Mood
Mood screening by GIA®, powered by digitalhumanOS™, uses Voice AI, Computer Vision, and Speech Biomarkers to detect mood through a single patient conversation. Screening performance: Clinically validated vocal biomarker screening. Screening takes under 5 minutes with results in 60 seconds.
Fluctuations in mood profoundly impact healing, influencing patient engagement and overall well-being.
Continuous mood assessment allows for proactive intervention in post-acute care. By monitoring mood, we can tailor care plans and improve patient outcomes.
Key Facts
- Screening Time
- Under 5 minutes
- Results
- 60 seconds
- Modalities
- Voice + Vision + Speech
- Registration
- 510(k)
- Status
- Live
About Mood screening.
How does the system assess patient mood?
The system analyzes vocal patterns, speech characteristics, and facial expressions to assess mood.
What are the benefits of continuous mood monitoring?
Continuous monitoring allows for early detection of mood changes, enabling timely interventions and preventing crises.
How does this impact resource allocation?
By identifying patients requiring additional support, staff can proactively allocate resources and improve overall care efficiency.
The science behind Mood screening.
Research demonstrates that a single conversational question contains sufficient vocal data to estimate anxiety levels, sleep quality, and mood states through computational voice analysis.
"How are you?" Estimation of Anxiety, Sleep Quality, and Mood Using Computational Voice Analysis (2020-07)A systematic scoping review from the University of Málaga, published in Biology (MDPI), confirms that voice production consistently engages the autonomic nervous system — with vocal markers providing measurable signals of stress, cognitive load, emotional state, and subclinical clinical conditions detectable before symptoms appear.
Mapping the Neurophysiological Link Between Voice and Autonomic Function: A Scoping Review — Biology, MDPI (2025-10-10) · University of Málaga, Biomedical Research Institute of Málaga (IBIMA Platform BIONAND)DOI: 10.3390/biology14101382 →