Imagine if your doctor could know how you're feeling every day without you having to remember or write it down. This tool listens to how you speak and uses AI to spot emotional patterns, acting like a digital bridge between clinic visits. It helps doctors catch warning signs early and adjust treatments based on real-time data rather than guesswork.
Psychiatrists lack tools to monitor patients between sessions, which occur every 3-4 months. This leads to a 60% dropout rate and a dangerous inability to predict relapses or suicide risks in real-time.
An AI-powered software for continuous emotion tracking via speech analysis and a scalable cloud architecture for remote patient monitoring.
If you are a telemedicine platform dealing with high patient dropout rates—this project developed an AI-powered software that could improve treatment adherence from 40% to 75%. It allows for continuous monitoring between sessions via smartphones.
If you are a clinic network dealing with psychiatrists who can only see patients every 3-4 months—this project developed a remote emotion tracker that provides objective insights into treatment effectiveness. It reduces the trial-and-error approach to prescribing medication.
If you are a wearable company dealing with a lack of objective mental health metrics—this project developed a system combining speech analysis and AI to detect emotions with high accuracy. This can be integrated into smartphone-based tools to reach over 95% of users.
Based on available project data, the specific pricing is not mentioned, but the project is currently creating a sustainable business model as a next step.
Yes, the project developed a scalable cloud-based architecture and a smartphone-based approach designed to make support accessible to over 95% of the target population.
Based on available project data, the project has developed a novel application of time-series AI analysis for speech patterns, though specific licensing terms are not listed.
It integrates as a patient-centric software that bridges communication gaps between sessions, providing clinicians with objective data to supplement traditional care.
The project period runs from 2023-11-01 to 2026-04-30, with current efforts focused on iterating the software with early adopters.
The project is led by a single French SME, CEPHALGO, which holds 100% of the industry ratio. This lean structure suggests a highly focused commercial drive, as the SME is directly responsible for both the technical AI development and the clinical validation with 6,000 patients.
Contact CEPHALGO in France for licensing and partnership inquiries.
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