Remote AI screening for early speech and swallowing changes in ALS
Official title: AI-assisted multimodal digital remote screening for bulbar ALS to support timely referral to SLP care
Funded at Sunnybrook Research Institute · NIH-11120113 · Data updated 2026-11-12
An AI-based remote audio and video tool for people with ALS to help spot early speech and swallowing changes so they can get speech-language care sooner.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Sunnybrook Research Institute NIH-funded |
| Lab location | 1 site (Toronto, Canada) |
| Project start | July 20, 2018 |
| Project end | July 31, 2030 |
| Funding year | 2025 |
| Award (this year) | $528,090 |
| NIH project number | 2R01DC017291-06 |
| Project ID | NIH-11120113 on NIH RePORTER |
Who could benefit from this research
✓Could help
People diagnosed with ALS, especially those early in their disease course or without obvious bulbar symptoms, would be the ideal candidates.
✕Less likely to help
People without ALS or those with already advanced bulbar impairment are unlikely to gain benefit from early remote screening.
What this research studies
This project is building an AI-based remote tool that uses short audio and video recordings you can do at home to look for early speech and swallowing (bulbar) changes common in ALS. Researchers will collect repeated recordings over time to see how practice affects speech measures and to train algorithms to detect subtle changes. They will develop and internally test clinical predictive algorithms that combine audio and video features to screen for early bulbar dysfunction and to predict future decline on established bulbar measures. The goal is an automatic remote system that flags people who need faster referral to speech-language pathology so problems are treated earlier.
Why it matters
Potential benefit: If successful, the tool could help detect bulbar problems earlier and speed up referral to speech-language pathology for timely care and management.
How similar studies have gone: Speech-analysis approaches have shown promise in ALS, but combining multimodal audio and video for remote bulbar screening and prediction is relatively new and still under development.
Where this research is happening
-
Sunnybrook Research Institute
Toronto, Canada Active
Researchers
- Principal investigator: Yunusova, Yana — Sunnybrook Research Institute
- Study coordinator: Yunusova, Yana
Related research
Other NIH-funded projects on the same topics.
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AI-powered remote screening to detect bulbar ALS and speed up speech therapy referrals
A test of smart digital tools that listen and watch how people with ALS speak to flag early bulbar symptoms and help doctors refer them to speech-language pathology sooner.
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Exploring how brain stimulation affects memory in Alzheimer's disease models
This study is looking at how a gentle brain stimulation technique called tACS might help improve memory and brain activity in people with Alzheimer's disease, and it's designed to be safe and comfortable for long-term use.
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Creating a new tool to assess swallowing and speaking difficulties in ALS patients
This study is working on a new tool to help doctors better understand and measure problems with speaking and swallowing in people with ALS, so they can improve care and treatment options for patients.
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.