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by Keyword: mHealth


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Castillo-Escario, Y., Ferrer-Lluis, I., Montserrat, J. M., Jané, R., (2019). Entropy analysis of acoustic signals recorded with a smartphone for detecting apneas and hypopneas: A comparison with a commercial system for home sleep apnea diagnosis IEEE Access 7, 128224-128241

Obstructive sleep apnea (OSA) is a prevalent disease, but most patients remain undiagnosed and untreated. Here we propose analyzing smartphone audio signals for screening OSA patients at home. Our objectives were to: (1) develop an algorithm for detecting silence events and classifying them into apneas or hypopneas; (2) evaluate the performance of this system; and (3) compare the information provided with a type 3 portable sleep monitor, based mainly on nasal airflow. Overnight signals were acquired simultaneously by both systems in 13 subjects (3 healthy subjects and 10 OSA patients). The sample entropy of audio signals was used to identify apnea/hypopnea events. The apnea-hypopnea indices predicted by the two systems presented a very high degree of concordance and the smartphone correctly detected and stratified all the OSA patients. An event-by-event comparison demonstrated good agreement between silence events and apnea/hypopnea events in the reference system (Sensitivity = 76%, Positive Predictive Value = 82%). Most apneas were detected (89%), but not so many hypopneas (61%). We observed that many hypopneas were accompanied by snoring, so there was no sound reduction. The apnea/hypopnea classification accuracy was 70%, but most discrepancies resulted from the inability of the nasal cannula of the reference device to record oral breathing. We provided a spectral characterization of oral and nasal breathing to correct this effect, and the classification accuracy increased to 82%. This novel knowledge from acoustic signals may be of great interest for clinical practice to develop new non-invasive techniques for screening and monitoring OSA patients at home.

Keywords: Sleep apnea, Acoustics, Monitoring, Entropy, Sensors, Microphones, Acoustics, Biomedical signal processing, mHealth, Monitoring, Sleep apnea, Smartphone


Isetta, V., Torres, M., González, K., Ruiz, C., Dalmases, M., Embid, C., Navajas, D., Farré, R., Montserrat, J. M., (2017). A New mHealth application to support treatment of sleep apnoea patients Journal of Telemedicine and Telecare , 23, (1), 14-18

Introduction: Continuous positive airway pressure (CPAP) is the first-choice treatment for obstructive sleep apnoea (OSA), but adherence is frequently suboptimal. Innovative, patient-centred interventions are, therefore, needed to enhance compliance. Due to its low cost and ubiquity, mobile health (mHealth) technology seems particularly suited for this purpose. We endeavoured to develop an mHealth application called “APPnea,” aimed at promoting patient self-monitoring of CPAP treatment. We then assessed the feasibility and acceptability of APPnea in a group of OSA patients. Methods: Consecutive OSA patients used APPnea for six weeks. APPnea gave patients daily reminders to answer three questions about their OSA treatment (CPAP use, physical activity, and diet) and prompted them to upload their body weight weekly. Answers were saved to a secure server for further analysis. After completing the study, patients gave their anonymous opinions about APPnea. Results: We enrolled 60 patients with OSA receiving CPAP treatment. The mean age was 56 ± 10 years and the apnoea–hypopnea index was 47 ± 25 events/hour. In total, 63% of participants completed the daily questionnaire for more than 66% of the study period. Objective CPAP compliance was generally high (5.3 ± 1.6 hours/night). In a subset of 38 patients naïve to CPAP, those who used APPnea regularly had significantly higher CPAP compliance. Satisfaction levels were high for the majority of users. Conclusion: This mHealth intervention is not only feasible but also satisfactory to patients. Although larger randomized trials and cost-effectiveness studies should be performed, this study shows that APPnea could promote participation and improve compliance among patients with OSA, thereby improving outcomes.

Keywords: CPAP, MHealth, Sleep apnoea, Smartphone application