Albert Tate1, Jennifer Walsh2,3, Veena Kurup2,3, Bindiya Shenoy2,3, Dwayne Mann1, Craig Freakley1, Peter Eastwood2,3, Philip Terrill1. 1. School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Queensland, Australia. 2. Centre for Sleep Science, School of Human Sciences, University of Western Australia. 3. West Australian Sleep Disorders Research Institute, Sir Charles Gairdner Hospital.
Abstract
STUDY OBJECTIVES: Body posture has a significant impact on the presence and severity of obstructive sleep apnea (OSA). The majority of polysomnography (PSG) systems have the capacity to categorize body (torso) posture as supine, left-lateral, right-lateral or prone, each within a 90-degree range. However, such broad categorization may limit the identification of subtle relationships between posture and OSA severity. The aim of this study was to quantify sleeping posture as a continuous variable; and to develop an intuitive tool for visualizing the relationship between body posture and OSA severity. METHODS: A customized triaxial accelerometer-based posture sensor which quantifies torso posture as a continuous variable was developed. 38 participants attending the sleep laboratory for suspected OSA were recruited. Each participant underwent a diagnostic PSG with an additional customized posture sensor securely attached to the sternum. Individual data were presented using a novel circular histogram-based visualization which displays sleeping position and position-specific OSA severity. RESULTS: Acceptable measurements were obtained in 21 participants. The mean ± standard deviation percentage of total sleep time spent within ± 15 degrees of the center of supine, left-lateral, right-lateral and prone was 59.7 ± 26.0%. A further 40.3 ± 26.0% of sleep time was spent in intermediate positions outside these traditional categorizations. The novel visualization revealed a wide variety of positional OSA phenotypes. CONCLUSIONS: Quantification of torso posture as a continuous variable and analysis of these data using a novel visualization enables the identification of subtle relationships between body posture and OSA severity that are not apparent using standard clinical sensors and summary statistics.
STUDY OBJECTIVES: Body posture has a significant impact on the presence and severity of obstructive sleep apnea (OSA). The majority of polysomnography (PSG) systems have the capacity to categorize body (torso) posture as supine, left-lateral, right-lateral or prone, each within a 90-degree range. However, such broad categorization may limit the identification of subtle relationships between posture and OSA severity. The aim of this study was to quantify sleeping posture as a continuous variable; and to develop an intuitive tool for visualizing the relationship between body posture and OSA severity. METHODS: A customized triaxial accelerometer-based posture sensor which quantifies torso posture as a continuous variable was developed. 38 participants attending the sleep laboratory for suspected OSA were recruited. Each participant underwent a diagnostic PSG with an additional customized posture sensor securely attached to the sternum. Individual data were presented using a novel circular histogram-based visualization which displays sleeping position and position-specific OSA severity. RESULTS: Acceptable measurements were obtained in 21 participants. The mean ± standard deviation percentage of total sleep time spent within ± 15 degrees of the center of supine, left-lateral, right-lateral and prone was 59.7 ± 26.0%. A further 40.3 ± 26.0% of sleep time was spent in intermediate positions outside these traditional categorizations. The novel visualization revealed a wide variety of positional OSA phenotypes. CONCLUSIONS: Quantification of torso posture as a continuous variable and analysis of these data using a novel visualization enables the identification of subtle relationships between body posture and OSA severity that are not apparent using standard clinical sensors and summary statistics.
Authors: Panagis Drakatos; Sean E Higgins; Christopher A Kosky; Rexford T Muza; Adrian J Williams Journal: Am J Respir Crit Care Med Date: 2013-05-15 Impact factor: 21.405
Authors: Ellen R van Kesteren; J Peter van Maanen; Anthony A J Hilgevoord; D Martin Laman; Nico de Vries Journal: Sleep Date: 2011-08-01 Impact factor: 5.849
Authors: Simon A Joosten; Kais Hamza; Scott Sands; Anthony Turton; Philip Berger; Garun Hamilton Journal: Respirology Date: 2012-01 Impact factor: 6.424
Authors: Richard B Berry; Rohit Budhiraja; Daniel J Gottlieb; David Gozal; Conrad Iber; Vishesh K Kapur; Carole L Marcus; Reena Mehra; Sairam Parthasarathy; Stuart F Quan; Susan Redline; Kingman P Strohl; Sally L Davidson Ward; Michelle M Tangredi Journal: J Clin Sleep Med Date: 2012-10-15 Impact factor: 4.062
Authors: Simon A Joosten; Fergal J O'Donoghue; Peter D Rochford; Maree Barnes; Kais Hamza; Thomas J Churchward; Philip J Berger; Garun S Hamilton Journal: Ann Am Thorac Soc Date: 2014-06