Harriet Akre

• Kristiansen, Stein; Nikolaidis, Konstantinos; Plagemann, Thomas Peter; Goebel, Vera Hermine; Traaen, Gunn Marit & Øverland, Britt [Show all 13 contributors for this article] (2023). A clinical evaluation of a low-cost strain gauge respiration belt and machine learning to detect sleep apnea. Smart Health. ISSN 2352-6483. 27. doi: 10.1016/j.smhl.2023.100373. Full text in Research Archive
• Hunt, Tove Elizabeth Frances; Traaen, Gunn Marit; Aakerøy, Lars; Bendz, Christina; Øverland, Britt & Akre, Harriet [Show all 15 contributors for this article] (2022). Effect of continuous positive airway pressure therapy on recurrence of atrial fibrillation after pulmonary vein isolation in patients with obstructive sleep apnea: A randomized controlled trial. Heart Rhythm. ISSN 1547-5271. 19(9), p. 1433–1441. doi: 10.1016/j.hrthm.2022.06.016. Full text in Research Archive
• Nikolaidis, Konstantinos; Kristiansen, Stein; Plagemann, Thomas Peter; Goebel, Vera Hermine; Liestøl, Knut & Kankanhalli, Mohan [Show all 10 contributors for this article] (2022). My Health Sensor, My Classifier - Adapting a Trained Classifier to Unlabeled End-User Data. ACM Transactions on Computing for Healthcare (HEALTH). ISSN 2691-1957. 3(4), p. 1–24. doi: 10.1145/3559767. Full text in Research Archive Show summary

  Sleep apnea is a common yet severely under-diagnosed sleep related disorder. Unattended sleep monitoring at home with low-cost sensors can be leveraged for condition detection, and Machine Learning offers a generalized solution for this task. However, patient characteristics, lack of sufficient training data, and other factors can imply a domain shift between training and end-user data; and reduced task performance. In this work, we address this issue with the aim to achieve personalization based on the patient’s needs. We present an unsupervised domain adaptation (UDA) solution with the constraint that labeled source data are not directly available. Instead, a classifier trained on the source data is provided. Our solution iteratively labels target data sub-regions based on classifier beliefs, and trains new classifiers from the expanding dataset. Experiments with sleep monitoring datasets and various sensors show that our solution outperforms the classifier trained on the source domain, with a kappa coefficient improvement from 0.012 to 0.242. Additionally, we apply our solution to digit classification DA between three well-established datasets, to investigate its generalizability, and allow for related work comparisons. Even without direct access to the source data, it outperforms several well-established UDA methods in these datasets.

• Nikolaidis, Konstantinos; Kristiansen, Stein; Plagemann, Thomas Peter; Goebel, Vera Hermine; Liestøl, Knut & Kankanhalli, Mohan [Show all 10 contributors for this article] (2022). Learning Realistic Patterns from Visually Unrealistic Stimuli: Generalization and Data Anonymization (Extended Abstract). In de Raed, Luc (Eds.), Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. AAAI Press. ISSN 978-1-956792-00-3. p. 5762–5766. doi: 10.24963/ijcai.2022/806. Show summary

  Good training data is a prerequisite to develop useful Machine Learning applications. However, in many domains existing data sets cannot be shared due to privacy regulations (e.g., from medical studies). This work investigates a simple yet unconventional approach for anonymized data synthesis to enable third parties to benefit from such anonymized data. We explore the feasibility of learning implicitly from visually unrealistic, task-relevant stimuli, which are synthesized by exciting the neurons of a trained deep neural network. As such, neuronal excitation can be used to generate synthetic stimuli. The stimuli data is used to train new classification models. Furthermore, we extend this framework to inhibit representations that are associated with specific individuals. Extensive comparative empirical investigation shows that different algorithms trained on the stimuli are able to generalize successfully on the same task as the original model.

• Nikolaidis, Konstantinos; Kristiansen, Stein; Plagemann, Thomas Peter; Goebel, Vera Hermine; Liestøl, Knut & Kankanhalli, Mohan [Show all 10 contributors for this article] (2021). Learning realistic patterns from visually unrealistic stimuli: Generalization and data anonymization. The journal of artificial intelligence research. ISSN 1076-9757. 72, p. 1163–1214. doi: 10.1613/JAIR.1.13252. Full text in Research Archive Show summary

  Good training data is a prerequisite to develop useful Machine Learning applications. However, in many domains existing data sets cannot be shared due to privacy regulations (e.g., from medical studies). This work investigates a simple yet unconventional approach for anonymized data synthesis to enable third parties to benefit from such anonymized data. We explore the feasibility of learning implicitly from visually unrealistic, task-relevant stimuli, which are synthesized by exciting the neurons of a trained deep neural network. As such, neuronal excitation can be used to generate synthetic stimuli. The stimuli data is used to train new classification models. Furthermore, we extend this framework to inhibit representations that are associated with specific individuals. We use sleep monitoring data from both an open and a large closed clinical study, and Electroencephalogram sleep stage classification data, to evaluate whether (1) end-users can create and successfully use customized classification models, and (2) the identity of participants in the study is protected. Extensive comparative empirical investigation shows that different algorithms trained on the stimuli are able to generalize successfully on the same task as the original model. Architectural and algorithmic similarity between new and original models play an important role in performance. For similar architectures, the performance is close to that of using the original data (e.g., Accuracy difference of 0.56%-3.82%, Kappa coefficient difference of 0.02-0.08). Further experiments show that the stimuli can provide state-ofthe-art resilience against adversarial association and membership inference attacks.

• Kristiansen, Stein; Nikolaidis, Konstantinos; Plagemann, Thomas Peter; Goebel, Vera Hermine; Traaen, Gunn Marit & Øverland, Britt [Show all 13 contributors for this article] (2021). Machine learning for sleep apnea detection with unattended sleep monitoring at home. ACM Transactions on Computing for Healthcare (HEALTH). ISSN 2691-1957. 2(2). doi: 10.1145/3433987. Show summary

  Sleep apnea is a common and strongly under-diagnosed severe sleep-related respiratory disorder with periods of disrupted or reduced breathing during sleep. To diagnose sleep apnea, sleep data are collected with either polysomnography or polygraphy and scored by a sleep expert. We investigate in this work the use of supervised machine learning to automate the analysis of polygraphy data from the A3 study containing more than 7,400 hours of sleep monitoring data from 579 patients. We conduct a systematic comparative study of classification performance and resource use with different combinations of 27 classifiers and four sleep signals. The classifiers achieve up to 0.8941 accuracy (kappa: 0.7877) when using all four signal types simultaneously and up to 0.8543 accuracy (kappa: 0.7080) with only one signal, i.e., oxygen saturation. Methods based on deep learning outperform other methods by a large margin. All deep learning methods achieve nearly the same maximum classification performance even when they have very different architectures and sizes. When jointly accounting for classification performance, resource consumption and the ability to achieve with less training data high classification performance, we find that convolutional neural networks substantially outperform the other classifiers.

• Kristiansen, Stein; Goebel, Vera Hermine; Hamborg Andersen, Morten; Plagemann, Thomas Peter; Traaen, Gunn Marit & Øverland, Britt [Show all 8 contributors for this article] (2021). Evaluating a Low-Cost Strain Gauge Breathing Sensor for Sleep Apnea Detection at Home. In Gedeon, Ibrahim (Eds.), 2021 IEEE International Conference on Communications Workshops (ICC Workshops). IEEE (Institute of Electrical and Electronics Engineers). ISSN 978-1-7281-9441-7. doi: 10.1109/ICCWorkshops50388.2021.9473597. Show summary

  We report results and experience from a clinical evaluation of a low-cost strain gauge breathing sensor for sleep apnea detection. We collected from 34 individuals 57 nights of unattended sleep monitoring data at home with the certified Type 3 monitor Nox-T3 and the Flow strain gauge sensor from SweetZpot. The quality of the Flow data does not match the quality of the Nox-T3 data due to the much simpler build of the Flow sensor and issues during data acquisition. The Flow data can still be used to accurately discriminate between normal and disrupted breathing. With appropriate data pre-processing, we achieve a mean breath detection sensitivity of 97.2% and positive prediction value of 94.2%.

• Traaen, Gunn Marit; Aakerøy, Lars; Hunt, Tove Elizabeth Frances; Øverland, Britt; Bendz, Christina & Sande, Lars Øivind [Show all 16 contributors for this article] (2021). Effect of continuous positive airway pressure on arrhythmia in atrial fibrillation and sleep apnea a randomized controlled trial. American Journal of Respiratory and Critical Care Medicine. ISSN 1073-449X. 204(5), p. 573–582. doi: 10.1164/rccm.202011-4133OC. Show summary

  Rationale: Sleep apnea (SA) is highly prevalent in patients with atrial fibrillation (AF), and both conditions are associated with adverse cardiovascular outcomes. Objectives: To determine the effect of continuous positive airway pressure (CPAP) on AF burden. Methods: This open-label, parallel-group, randomized controlled trial included patients with paroxysmal AF and moderate to severe SA (apnea–hypopnea index ⩾15). A computerized system randomized eligible patients (1:1) to 5 months’ treatment with CPAP plus usual care (CPAP, n = 55) or usual care alone (control, n = 54). The outcome assessment was blinded. The planned primary outcome was the difference between CPAP treatment and control groups in change of AF burden (percentage of time in AF) as measured by implantable loop recorder. Measurements and Main Results: A total of 579 patients with paroxysmal AF had respiratory polygraphy, of whom 244 (42%) had moderate to severe SA. Of these, 158 (65%) participated in the CPAP run-in period, of whom 39 (25%) patients did not tolerate the treatment. A total of 108 patients were available for the primary analysis. The mean time in AF decreased from 5.6% at baseline to 4.1% during the last 3 months of CPAP intervention and from 5.0% to 4.3% in the control group. The adjusted between-group difference at follow-up was −0.63 (95% confidence interval, −2.55 to 1.30) percentage points (P = 0.52). Seven serious adverse events (13%) occurred in the CPAP group, and two (4%) occurred in the control group. Conclusions: In patients with paroxysmal AF and SA, treatment with CPAP did not result in a statistically significant reduction in the burden of AF.Clinical trial registered with www.clinicaltrials.gov (NCT02727192).

• Øverland, Britt; Berdal, Hanne & Akre, Harriet (2021). Surgery for obstructive sleep apnea in young children: Outcome evaluated by polysomnograhy and quality of life. International Journal of Pediatric Otorhinolaryngology. ISSN 0165-5876. 142:110609, p. 1–6. doi: 10.1016/j.ijporl.2021.110609.
• Hui, David; Johansen, Edvard; Akre, Harriet; Osnes, Terje & Dheyauldeen, Sinan (2020). Øre-nese-hals-leger og sars-CoV-2-viruset. Tidsskrift for Den norske legeforening. ISSN 0029-2001. 140(10). doi: 10.4045/tidsskr.20.0423.
• Kristiansen, Stein; Traaen, Gunn Marit; Øverland, Britt; Plagemann, Thomas Peter; Gullestad, Lars & Akre, Harriet [Show all 13 contributors for this article] (2020). Comparing manual and automatic scoring of sleep monitoring data from portable polygraphy. Journal of Sleep Research. ISSN 0962-1105. doi: 10.1111/jsr.13036. Full text in Research Archive
• Øverland, Britt; Berdal, Hanne & Akre, Harriet (2020). Correlations between disease-specific quality of life and polysomnographic findings in children with obstructive sleep apnea. International Journal of Pediatric Otorhinolaryngology. ISSN 0165-5876. 134. doi: 10.1016/j.ijporl.2020.110077.
• Traaen, Gunn Marit; Øverland, Britt; Aakerøy, Lars; Hunt, Tove Elizabeth Frances; Bendz, Christina & Leif Magne, Sande [Show all 13 contributors for this article] (2019). Prevalence, risk factors, and type of sleep apnea in patients with paroxysmal atrial fibrillation. International journal of cardiology: Heart and Vasculature (IJCHA). ISSN 2352-9067. doi: 10.1016/j.ijcha.2019.100447. Full text in Research Archive
• Øverland, Britt; Berdal, Hanne & Akre, Harriet (2019). Obstructive sleep apnea in 2–6 year old children referred for adenotonsillectomy. European Archives of Oto-Rhino-Laryngology. ISSN 0937-4477. 276(7), p. 2097–2104. doi: 10.1007/s00405-019-05362-3.
• Traaen, Gunn Marit; Aakerøy, Lars; Hunt, Tove Elisabeth F.; Øverland, Britt; Lyseggen, Erik & Aukrust, Pål [Show all 16 contributors for this article] (2018). Treatment of sleep apnea in patients with paroxysmal atrial fibrillation: design and rationale of a randomized controlled trial. Scandinavian Cardiovascular Journal. ISSN 1401-7431. 52(6), p. 372–377. doi: 10.1080/14017431.2019.1567933. Full text in Research Archive
• Omland, Turid; Akre, Harriet; Lie, Kathrine; Jebsen, Peter Wilhelm; Sandvik, Leiv & Brøndbo, Kjell (2014). Risk factors for aggressive recurrent respiratory papillomatosis in adults and juveniles. PLOS ONE. ISSN 1932-6203. 9(11). doi: 10.1371/journal.pone.0113584.
• Herrscher, Tobias Erik ; Akre , Harriet ; Øverland, Britt; Sandvik, Leiv & Westheim, Arne (2014). Clinical predictors of sleep apnoea in heart failure outpatients. International Journal of Clinical Practice. ISSN 1368-5031. 68(6), p. 725–730. doi: 10.1111/ijcp.12396.
• Austeng, Marit Erna; Øverland, Britt; Kvaerner, Kari Jorunn; Andersson, Els-Marie; Axelsson, Stefan & Abdelnoor, Michael [Show all 7 contributors for this article] (2014). Obstructive sleep apnea in younger school children with Down syndrome. International Journal of Pediatric Otorhinolaryngology. ISSN 0165-5876. 78(7), p. 1026–1029. doi: 10.1016/j.ijporl.2014.03.030.
• Åsten , Pamela ; Akre , Harriet & Persson, Christina (2014). Associations between speach features and phenotypic severity in Treacher Collins syndrome. BMC Medical Genetics. ISSN 1471-2350. 15:47. doi: 10.1186/1471-2350-15-47.
• Omland, Turid; Lie, Kathrine; Akre , Harriet ; Sandlie, Lars Eriks; Jebsen, Peter Wilhelm & Sandvik, Leiv [Show all 10 contributors for this article] (2014). Recurrent respiratory papillomatosis: HPV genotypes and risk of high-grade laryngeal neoplasia. PLOS ONE. ISSN 1932-6203. 9(6). doi: 10.1371/journal.pone.0099114.
• Herrscher, Tobias Erik ; Øverland, Britt; Sandvik, Leiv; Westheim, Arne & Akre , Harriet (2014). High cardiovascular risk profile in patients with sleep apnea. The Laryngoscope. ISSN 0023-852X. 124(1), p. 306–310. doi: 10.1002/lary.24304.
• Andersson, Els-Marie; Axelsson, Stefan; Austeng, Marit Erna; Øverland, Britt; Valen, Ingrid Ekroll & Jensen, Terese Agustin [Show all 7 contributors for this article] (2014). Bilateral hypodontia is more common than unilateral hypodontia in children with Down syndrome: A prospective population-based study. European Journal of Orthodontics. ISSN 0141-5387. 36(4), p. 414–418. doi: 10.1093/ejo/cjt063.
• Austeng, Marit Erna; Akre , Harriet ; Øverland, Britt; Abdelnoor, Michael; Falkenberg, Eva-Signe & Kvaerner, Kari Jorunn (2013). Otitis media with effusion in children with in Down syndrome. International Journal of Pediatric Otorhinolaryngology. ISSN 0165-5876. 77(8), p. 1329–1332. doi: 10.1016/j.ijporl.2013.05.027.
• Austeng, Marit Erna; Akre , Harriet ; Falkenberg, Eva-Signe; Øverland, Britt; Abdelnoor, Michael & Kvaerner, Kari Jorunn (2013). Hearing level in children with Down syndrome at the age of eight. Research in Developmental Disabilities. ISSN 0891-4222. 34(7). doi: 10.1016/j.ridd.2013.04.006.
• Geirdal, Amy Østertun; Øverland, Britt; Heimdal, Ketil Riddervold; Storhaug, Kari ; Åsten , Pamela & Akre , Harriet (2013). Association between obstructive sleep apnea and health-related quality of life in individuals affected with Treacher Collins syndrome. European Archives of Oto-Rhino-Laryngology. ISSN 0937-4477. 270(11), p. 2879–2884. doi: 10.1007/s00405-013-2409-0.
• Åsten , Pamela ; Skogedal, Nina ; Nordgarden, Hilde; Axelsson, Stefan; Akre , Harriet & Sjogren, Lotta (2013). Orofacial functions and oral health associated with Treacher Collins syndrome. Acta Odontologica Scandinavica. ISSN 0001-6357. 71(3-4), p. 616–625. doi: 10.3109/00016357.2012.700065.
• Østerhus, Ingvild; Skogedal, Nina ; Akre , Harriet ; Johnsen, Ulf; Nordgarden, Hilde & Åsten , Pamela (2012). Salivary gland pathology as a new finding in Treacher Collins syndrome. American Journal of Medical Genetics. Part A. ISSN 1552-4825. 158A(6), p. 1320–1325. doi: 10.1002/ajmg.a.35331.
• Omland, Turid; Akre , Harriet ; Vårdal, Mari H & Brøndbo, Kjell (2012). Epidemiological aspects of recurrent respiratory papillomatosis: A population-based study. The Laryngoscope. ISSN 0023-852X. 122(7), p. 1595–1599. doi: 10.1002/lary.23327.
• Kristiansen, Håvard Anton; Kvaerner, Kari Jorunn; Akre , Harriet ; Øverland, Britt; Sandvik, Leiv & Russell, Michael Bjørn (2012). Sleep apnoea headache in the general population. Cephalalgia. ISSN 0333-1024. 32(6), p. 451–458. doi: 10.1177/0333102411431900.
• Øverland, Britt; Akre , Harriet ; Berdal, Hanne & Skatvedt, Olav (2012). Sleep-relating groaning: Prevalence and characteristics in a cohort of patients with suspected obstructive sleep apnea. Acta Oto-Laryngologica. ISSN 0001-6489. 132(1), p. 90–95. doi: 10.3109/00016489.2011.624119.
• Akre , Harriet ; Øverland, Britt; Åsten , Pamela ; Heimdal, Ketil Riddervold & Skogedal, Nina (2012). Obstructive sleep apnea in Treacher Collins syndrome. European Archives of Oto-Rhino-Laryngology. ISSN 0937-4477. 269(1), p. 331–337. doi: 10.1007/s00405-011-1649-0.
• Kristiansen, Håvard Anton; Kvaerner, Kari Jorunn; Akre , Harriet ; Øverland, Britt & Russell, Michael Bjørn (2011). Tension-type headache and sleep apnea in the general population. The Journal of Headache and Pain. ISSN 1129-2369. 12(1), p. 63–69. doi: 10.1007/s10194-010-0265-5.
• Kristiansen, Håvard Anton; Kvaerner, Kari Jorunn; Akre , Harriet ; Øverland, Britt & Russell, Michael Bjørn (2011). Migraine and sleep apnea in the general population. The Journal of Headache and Pain. ISSN 1129-2369. 12(1), p. 55–61. doi: 10.1007/s10194-010-0268-2.
• Herrscher, Tobias Erik ; Akre , Harriet ; Øverland, Britt; Sandvik, Leiv & Westheim, Arne (2011). High Prevalence of Sleep Apnea in Heart Failure Outpatients: Even in Patients With Preserved Systolic Function. Journal of Cardiac Failure. ISSN 1071-9164. 17(5), p. 420–425. doi: 10.1016/j.cardfail.2011.01.013.
• Kristiansen, Håvard Anton; Kvaerner, Kari Jorunn; Akre , Harriet ; Øverland, Britt & Russell, Michael Bjørn (2010). Tension-type headache and sleep apnea in the general population. The Journal of Headache and Pain. ISSN 1129-2369. doi: 10.1007/s10194-010-0265-5.
• Kristiansen, Håvard Anton; Kvaerner, Kari Jorunn; Akre , Harriet ; Øverland, Britt & Russell, Michael Bjørn (2010). Migraine and sleep apnea in the general population. The Journal of Headache and Pain. ISSN 1129-2369. doi: 10.1007/s10194-010-0268-2.
• Akre , Harriet ; Øverland, Britt & Skatvedt, Olav (2009). Respirasjonsforstyrrelser under søvn. Tidsskrift for Den norske legeforening. ISSN 0029-2001. 129(17), p. 1762–1765. doi: 10.4045/tidsskr.08.0497.

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• Traaen, Gunn Marit; Akre, Harriet; Loennechen, Jan Pål & Gullestad, Lars (2022). Reply to Lalonde et al. American Journal of Respiratory and Critical Care Medicine. ISSN 1073-449X. 205(9), p. 1129–1130. doi: 10.1164/rccm.202112-2738LE.
• Øverland, Britt; Berdal, Hanne & Akre, Harriet (2018). High prevalence of OSA in children referred for adenotonsillectomy.
• Russell, Michael Bjørn; Kvaerner, Kari Jorunn; Akre , Harriet ; Øverland, Britt & Kristiansen, Håvard Anton (2009). A population-based study of tension-type headache in obstructive sleep apnea. The Akershus sleep apnea project. Cephalalgia. ISSN 0333-1024. 29, p. 159–159.

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