Tripat Deep Singh: basic polysomnography: an algorithmic approach to sleep scoring

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Tripat Deep Singh: basic polysomnography: an algorithmic approach to sleep scoring Deepak Shrivastava1  Received: 1 September 2020 / Revised: 1 September 2020 / Accepted: 11 September 2020 © Springer Nature Singapore Pte Ltd. 2020

Just like obtaining a good quality signal without noise defines the quality of the polysomnogram, similarly, accurate scoring of the collected data defines the quality of the ultimate report. While scoring is an art, it is a formidable challenge especially for the beginners. The American Academy of Sleep Medicine developed “The AASM manual for the scoring of sleep and associated events: rules, terminology and technical specifications’ in 2007” [1]. This document replaced the old Rechtschaffen and Kales (R&K) criteria for sleep scoring. Since then AASM has constantly improved the rules and many versions have been published [2]. Although there is more scientific reasoning, some evidence and standardization, most rules still lack scientific levels of standard practice parameters and the vast majority is based on consensus [3] Scoring of polysomnographic (PSG) data remains a manual task of visually annotating three primary categories: sleep stages, respiratory events, and limb movements [4]. Visual sleep scoring is a time-consuming and subjective process. Many projects are underway to design accurate computerized flow charts and algorithms based on multichannel signals and single-channel recordings for automatic scoring with high degree of confidence [5]. However, the science of autoscoring is still inexact and not validated for the clinical use. In addition, it requires supervised editing and over-scoring of a certified sleep technologist. “Basic Polysomnography” is a conceptual breakthrough in how to simplify the science of scoring, while maintaining the quality and conformity to the current AASM scoring rules. In a total of 13 chapters, spanning over 78 pages, this book provides a framework to learn scoring not only with accuracy but within shorter period of time. The first four chapters briefly yet clearly review the recognition of various waveforms supplanted with clear annotations. Reproduction * Deepak Shrivastava [email protected] 1



of the epoch images is excellent and reader can easily discern depicted waveforms. Most important events are highlighted or boxed to draw attention without visually scanning for them. Subsequent chapters flow in a systematic fashion and reader can easily recognize repeating pattern of the algorithms. Once this realization of flow occurs, the learning curve becomes steep. Chapter 5 is the largest one, that reviews scoring of the sleep stages in Dr. Tripat’s copyrighted algorithmic approach. Strategically embedded epochs continue to help visually comprehend some of the difficult concepts. Using specific graphic design to show a descending process with multiple steps and sub-steps, the author moves in a logical fashion. Remaining chapters address scoring of arousals, respiratory events, limb movements and cardiac movements using the