Background:The relationship between osteopathic manipulative treatment (OMT) and the autonomic nervous system has long been acknowledged, but is poorly understood. In an effort to define this relationship, cervical myofascial release was used as the OMT technique with heart rate variability (HRV) as a surrogate for autonomic activity. This study quantifies that relationship and demonstrates a cause and effect.
This paper introduces an online sleep apnea detection method based on heart rate complexity as measured by recurrence quantification analysis (RQA) statistics of heart rate variability (HRV) data. RQA statistics can capture nonlinear dynamics of a complex cardiorespiratory system during obstructive sleep apnea. In order to obtain a more robust measurement of the nonstationarity of the cardiorespiratory system, we use different fixed amount of neighbor thresholdings for recurrence plot calculation. We integrate a feature selection algorithm based on conditional mutual information to select the most informative RQA features for classification, and hence, to speed up the real-time classification process without degrading the performance of the system. Two types of binary classifiers, i.e., support vector machine and neural network, are used to differentiate apnea from normal sleep. A soft decision fusion rule is developed to combine the results of these classifiers in order to improve the classification performance of the whole system. Experimental results show that our proposed method achieves better classification results compared with the previous recurrence analysis-based approach. We also show that our method is flexible and a strong candidate for a real efficient sleep apnea detection system.
Purpose
– The purpose of this paper is to review the historical development of Lean Six Sigma and to identify the relevant opportunities for the application of Lean Six Sigma within the university setting. The paper also discusses the challenges of Lean Six Sigma implementation in higher education, as well as the cultural changes necessary to provide an appropriate climate for its long-term success.
Design/methodology/approach
– The paper contains a comprehensive discussion of the development of Lean Six Sigma over the past three decades. Additionally, the paper describes how Lean Six Sigma may be applied in the university setting to improve processes in curriculum delivery; business and auxiliary services; admissions and enrollment management; and research.
Findings
– Lean Six Sigma can be applied to facilitate process improvements in curriculum delivery; business and auxiliary services; admissions and enrollment management; and research. While obstacles to Lean Six Sigma implementation exist, the process improvements and resulting cultural changes are worthwhile and noteworthy.
Research limitations/implications
– The paper serves as a guide for how Lean Six Sigma processes can be utilized in the higher education setting. Other researchers and practitioners may use the paper as a practical orientation to Lean Six Sigma in the university setting.
Originality/value
– Due to the unique culture of higher education, the application of Lean Six Sigma to university processes has been sparse. The paper provides a needed orientation as to how Lean Six Sigma may be applied to improve some of the more important functional aspects of the university.
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