Newly designed computer program using artificial intelligence (AI) tool can now help diagnose post-traumatic stress disorder (PTSD) in veterans by simply analyzing their voices. The findings of the study are published in the journal Depression and Anxiety.
The study found that an artificial intelligence tool can distinguish - with 89 percent accuracy - between the voices of those with or without PTSD.
Post Traumatic Stress Disorder
Post Traumatic Stress Disorder (PTSD), is a mental condition triggered by a traumatic event. PTSD treatment includes pyschotherapy, behavior therapy and medications.
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‘Artificial intelligence (AI) tool can now help diagnose post-traumatic stress disorder (PTSD) in veterans by just analyzing their voices.’
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"Our findings suggest that speech-based characteristics can be used to diagnose this disease, and with further refinement and validation, may be employed in the clinic in the near future," says senior study author Charles R. Marmar, MD, the Lucius N. Littauer Professor and chair of the Department of Psychiatry at NYU School of Medicine.
More than 70 percent of adults worldwide experience a traumatic event at some point in their lives, with up to 12 percent of people in some struggling countries suffering from PTSD. Those with the condition experience strong, persistent distress when reminded of a triggering event.
![Potential PTSD Treatment Improvement Discovered]( "Potential PTSD Treatment Improvement Discovered")
Novel way improves a common treatment for post-traumatic stress disorder (PTSD) by altering how the brain learns to react less severely to fearful conditions, finds a new study.
The study authors say that a PTSD diagnosis is most often determined by clinical interview or a self-report assessment, both inherently prone to biases. This has led to efforts to develop objective, measurable, physical markers of PTSD progression, much like laboratory values for medical conditions, but progress has been slow.
Learning How to Learn
In the current study, the research team used a statistical/machine learning technique, called random forests, that has the ability to "learn" how to classify individuals based on examples. Such AI programs build "decision" rules and mathematical models that enable decision-making with increasing accuracy as the amount of training data grows.
The research team first recorded standard, hours-long diagnostic interviews, called Clinician-Administered PTSD Scale, or CAPS, of 53 Iraq and Afghanistan veterans with military-service-related PTSD, as well as those of 78 veterans without the disease. The recordings were then fed into voice software from SRI International - the institute that also invented Siri - to yield a total of 40,526 speech-based features captured in short spurts of talk, which the team's AI program sifted through for patterns.
The random forest program linked patterns of specific voice features with PTSD, including less clear speech and a lifeless, metallic tone, both of which had long been reported anecdotally as helpful in diagnosis. While the current study did not explore the disease mechanisms behind PTSD, the theory is that traumatic events change brain circuits that process emotion and muscle tone, which affects a person's voice.
Moving forward, the research team plans to train the AI voice tool with more data, further validate it on an independent sample, and apply for government approval to use the tool clinically.
"Speech is an attractive candidate for use in an automated diagnostic system, perhaps as part of a future PTSD smartphone app, because it can be measured cheaply, remotely, and non-intrusively," says lead author Adam Brown, Ph.D., adjunct assistant professor in the Department of Psychiatry at NYU School of Medicine.
"The speech analysis technology used in the current study on PTSD detection falls into the range of capabilities included in our speech analytics platform called SenSay Analytics™," says Dimitra Vergyri, director of SRI International's Speech Technology and Research (STAR) Laboratory.
"The software analyzes words - in combination with frequency, rhythm, tone, and articulatory characteristics of speech - to infer the state of the speaker, including emotion, sentiment, cognition, health, mental health, and communication quality. The technology has been involved in a series of industry applications visible in startups like Oto, Ambit and Decoded Health."
Source: Eurekalert
Potential PTSD Treatment Improvement Discovered
Novel way improves a common treatment for post-traumatic stress disorder (PTSD) by altering how the brain learns to react less severely to fearful conditions, finds a new study.
Advertisement
The study authors say that a PTSD diagnosis is most often determined by clinical interview or a self-report assessment, both inherently prone to biases. This has led to efforts to develop objective, measurable, physical markers of PTSD progression, much like laboratory values for medical conditions, but progress has been slow.
Learning How to Learn
In the current study, the research team used a statistical/machine learning technique, called random forests, that has the ability to "learn" how to classify individuals based on examples. Such AI programs build "decision" rules and mathematical models that enable decision-making with increasing accuracy as the amount of training data grows.
The research team first recorded standard, hours-long diagnostic interviews, called Clinician-Administered PTSD Scale, or CAPS, of 53 Iraq and Afghanistan veterans with military-service-related PTSD, as well as those of 78 veterans without the disease. The recordings were then fed into voice software from SRI International - the institute that also invented Siri - to yield a total of 40,526 speech-based features captured in short spurts of talk, which the team's AI program sifted through for patterns.
The random forest program linked patterns of specific voice features with PTSD, including less clear speech and a lifeless, metallic tone, both of which had long been reported anecdotally as helpful in diagnosis. While the current study did not explore the disease mechanisms behind PTSD, the theory is that traumatic events change brain circuits that process emotion and muscle tone, which affects a person's voice.
Moving forward, the research team plans to train the AI voice tool with more data, further validate it on an independent sample, and apply for government approval to use the tool clinically.
"Speech is an attractive candidate for use in an automated diagnostic system, perhaps as part of a future PTSD smartphone app, because it can be measured cheaply, remotely, and non-intrusively," says lead author Adam Brown, Ph.D., adjunct assistant professor in the Department of Psychiatry at NYU School of Medicine.
"The speech analysis technology used in the current study on PTSD detection falls into the range of capabilities included in our speech analytics platform called SenSay Analytics™," says Dimitra Vergyri, director of SRI International's Speech Technology and Research (STAR) Laboratory.
"The software analyzes words - in combination with frequency, rhythm, tone, and articulatory characteristics of speech - to infer the state of the speaker, including emotion, sentiment, cognition, health, mental health, and communication quality. The technology has been involved in a series of industry applications visible in startups like Oto, Ambit and Decoded Health."
Source: Eurekalert
PTSD in Children: Fresh Insights
Children are more likely to suffer Post Traumatic Stress Disorder (PTSD) if they think their reaction to traumatic events is not 'normal', found new study.
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Predicting the Chances of PTSD Using a New Analytical ModelA new analytical model has been developed by the scientists that can predict the likelihood of developing Post-Traumatic Stress Disorder after a shock or scary event. | Advertisement
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