OBJECTIVES: The aim of this project was to evaluate the diagnostic accuracy of an automated, remote system for correctly identifying vocal fold paralysis. METHODS:Consecutive patients presenting for vocal analysis at the Beaumont Hospital Voice Clinic were enrolled in this prospective, blinded study. Control patients were enlisted from routine otolaryngology clinics. All patients were assessed by standard history, clinical examination, and flexible laryngoscopy or videostroboscopy. The subjects were blindly assessed by remote voice analysis. Sustained phonation was recorded over a standard telephone network. Each recording was subjected to automated, remote analysis of extracted features, including measures of pitch perturbation, amplitude perturbation, and harmonics-to-noise ratio. The presence or absence of a vocal fold paralysis as determined by the automated classifier was recorded and correlated with clinical findings. RESULTS:Seventy-eight consecutive patients were enrolled in the study. The automated speech analysis system demonstrated 92% sensitivity and 75% specificity for detecting vocal fold paralysis. CONCLUSIONS: This pilot study, assessing an automated system that analyzes audiological data remotely over the standard telephone network, suggests that with further "training" it may become a reliable, simple, and convenient means for screening patients for voice disorders.
RCT Entities:
OBJECTIVES: The aim of this project was to evaluate the diagnostic accuracy of an automated, remote system for correctly identifying vocal fold paralysis. METHODS: Consecutive patients presenting for vocal analysis at the Beaumont Hospital Voice Clinic were enrolled in this prospective, blinded study. Control patients were enlisted from routine otolaryngology clinics. All patients were assessed by standard history, clinical examination, and flexible laryngoscopy or videostroboscopy. The subjects were blindly assessed by remote voice analysis. Sustained phonation was recorded over a standard telephone network. Each recording was subjected to automated, remote analysis of extracted features, including measures of pitch perturbation, amplitude perturbation, and harmonics-to-noise ratio. The presence or absence of a vocal fold paralysis as determined by the automated classifier was recorded and correlated with clinical findings. RESULTS: Seventy-eight consecutive patients were enrolled in the study. The automated speech analysis system demonstrated 92% sensitivity and 75% specificity for detecting vocal fold paralysis. CONCLUSIONS: This pilot study, assessing an automated system that analyzes audiological data remotely over the standard telephone network, suggests that with further "training" it may become a reliable, simple, and convenient means for screening patients for voice disorders.
Authors: Janet S Choi; Victoria Yin; Franklin Wu; Neel K Bhatt; Karla O'Dell; Michael Johns Journal: Laryngoscope Date: 2021-08-24 Impact factor: 2.970
Authors: Amrita K Singh; David A Kasle; Roy Jiang; Jordan Sukys; Emily L Savoca; Michael Z Lerner; Nikita Kohli Journal: Laryngoscope Date: 2020-10-01 Impact factor: 2.970