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Novel Speech Recognizing App may help Predict HF by recognising fluid buildup in lungs: Study
Heart failure (HF) is a progressive condition that affects approximately 26 million people worldwide. Most patients with HF present to the hospital with fluid retention, which manifests as worsening dyspnea caused by pulmonary edema. In a recent study, researchers have developed a novel mobile app, HearO that detects changes in speech which predicts clinical congestion in patients with HF. The study findings were published in the journal JACC: Heart Failure on December 8, 2021.
Recent advances in speech, voice, and sound analysis enabled the identification of speech features of clinical significance. Various speech processing algorithms have been developed to use such features in screening for depression, pneumonia-asthma, coronary artery disease, and an autism spectrum disorder. Pulmonary edema is the main cause of heart failure (HF)−related hospitalizations. It is an important predictor of poor prognosis after discharge. Frequent monitoring is often recommended, but signs of decompensation are overlooked. Recently, Dr Offer Amir and his team conducted a study to assess the performance of an automated speech analysis technology in detecting pulmonary fluid overload in patients with acute decompensated heart failure (ADHF). They distinguishing between ADHF on admission ("wet") versus at discharge ("dry") by using a novel speaker verification, speech processing, and analysis technology, implemented within a proprietary Smartphone application (app) (HearO Cordio Medical Ltd, Or Yehuda, Israel).
In this observational open-label study, the researchers included a total of 40 patients with ADHF and recorded 5 sentences, in 1 of 3 languages, using HearO app, upon admission (wet) to and discharge (dry) from the hospital. HerO app is a proprietary speech processing application that was used to record and digitize the patients' speech. The researchers uploaded the speech files to the server, where they were stored and analyzed. Recordings were analyzed for 5 distinct speech measures (SMs), each a distinct time, frequency resolution, and linear versus perceptual (ear) model. They further calculated the mean change from baseline SMs.
Article Source : JACC Heart Failure
Medical Dialogues Bureau consists of a team of passionate medical/scientific writers, led by doctors and healthcare researchers. Our team efforts to bring you updated and timely news about the important happenings of the medical and healthcare sector. Our editorial team can be reached at editorial@medicaldialogues.in.
Dr Kamal Kant Kohli-MBBS, DTCD- a chest specialist with more than 30 years of practice and a flair for writing clinical articles, Dr Kamal Kant Kohli joined Medical Dialogues as a Chief Editor of Medical News. Besides writing articles, as an editor, he proofreads and verifies all the medical content published on Medical Dialogues including those coming from journals, studies,medical conferences,guidelines etc. Email: drkohli@medicaldialogues.in. Contact no. 011-43720751