Pinna Gian Domenico, La Rovere Maria Teresa, Robbi Elena, Maestri Roberto
Department of Biomedical Engineering, S. Maugeri Foundation, Montescano, Italy.
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:3571-4. doi: 10.1109/IEMBS.2010.5627463.
In this manuscript we present an overview of novel signal processing techniques developed by our group to reduce scoring time in the assessment of the severity of sleep-related breathing disorders in heart failure patients and to detect sleep/wake fluctuations during periodic breathing. Besides describing these methods, we present the results of validation experiments. Our work shows that novel signal processing techniques can reduce costs and resources needed to screen the patients and can provide relevant information for better understanding the role of wake/sleep transitions in the development and maintenance of breathing disorders.
在本手稿中，我们概述了我们团队开发的新型信号处理技术，这些技术用于减少心力衰竭患者睡眠相关呼吸障碍严重程度评估中的评分时间，并检测周期性呼吸期间的睡眠/觉醒波动。除了描述这些方法外，我们还展示了验证实验的结果。我们的工作表明，新型信号处理技术可以降低筛查患者所需的成本和资源，并可为更好地理解觉醒/睡眠转换在呼吸障碍发生和维持中的作用提供相关信息。
