Obstructive sleep apnea (OSA) is an under-diagnosed risk factor for several adverse health outcomes. The gold standard diagnostic test for OSA is laboratory-based polysomnography (PSG). Portable sleep monitoring has been studied as an alternative for patients lacking access to PSG. This study aimed to assess the validity of the Zephyr BioHarness 3 (BH3), a chest-worn activity monitor that records movement, electrocardiography, and respiratory parameters, to identify apnea events in patients suspected of OSA. Patients (N = 18) underwent single-night laboratory-based PSG while wearing the BH3. PSG data were scored in 30-second epochs by PSG technicians. PSG and BH3 data were sampled and analyzed using three sets of features with a radial basis function support vector machine and three-layer neural networks: (1) apnea events were identified second by second using 5-second windows of raw BH3 data (sensitivity = 48.0 ± 8.7%, specificity = 75.6 ± 3.0%, accuracy = 74.4 ± 2.7%); (2) apnea events were identified second by second using mean, median, and variance values of 5-second windows of BH3 data (sensitivity = 54.7 ± 17.3%, specificity = 66.5 ± 12.1%, accuracy = 66.0 ± 10.9%); and (3) apnea events were identified second by second using phase-space transformation of BH3 data (sensitivity = 68.4 ± 9.0%, specificity = 81.5 ± 2.7%, accuracy = 80.9 ±2.5% for τ = 60; sensitivity = 64.0 ± 7.9%, specificity = 81.8 ± 2.5%, accuracy = 81.0 ± 2.3% for τ = 70). The BH3 may be useful for patients suspected of OSA without timely access to PSG.
Eduardo Salazar, Mayank Gupta, Meynard Toledo, Qiao Wang, Pavan Turaga, James M. Parish and Matthew P. Buman
Jennifer L. Huberty, Jeni L. Matthews, Meynard Toledo, Lindsay Smith, Catherine L. Jarrett, Benjamin Duncan and Matthew P. Buman
Purpose: To estimate the energy expenditure (EE) of Vinyasa Flow and validate the Actigraph (AG) and GENEActiv (GA) for measuring EE in Vinyasa Flow. Methods: Participants (N = 22) were fitted to a mask attached to the Oxycon. An AG was placed on the left hip and a GA was placed on the non-dominant wrist. Participants were randomized to an initial resting activity before completing a 30-minute Vinyasa Flow video. AG data was scored using the Freedson VM3 (2011) and the Freedson Adult (1998) algorithms in the Actilife software platform. EE from GA were derived using cut points from a previous study. Date and time filters were added corresponding to the time stamps recorded by the tablet video files of each yoga session. Kcals and METs expended by participants were calculated using bodyweight measured during their visit. Data was analyzed using SPSS. A dependent samples t-test, an intraclass correlation coefficient (ICC), and mean absolute difference were used to determine agreement between variables. Results: According to the Oxycon, participation in Vinyasa Flow required an average EE of 3.2 ± 0.4 METs. The absolute agreement between the Oxycon, AG, or GA was poor (ICC < .20). The mean difference in METs for the AG was −2.1 ± 0.6 and GA was −1.4 ± 0.6 (all p < .01). Conclusion: According to the Oxycon, participation in Vinyasa Flow met the criteria for moderate-intensity physical activity. The AG and GA consistently underestimated EE. More research is needed to determine an accurate measurement for EE during yoga using a wearable device appropriate for free-living environments.