Expanding the functionality of speech recognition in radiology: Creating a real-time methodology for measurement and analysis of occupational stress and fatigue

摘要

While occupational stress and fatigue have been well described throughout medicine, the radiology community is particularly susceptible due to declining reimbursements, heightened demands for service deliverables, and increasing exam volume and complexity. The resulting occupational stress can be variable in nature and dependent upon a number of intrinsic and extrinsic stressors. Intrinsic stressors largely account for inter-radiologist stress variability and relate to unique attributes of the radiologist such as personality, emotional state, education/training, and experience. Extrinsic stressors may account for intra-radiologist stress variability and include cumulative workload and task complexity. The creation of personalized stress profiles creates a mechanism for accounting for both inter- and intra-radiologist stress variability, which is essential in creating customizable stress intervention strategies. One viable option for real-time occupational stress measurement is voice stress analysis, which can be directly implemented through existing speech recognition technology and has been proven to be effective in stress measurement and analysis outside of medicine. This technology operates by detecting stress in the acoustic properties of speech through a number of different variables including duration, glottis source factors, pitch distribution, spectral structure, and intensity. The correlation of these speech derived stress measures with outcomes data can be used to determine the user-specific inflection point at which stress becomes detrimental to clinical performance.