Emfit-patjalla mitatun unihäiriön vaikutus suoriutumiseen vireystilakokeessa

Tavoitteet:Tutkia unipolygrafiasta saatujen suureiden ja Emfit-patjalla mitattujen unihäiriöiden vaikutusta päiväaikaiseen suoriutumiseen vireystilakokeessa. Menetelmät: Aineisto koostui 15 koehenkilöstä, joista jokaisella oli jokin unenaikainen hengityshäiriö, ja jotka olivat suorittaneet Cognispeed-vireystilakokeen sekä illalla että aamulla. Yön potilaat nukkuivat Emfit-liikeanturipatjalla, ja heille tehtiin laaja unipolygrafia, joista saadut suureet kirjattiin ylös. Tulokset: Yölliset Emfit-patjalla mitatut periodiset obstruktiohäiriöt (OP1-OP3 –ilmiöt) vaikuttivat aamun reaktioaikaan hidastavasti. Reaktioaikaa hidasti myös S2- unen määrän lisääntyminen, tehokas uni ja uniajan pidentyminen. Reaktioaikoja nopeuttivat S1-unen lisääntyminen ja unenaikaiset aivokuoren lyhyet havahtumisreaktiot. Vireystilakokeen pisteet näyttivät olleen parempia aamulla mikäli unenaikainen apnea ja hypopnea lisääntyi, happisaturaatio laski tai obstruktiohäiriöiden osuus nousi. Pistesuoriutumista huononsi parempi vähimmäishappisaturaatio sekä kokonaisuniajan lisääntyminen. Päätelmä: Unenaikaiset obstruktiohäiriöt tuntuvat aiheuttavan hitaampaa suoriutumista vireystilakokeessa, mutta pinnallisemmin nukutun yön jälkeen päätöksentekoaika näyttää nopeutuvan.Asiasanat: unipolygrafia, uniapnea, vigilance, tarkkaavaisuus, aikuine

Modelling of sleep behaviors of patients with mood disorders

Sleep is an essential function of the human body. It has a restorative effect on both physical and mental health functions. Short and long-term consequences of sleep disruption include changes to stress response, anxiety, and depression, as well as deficiencies in memory, cognition, and performance. Several methods have been developed to assess sleep. While polysomnography is considered the golden standard of sleep assessment, researchers have focused on alternate ways of tracking sleep using non-intrusive and less costly methods such as actigraphy. Some studies suggested that screen activity from smartphones can be an indicator of the sleep and wake states of an individual as smartphone usage increased drastically in the last decade. Mood disorders are mental health conditions that disrupt the emotional state of individuals. Sudden and extreme mood changes interfere with the patients’ daily rhythm in many ways, including their sleep behavior. Timely diagnosis of the severity of mood disorders plays a critical role in their treatment process. Previous research shows strong links between decreased sleep quality in patients suffering from mood disorders. This thesis uses the data from a digital phenotyping study, Mobile Monitoring of Mood (MoMo-Mood), to analyze the sleep behaviors of patients with mood disorders using some sleep parameters. In addition, a predictive model is built to investigate the severity of depression using the information tracked via actigraph and bed sensor. Lastly, the perceived sleep quality from questionnaires is compared with the data tracked by these sensors to evaluate the differences in the three different groups of patients: bipolar disorder, borderline personality disorder, and major depressive disorder

Methods for Doppler Radar Monitoring of Physiological Signals

Unobtrusive health monitoring includes advantages such as long-term monitoring of rarely occurring conditions or of slow changes in health, at reasonable costs. In addition, the preparation of electrodes or other sensors is not needed. Currently, the main limitation of remote patient monitoring is not in the existing communication infrastructure but the lack of reliable, easy-to-use, and well-studied sensors.The aim of this thesis was to develop methods for monitoring cardiac and respiratory activity with microwave continuous wave (CW) Doppler radar. When considering cardiac and respiration monitoring, the heart and respiration rates are often the first monitored parameters. The motivation of this thesis, however, is to measure not only rate-related parameters but also the cardiac and respiratory waveforms, including the chest wall displacement information.This dissertation thoroughly explores the signal processing methods for accurate chest wall displacement measurement with a radar sensor. The sensor prototype and measurement setup choices are reported. The contributions of this dissertation encompass an I/Q imbalance estimation method and a nonlinear demodulation method for a quadrature radar sensor. Unlike the previous imbalance estimation methods, the proposed method does not require the use of laboratory equipment. The proposed nonlinear demodulation method, on the other hand, is shown to be more accurate than other methods in low-noise cases. In addition, the separation of the cardiac and respiratory components with independent component analysis (ICA) is discussed. The developed methods were validated with simulations and with simplified measurement setups in an office environment. The performance of the nonlinear demodulation method was also studied with three patients for sleep-time respiration monitoring. This is the first time that whole-night measurements have been analyzed with the method in an uncontrolled environment. Data synchronization between the radar sensor and a commercial polysomnographic (PSG) device was assured with a developed infrared (IR) link, which is reported as a side result.The developed methods enable the extraction of more useful information from a radar sensor and extend its application. This brings Doppler radar sensors one step closer to large-scale commercial use for a wide range of applications, including home health monitoring, sleep-time respiration monitoring, and measuring gating signals for medical imaging

Obstructive Sleep Apnea Syndrome: Pathogenetic Aspects and Treatment

Almost twenty years ago obstmctive sleep apnea was considered to be a medical curiosity that was of little importance, and snoring was merely the subject of humor than one of serious investigation. Although the clinical manifestations of sleep apnea syndrome have been described as early as in the fat boy Joe in Charles Dickens Pickwick Papers, it was Gastaut in 1965 who provided the first detailed polygraphic description of the manifestations of this sleep related breathing disorder. Since that date countless studies have been perfornled and published, concerning all possible aspects of sleep apnea syndrome. Epidemiological and clinical research revealed that the obshuctive sleep apnea syndrome may be considered a major public health problem and that the sequelae of the syndrome may have devastating consequences for the lives of those affected, but the long telm sequelae of obstmctive sleep apnea need fmiher elucidation in well designed studies. This chapter provides a review of prevalence, pathogenesis, natural history, symptomatology, diagnosis and treatment of Obstmctive Sleep Apnea Syndrome (OSAS). First a brief description of the spectnnll of sleep related breathing disorders is given

Detection of sleep-disordered breating with Pressure Bed Sensor.

reserved8A Pressure Bed Sensor (PBS) can offer an unobtrusive method for sleep monitoring. This study focuses on the detection of the sleep related breathing disorders using a PBS in comparison to the methods used in a sleep laboratory. A newly developed PCA modeling approach for the eight sensor signals of the PBS is evaluated using the Reduced Respiratory Amplitude Index (RRAI) as a central measure. The method computes the respiration amplitude with the Hilbert transform, and then detects the events based on a 20% amplitude reduction from the baseline signal. A similar calculation was used for the sleep laboratory RIP measurements, and both PBS and RIP were compared against the reference based on the nasal flow signal. In the reference RRAI method, the respiratory-disordered events were obtained using RemLogic respiration analyzer to detect over 50% amplitude reduction in the nasal respiratory flow, but removing the RemLogic standard hypopnea event associations on the oxygen desaturation events and the sleep arousals. The movement artifacts were automatically detected based on the movement activity signal of the PBS. Twenty-five (25) out of 28 patients were finally analysed. On average 87% of a night measurement has been covered by the system. The correlation coefficient was 0.92 between the PBS and the reference RRAI, and the performance of the PBS was similar with the RIP belts. Classifying the severity of the sleep related breathing by dividing RRAI in groups according to the severity criteria, the sensitivity was 92% and the specificity was 70% for the PBS. The results suggest that PBS recording can provide an easy and un-obstructive alternative method for the detection of the sleep disordered breathing and thus has a great promise for the home monitoring.Guerrero G.; Kortelainen J. M.; Palacios E.; Bianchi A. M.; Tacchino G.; Tenhunen M.; Mendez M. O.; van Gils M.Guerrero, G.; Kortelainen, J. M.; Palacios, E.; Bianchi, ANNA MARIA; Tacchino, Giulia; Tenhunen, M.; Mendez, M. O.; van Gils, M