Editor’s note: This article is by Dr. Guillermo
Cecchi of IBM Research’s Computational Biology Group.
Analyzing the spoken words of people with mental
health disorders could significantly improve the accuracy of diagnosing mania
and schizophrenia. In a PLoS ONE paper, my Computational
Biology team collaborating with researchers and clinicians in Brazil showed
that quantifying and graphing only speech was 93 percent accurate in
identifying these cases of psychosis.
This collaboration with professionals across medical, neuroscience, and
technical departments at Brazil’s Federal University, and Universidade de Sao
Paulo was the first time that psychiatric differential diagnosis was
implemented directly from speech analysis. In other words, our study, Speech
Graphs Provide a Quantitative Measure of Thought Disorder in Psychosis
, was the first to relate thought
disorder with mathematical structures – graphs.
|We transcribe the speech to text,|
and create graphs in which nodes
denote words, and edges
between them indicate the
temporal succession of the wor
Diseases such as cancer have clear genomic and proteomic signatures, while psychiatric
conditions are more elusive, and may be mostly determined by functional
disruptions (problems with our human “software” versus our “hardware”). We set
out to show how psychiatry can benefit from computational insights.
did we do, and what did we find?
at Federal University interviewed hospital patients using standard
diagnostic methods, according to the Diagnostic and Statistical Manual of
Mental Disorders requirements. The IBM team
wanted the text. And after the interviews were manually translated into
English, we analytically confirmed – through graphs – the qualitative features
of mania and schizophrenia.
graphs are more verbose and contain more loops (when the patient’s train of
thought continually return to the same concept) than a normal graph. Schizophrenic
graphs are less verbose, but more tangential (when a patient’s focus on one concept
consistently changes to many other concepts) than normal.
Traditional interviews consider a handful of scales that quantify the
severity of symptoms, with final diagnosis resting with the judgment of the
psychiatrist. This method is about 62 percent accurate. Taking only patterns of
words – how many words were spoken; how quickly they were spoken; how topical
they were – our study’s diagnosis was 93 percent accurate.
|Speech graph analysis in schizophrenia, mania
and control reports. A) Subjects were asked to report a recent dream. Each
report was transcribed and parsed into canonical grammatical elements (words
translated from Portuguese, elements separated by slashes). Parts related to
dreaming (blue) were sorted from parts related to waking (red), which were
considered deviations from the anchor topic. B) Speech graph from the example
shown in A), with edges sequentially numbered. The node ‘‘I’’ appears 3 times
in the dream sub-graph (‘‘I walked’’, ‘‘I found’’, ‘‘I hugged’’), and then once
in the waking sub-graph (‘‘I woke up’’). C) Speech graph examples
representative of the schizophrenics (subject MG), manics (subject AB) and
controls (subject OR). Graphs plotted using global energy minimum (GEM). The complete
database is available as Supporting Information.
difference is purely due to psychiatrists’ use of other factors to make a
is part of the spectrum of thought disorders, and the most conspicuous symptoms
are expressed in language. Today, the main tool for diagnosis is the personal
interview, and a doctor’s assessment of abnormal thought processes reflected in
are the most-prominent variables when talking about manic and schizophrenic
conditions. We want to establish variables and boundaries – such as the number
of words to indicate a condition – that could be put into a technology that will
provide clinicians, as well as researchers, with a more quantitative look at
their data so that their diagnosis and treatment decisions, which ultimately
rest with them, can be better informed.
We are also
engaged in extending these initial results to larger cohorts, as well as other
modalities of thought and emotional alterations, such as autism and Asperger’s.
Preliminary indications show that semantic measures of similarity between words
(as opposed to the speech structure revealed by graphs) can be used to help diagnose
these other psychiatric conditions that affect emotional processing.
Read the complete report, here: Speech
Graphs Provide a Quantitative Measure of Thought Disorder in Psychosis.
Labels: computational biology, ibmresearch, manic, PLoS ONE, psychiatry, psychology, schizophrenia