Ellipsis Health, Inc.

Amir Hossein Harati Nejad Torbati

Tomasz Rutowski

Michael Aratow

Mainul Islam

David Lin

Robert Derward Rogers

Elizabeth E Shriberg

Yang Lu

Farshid Haque

Piotr Chlebek

Melissa McCool

The present disclosure provides acoustic and natural language processing (NLP) models for predicting whether a subject has a behavioral or mental health state of interest based at least in part on input speech from said subject.

Acoustic and natural language processing models for speech-based screening and monitoring of behavioral health conditions

The present disclosure provides systems and methods for assessing a mental state of a subject in a single session or over multiple different sessions, using for example an automated module to present and/or formulate at least one query based in part on one or more target mental states to be assessed. The query may be configured to elicit at least one response from the subject. The query may be transmitted in an audio, visual, and/or textual format to the subject to elicit the response. Data comprising the response from the subject can be received. The data can be processed using one or more individual, joint, or fused models. One or more assessments of the mental state associated with the subject can be generated for the single session, for each of the multiple different sessions, or upon completion of one or more sessions of the multiple different sessions.

Systems and methods for mental health assessment

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Toronto, Canada

Amir Hossein Harati Nejad Torbati