Remote Speech Analysis in the Evaluation of Hospitalized Patients With Acute Decompensated Heart Failure

医学 失代偿 心力衰竭 急性失代偿性心力衰竭 心脏病学 听力学 内科学 语音识别 计算机科学
作者
Offer Amir,William T. Abraham,Zaher S. Azzam,Gidon Berger,Deepak L. Bhatt,Sean Pinney,Daniel Burkhoff,Ilan D. Shallom,Chaim Lotan,Elazer R. Edelman
出处
期刊:Jacc-Heart Failure [Elsevier BV]
卷期号:10 (1): 41-49 被引量:33
标识
DOI:10.1016/j.jchf.2021.08.008
摘要

This study assessed the performance of an automated speech analysis technology in detecting pulmonary fluid overload in patients with acute decompensated heart failure (ADHF).Pulmonary edema is the main cause of heart failure (HF)-related hospitalizations and a key predictor of poor postdischarge prognosis. Frequent monitoring is often recommended, but signs of decompensation are often missed. Voice and sound analysis technologies have been shown to successfully identify clinical conditions that affect vocal cord vibration mechanics.Adult patients with ADHF (n = 40) recorded 5 sentences, in 1 of 3 languages, using HearO, a proprietary speech processing and analysis application, upon admission (wet) to and discharge (dry) from the hospital. Recordings were analyzed for 5 distinct speech measures (SMs), each a distinct time, frequency resolution, and linear versus perceptual (ear) model; mean change from baseline SMs was calculated.In total, 1,484 recordings were analyzed. Discharge recordings were successfully tagged as distinctly different from baseline (wet) in 94% of cases, with distinct differences shown for all 5 SMs in 87.5% of cases. The largest change from baseline was documented for SM2 (218%). Unsupervised, blinded clustering of untagged admission and discharge recordings of 9 patients was further demonstrated for all 5 SMs.Automated speech analysis technology can identify voice alterations reflective of HF status. This platform is expected to provide a valuable contribution to in-person and remote follow-up of patients with HF, by alerting to imminent deterioration, thereby reducing hospitalization rates. (Clinical Evaluation of Cordio App in Adult Patients With CHF; NCT03266029).
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