Approach to Emotion Recognition

    Rather than using single images to train systems to detect emotions, the team—led by ECU senior lecturer and AI expert Dr. Syed Afaq Shah—adopted a more human-like method: presenting sets of related facial expressions to give machines a wider emotional context.

    “Just as we don’t judge someone’s emotions from a single glance, our approach analyzes multiple expressions to make more accurate predictions,” Tahir said. “It helps machines better understand emotions, even when faces appear at different angles or in varied lighting.”

    Though not applied to physical robots, the research could shape the development of emotionally aware systems in areas like mental health support, customer service, and interactive learning.

    Building Machines That Truly Understand Faces

    “We’re building a foundation for machines that truly understand faces—not just see them,” Tahir added.

    Co-author and Ph.D. student Nima Mirnateghi noted that their method provides rich visual context, boosting emotion recognition accuracy while remaining computationally efficient. The findings were published in the 2024 International Conference on Digital Image Computing: Techniques and Applications (DICTA).

    “By training the model with diverse features in an organized set, we found it could recognize emotional patterns much more effectively,” he said.

    Guided by Dr. Shah, Tahir is now focusing on developing artificial empathy in AI agents, enabling them to respond appropriately to human emotions.

    Meeting the Rising Need for Emotional Support with Intelligent Machines

    “There’s a growing demand for emotional support, and emotionally intelligent machines or robots could help meet that need,” Tahir noted.

    Mirnateghi added that the research not only advanced AI’s ability to recognize emotions but also encouraged a deeper investigation into how AI models make decisions.

    “Our research group is now concentrating on explainable AI in language models, aiming to reveal the complex processes behind how artificial agents recognize and interpret patterns,” he said.

    “By increasing transparency, we hope to design AI systems that are easier for humans to understand—narrowing the divide between sophisticated algorithms and human insight. One key question we’re exploring is: what truly makes a machine emotionally intelligent?”

    Read the original article on: Techxplore

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  • Facial Expressions Could Help Diagnose Severe Melancholia Depression

    Facial Expressions Could Help Diagnose Severe Melancholia Depression

    A promising path to earlier treatment may be emerging for individuals experiencing the most severe type of depression.
    Credit: Pixabay

    A promising path to earlier treatment may be emerging for individuals experiencing the most severe type of depression.

    In a recent study, researchers observed that individuals with melancholia, a severe form of depression, displayed noticeably different reactions while watching emotionally charged films compared to those with less severe forms of depression.

    This finding could enable earlier diagnosis of melancholia, ensuring patients receive appropriate treatment quickly and potentially avoiding the need for more invasive interventions caused by delayed care.

    Physical Symptoms of Depression

    “For as long as depression has been recognized, dating back to ancient Greek times, it’s been noted that some individuals with depression exhibit very physical symptoms,” explained neuropsychiatrist Philip Mosley from Australia’s QIMR Berghofer Medical Research Institute in an interview with ScienceAlert.

    “They stop eating, struggle to sleep, move as though they’re wading through concrete, and their thinking slows dramatically. These individuals are often very unwell,” he said.

    Known as melancholia, this subtype of depression frequently resists psychological treatments. Mosley described the research as an effort to develop tools that enable precise diagnosis of depression types, allowing for faster and more personalized treatment strategies.

    Dr Philip Mosley. (QIMR Berghofer)

    Challenges in Diagnosing and Treating Melancholia in Depression

    Melancholia impacts approximately 5 to 10 percent of individuals with depression and is often difficult to diagnose. Delays in diagnosis increase the likelihood that patients may require more intensive treatments, such as electroconvulsive therapy or transcranial magnetic stimulation. While these treatments are highly effective, they can also seem daunting and invasive to many patients.

    Mosley and his team aim to enable early diagnosis, where medications can be highly effective.

    At QIMR Berghofer, researchers used emotional videos to study responses in 70 depression patients—30 with melancholic and 40 with non-melancholic depression. To explore whether melancholia’s flat affect could be detected, participants watched two clips: a humorous segment from Ricky Gervais’ Animals and the emotionally stirring short film The Butterfly Circus.

    The difference in responses observed between melancholic and non-melancholic depression. (Mosley et al., Mol. Psychiatry, 2024)

    Monitoring Facial Expressions and Brain Activity in Depression Research

    During the video sessions, researchers monitored patients’ facial expressions and brain activity. Facial movements were tracked using a camera to capture even the slightest muscle twitches during the Gervais clip, while brain activity was recorded using MRI scans as patients watched The Butterfly Circus.

    The contrast was clear: non-melancholic patients showed facial expressions and occasional giggles during the Gervais video, while melancholic patients remained motionless, like “statues,” with no smiles or chuckles, Mosley noted.

    MRI scans revealed similar differences. Non-melancholic patients’ brains showed activity in the cerebellum, linked to emotional responses, whereas melancholic patients’ emotional brain regions operated independently, disconnected from other areas involved in processing emotions.

    Some of the muscle movements monitored in the study. (Mosley et al., Mol. Psychiatry, 2024)

    The clear difference in responses could provide a quick, non-invasive diagnostic tool for identifying melancholia, reducing delays and allowing for faster, tailored treatment.

    This research also has long-term potential. By understanding the underlying causes of depression and why it can become life-threatening, scientists can better customize treatments for individuals.

    “Our study shows that melancholia, recognized as a distinct form of depression since ancient times, differs in its brain and physical manifestations,” Mosley said. “This could lead us to rethink treatment approaches for quicker recovery.”

    Read the original article on: Science Alert

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