Pentax Medical, ASHA digitize voice disorder assessment

The new integration will allow clinicians using Pentax's acoustic products to enter data electronically rather than manually. (Pentax Medical)

Pentax Medical and the American Speech-Language-Hearing Association have inked a licensing deal to integrate the latter’s voice assessment tool into the former’s acoustic products.

ASHA developed a tool, dubbed Consensus Auditory-Perceptual Evaluation of Voice, or CAPE-V, to serve as a standard protocol for speech pathologists making clinical assessments of voice quality, according to the statement.

Under the agreement, Pentax will integrate the tool into its Visi-Pitch and Computerized Speech Lab products. Used to record a patient’s speech, the systems then display a visual representation of the sound, employing various measures of speech and voice quality, the company says.

Now, clinicians may enter data electronically, rather than on paper, Pentax said in the statement. It allows clinicians to electronically measure CAPE-V scores using a sliding visual analog scale, rather than requiring manual measurements.

"Pentax Medical is dedicated to working with ASHA and the speech-language pathologist, voice scientist and logopedist communities to develop products that further the field and help the patient population," said Jim Cavanaugh, vice president of global product management at Pentax. "We are extremely excited to have partnered with ASHA to develop a meaningful advancement to the industry."

While the deal could improve the assessment of patients with voice disorders, some companies are working on ways to use the voice to diagnose conditions that affect other parts of the body.

Last year, PureTech’s Sonde Health joined forces with MIT on a platform that analyzes “vocal biomarkers” in voice samples to identify changes in a person’s health or disease status. These biomarkers are nonlinguistic characteristics, including changes in pitch or hoarseness. And Mindstrong is looking to “digitally phenotype” mental health disorders by analyzing how people use a smartphone, which includes word choice while texting and voice patterns while speaking to digital assistants.

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