The Future Of Mental Health Screening

Aiberry’s easy-to-use AI solution enhances the provider-patient relationship and screens for multiple mental health conditions with a 3–5-minute conversation.

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Aiberry makes it easy for

self-screening
in-clinic
telehealth

By allowing patients to actively participate in the conversation, providers can screen for mental health disorders while keeping the primary focus on the patient’s direct needs and concerns.

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How Mental Health Screening works

Our solution analyzes words, tone of voice, and facial expressions to screen for a range of mental health conditions. Findings are delivered via a user-friendly online dashboard for analysis where ongoing screening results and trends can be measured over time.

Aiberry helps healthcare providers conduct quick and objective mental health screenings during in-clinic visits by eliminating the need for paper-based forms and delivering real-time assessments of a patient’s mental state.

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Why Aiberry?

Performs one efficient screening for multiple mental health conditions.

Saves time during the mental health screening process.

Eliminates the need for paper-based screening forms.

Provides objective screening results to ensure accurate diagnosis.

Reduces inaccurate reporting of symptoms by patients.

Allows patients to talk freely and share important details with their healthcare provider.

Keeps both patients and providers informed about mental health scores and trends over time.

Offers a built-in telehealth platform to meet with patients virtually.

Start redefining mental health care.

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Start redefining mental health care.
Start redefining mental health care
Start redefining mental health care
Start redefining mental health care

Award Winning Technology

Aiberry is an award winning solution and platform that has been recognized for outstanding AI technology and innovation in mental and behavioral health.

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Patient safety, security and privacy

Patient privacy and protection is our obligation, and we are steadfast in ensuring that our solution meets the highest standards at every turn. Aiberry incorporates state of the art security and encryption measures to ensure complete patient privacy and data security.

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How It Works

People exhibit important clues about their mental health through the way they talk, the words they use, and the facial expressions they make – many of which are easily missed with the subjective, paper-based screening methods that are widely used today. 

With a guided 3–5-minute patient conversation, our solution analyzes words, tone of voice, and facial expressions to screen for a range of mental health conditions. Findings are delivered via a user-friendly online dashboard for analysis, enabling providers to make swift, sound decisions and develop a path to better mental health for their patients. Ongoing screening results and trends can be measured over time to ensure that patients are receiving the best care possible.

A World Of Benefits For Patients & Providers

  • Performs one efficient screening for multiple mental health conditions
  • Saves time during the mental health screening process
  • Eliminates the need for paper-based screening forms
  • Provides objective screening results to ensure accurate diagnosis
  • Reduces inaccurate reporting of symptoms by patients
  • Allows patients to talk freely and share important details with their healthcare provider
  • Keeps both patients and providers informed about mental health scores and trends over time
  • Offers a built-in telehealth platform to meet with patients virtually
Request a Demo
learn more

A Firm Commitment to Patient Safety, Security and Privacy

Patient privacy and protection is our obligation, and we are steadfast in ensuring that our solution meets the highest standards at every turn. Aiberry incorporates state of the art security and encryption measures to ensure complete patient privacy and data security.

Request a Demo

Simultaneous screening for multiple mental health conditions

People exhibit clues about their state of mind in the way they talk, the words they use, and the facial expressions they make. Observing these signals objectively — and weaving them together, can offer evidence-based insights about a person’s state-of-mind.

Aiberry uses securely captured video footage to quickly and accurately analyze patients’ words, voices, and facial expressions to screen for multiple mental health conditions simultaneously.

AI is leveraged to extract and analyze specific data points such as lip and eyebrow movements, twitching of muscles, pitch, frequency, pause, words used, sentence construct, to identify patterns characterizing a particular mental health disorder.

Simultaneous screening for multiple
mental health conditions

People exhibit clues about their state of mind in the way they talk, the words they use, and the facial expressions they make. Observing these signals objectively — and weaving them together, can offer evidence-based insights about a person’s state-of-mind.

Aiberry uses securely captured video footage to quickly and accurately analyze patients’ words, voices, and facial expressions to screen for multiple mental health conditions simultaneously.

AI is leveraged to extract and analyze specific data points such as lip and eyebrow movements, twitching of muscles, pitch, frequency, pause, words used, sentence construct, to identify patterns characterizing a particular mental health disorder.

So how does it work?

We leverage advanced techniques such as artificial intelligence, machine learning, and natural language processing to examine audiovisual signals. These signals are analyzed in isolation and as an aggregated pool of data, thus providing accurate, objective, and relevant insights, augmenting a clinician’s capacity and accelerating time-to-insight.

Our technology is supported by multiple patents, including a pending patent application supporting our unique multi-modal approach.

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Step 1
Video Intake​
Intake video of conversation between patient and provider
Step 1
Step 2
Feature Extraction​
Separate the video into three modalities - frames, audio, transcript and extract features ​
Step 2
Step 3
Feature Analysis​
Analyze features for each modality using neural networks and proprietary algorithms​
Step 3
Step 4
Modality Fusion​
Use advanced fusion techniques to predict level of mental illness (score, severity)
Step 4
Step 5
Insights​
Provide insights about overall mental state​
Step 5

Engaging with the future of mental health made easy

Aiberry’s end-to-end architecture and processing pipeline are hosted in the AWS cloud. The entire process from video intake to insight is automated and the results are available immediately.

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Over a decade of research
bundled into one innovative solution only for you

Aiberry’s innovative technology is the result of over a decade of research performed by our Chief Scientist Dr. Newton Howard, who is one of today’s foremost experts in computational and cognitive neurosciences and his collaborators.This in-depth research in the field of Sentiment Analysis, Intention Awareness and Multi-modal Dialogue Systems positions us to create novel and impactful behavioral health products and platforms.

Approach Towards a Natural Language Analysis for Diagnosing Mood Disorders and Comorbid Conditions
(Dr. Newton Howard (2013))

Towards a Differential Diagnostic of PTSD Using Cognitive Computing Methods
(Newton Howard, Louis Jehel, Romain Arnal (2014))

Fusing audio, visual, and textual clues for sentiment analysis from multimodal content
(Soujanya Poria, Erik Cambria, Newton Howard, Guang-Bin Huang, Amir Hussain (2015))

Emotion Recognition in Conversation: Research Challenges, Datasets, and Recent Advances
(Soujanya Poria, Navonil Majumder, Rada Mihalcea, Eduard Hovy (2019))

Real-time vocal features extraction for automated suicidal risk assessment in hotlines
(C. Aguet, L. Falissard, F. Shurmann, N. Howard)

Click on the button bellow to find more information about the research papers

Request Research Papers

Over a decade of research
bundled into one innovative solution only for you

Aiberry’s innovative technology is the result of over a decade of research performed by our Chief Scientist Dr. Newton Howard, who is one of today’s foremost experts in computational and cognitive neurosciences and his collaborators. This in-depth research in the field of Sentiment Analysis, Intention Awareness and Multi-modal Dialogue Systems positions us to create novel and impactful behavioral health products and platforms.

  • Approach Towards a Natural Language Analysis for Diagnosing Mood Disorders and Comorbid Conditions (Dr. Newton Howard (2013))
  • Emotion Recognition in Conversation: Research Challenges, Datasets, and Recent Advances (Soujanya Poria, Navonil Majumder, Rada Mihalcea, Eduard Hovy (2019))
  • Fusing audio, visual, and textual clues for sentiment analysis from multimodal content (Soujanya Poria, Erik Cambria, Newton Howard, Guang-Bin Huang, Amir Hussain (2015))
  • Real-time vocal features extraction for automated suicidal risk assessment in hotlines (C. Aguet, L. Falissard, F. Shurmann, N. Howard)
  • Towards a Differential Diagnostic of PTSD Using Cognitive Computing Methods (Newton Howard, Louis Jehel, Romain Arnal (2014))
Request Research Papers

Clinically validated mental health solutions that work for all

We strongly believe in developing AI tools using the same rigorous standards as research clinicians. Tools that work for all segments of society. We are conducting a multi-site clinical study to validate the efficacy of our depression solution across different demographics.

Get in touch with us

Clinically validated mental health solutions that work for all

We strongly believe in developing AI tools using the same rigorous standards as research clinicians. Tools that work for all segments of society. We are conducting a multi-site clinical study to validate the efficacy of our depression solution across different demographics.

GET IN TOUCH WITH US

A Controlled Clinical Trial to Train the Aiberry AI Depression Detection Platform

Controlled, multicenter trial to train and validate the Aiberry platform’s ability to detect depression in a diverse patient population (ages 13 – 79).

Clinical Study Partners:
Learn More About Our Clinical Study

A Firm Commitment to Patient Safety, Security and Privacy

Patient privacy and protection is our responsibility, and we are steadfast in ensuring that our solution meets the highest standards at every turn. Aiberry incorporates state of the art security and encryption measures to ensure complete patient privacy and data security.

Request a Demo