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van Gilst MM, Wulterkens BM, Fonseca P, Radha M, Ross M, Moreau A, Cerny A, Anderer P, Long X, van Dijk JP, Overeem S. Direct application of an ECG-based sleep staging algorithm on reflective photoplethysmography data decreases performance. BMC Res Notes 2020; 13:513. [PMID: 33168051 PMCID: PMC7653690 DOI: 10.1186/s13104-020-05355-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 10/23/2020] [Indexed: 02/05/2023] Open
Abstract
OBJECTIVE The maturation of neural network-based techniques in combination with the availability of large sleep datasets has increased the interest in alternative methods of sleep monitoring. For unobtrusive sleep staging, the most promising algorithms are based on heart rate variability computed from inter-beat intervals (IBIs) derived from ECG-data. The practical application of these algorithms is even more promising when alternative ways of obtaining IBIs, such as wrist-worn photoplethysmography (PPG) can be used. However, studies validating sleep staging algorithms directly on PPG-based data are limited. RESULTS We applied an automatic sleep staging algorithm trained and validated on ECG-data directly on inter-beat intervals derived from a wrist-worn PPG sensor, in 389 polysomnographic recordings of patients with a variety of sleep disorders. While the algorithm reached moderate agreement with gold standard polysomnography, the performance was significantly lower when applied on PPG- versus ECG-derived heart rate variability data (kappa 0.56 versus 0.60, p < 0.001; accuracy 73.0% versus 75.9% p < 0.001). These results show that direct application of an algorithm on a different source of data may negatively affect performance. Algorithms need to be validated using each data source and re-training should be considered whenever possible.
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Affiliation(s)
- M M van Gilst
- Department of Electrical Engineering, Eindhoven University of Technology, PO Box 513, 5600 MB, Eindhoven, The Netherlands. .,Sleep Medicine Centre Kempenhaeghe, Sterkselseweg 65, 5591 VE, Heeze, The Netherlands.
| | - B M Wulterkens
- Department of Electrical Engineering, Eindhoven University of Technology, PO Box 513, 5600 MB, Eindhoven, The Netherlands.,Philips Research, High Tech Campus 34, 5656 AE, Eindhoven, The Netherlands
| | - P Fonseca
- Department of Electrical Engineering, Eindhoven University of Technology, PO Box 513, 5600 MB, Eindhoven, The Netherlands.,Philips Research, High Tech Campus 34, 5656 AE, Eindhoven, The Netherlands
| | - M Radha
- Department of Electrical Engineering, Eindhoven University of Technology, PO Box 513, 5600 MB, Eindhoven, The Netherlands.,Philips Research, High Tech Campus 34, 5656 AE, Eindhoven, The Netherlands
| | - M Ross
- Sleep and Respiratory Care, Home Healthcare Solutions, Philips Austria GmbH, Kranichberggasse 4, 1120, Vienna, Austria
| | - A Moreau
- Sleep and Respiratory Care, Home Healthcare Solutions, Philips Austria GmbH, Kranichberggasse 4, 1120, Vienna, Austria
| | - A Cerny
- Sleep and Respiratory Care, Home Healthcare Solutions, Philips Austria GmbH, Kranichberggasse 4, 1120, Vienna, Austria
| | - P Anderer
- Sleep and Respiratory Care, Home Healthcare Solutions, Philips Austria GmbH, Kranichberggasse 4, 1120, Vienna, Austria
| | - X Long
- Department of Electrical Engineering, Eindhoven University of Technology, PO Box 513, 5600 MB, Eindhoven, The Netherlands.,Philips Research, High Tech Campus 34, 5656 AE, Eindhoven, The Netherlands
| | - J P van Dijk
- Department of Electrical Engineering, Eindhoven University of Technology, PO Box 513, 5600 MB, Eindhoven, The Netherlands.,Sleep Medicine Centre Kempenhaeghe, Sterkselseweg 65, 5591 VE, Heeze, The Netherlands
| | - S Overeem
- Department of Electrical Engineering, Eindhoven University of Technology, PO Box 513, 5600 MB, Eindhoven, The Netherlands.,Sleep Medicine Centre Kempenhaeghe, Sterkselseweg 65, 5591 VE, Heeze, The Netherlands
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Blom LJ, Groeneveld SA, Wulterkens BM, van Rees B, Nguyen UC, Roudijk RW, Cluitmans M, Volders PGA, Hassink RJ. Novel use of repolarization parameters in electrocardiographic imaging to uncover arrhythmogenic substrate. J Electrocardiol 2020; 59:116-121. [PMID: 32062380 DOI: 10.1016/j.jelectrocard.2020.02.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Revised: 01/23/2020] [Accepted: 02/06/2020] [Indexed: 11/28/2022]
Abstract
BACKGROUND Measuring repolarization characteristics is challenging and has been reserved for experienced physicians. In electrocardiographic imaging (ECGI), activation-recovery interval (ARI) is used as a measure of local cardiac repolarization duration. We hypothesized that repolarization characteristics, such as local electrogram morphology and local and global dispersion of repolarization timing and duration could be of significance in ECGI. OBJECTIVE To further explore their potential in arrhythmic risk stratification we investigated the use of novel repolarization parameters in ECGI. MATERIALS AND METHODS We developed and compared methods for T-peak and T-end detection in reconstructed potentials. All methods were validated on annotated reconstructed electrograms (EGMs). Characteristics of the reconstructed EGMs and epicardial substrate maps in IVF patients were analyzed by using data recorded during sinus rhythm. The ECGI data were analyzed for EGM morphology, conduction, and repolarization. RESULTS We acquired ECGI data from 8 subjects for this study. In all patients we evaluated four repolarization parameters: Repolarization time, T-wave area, Tpeak-Tend interval, and T-wave alternans. Most prominent findings were steep repolarization time gradients in regions with flat EGMs. These regions were also characterized by low T-wave area and large differences in Tpeak-Tend interval. CONCLUSIONS Measuring novel repolarization parameters in reconstructed electrograms acquired with ECGI is feasible, can be done in a fully automated manner and may provide additional information on underlying arrhythmogenic substrate for risk stratification. Further studies are needed to investigate their potential use and clinical application.
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Affiliation(s)
- L J Blom
- Department of Cardiology, University Medical Center Utrecht, Utrecht, the Netherlands.
| | - S A Groeneveld
- Department of Cardiology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - B M Wulterkens
- Department of Cardiology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - B van Rees
- Department of Cardiology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University Medical Center, Maastricht, the Netherlands
| | - U C Nguyen
- Department of Cardiology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University Medical Center, Maastricht, the Netherlands
| | - R W Roudijk
- Department of Cardiology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - M Cluitmans
- Department of Cardiology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University Medical Center, Maastricht, the Netherlands
| | - P G A Volders
- Department of Cardiology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University Medical Center, Maastricht, the Netherlands
| | - R J Hassink
- Department of Cardiology, University Medical Center Utrecht, Utrecht, the Netherlands
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