[ Ссылка ]
Our study uses advanced computation technology and speech, audio and video data. You can participate if your voice is normal or affected by ALS.
You will have access to your own recordings and feedback of analysis of your speech. Your data is protected and stored unidentifiable (anonymous) following the FDA IRB approved privacy protocol. Your data is worked on by
MIT, Mass general, IBM, UT Austin, Google Euphonia, CMU etc.
We are looking for Individuals Diagnosed or Probable with Amyotrophic Lateral Sclerosis (ALS) and Healthy Participants between 18 and 100 years of age.
Our study is motivated by the need for early detection and improved prognostic accuracy of ALS using advanced computational technology and speech data (audio, video). By participating in this study, you will contribute to a growing large ALS data set and further advance current knowledge relating to the decline in speech production due to ALS while also improving the performance of this technology.
The approach will be to perform analysis of online audio/video recordings: The study activity involves the use of web-based software that collects speech audio and video data and then uses AI and machine learning algorithms to analyze facial and speech metrics. Data collection can be conducted anywhere you feel comfortable (e.g., your home). Each session will last approximately 20 minutes. Participants are welcome to do multiple sessions if interested.
Protocol Number: 2020-06-PI42 | Sponsor: Peter Cohen Foundation
Principal Investigators: Aria Anvar, MD, MBA, Indu Navar Bingham, MS
