Väitös (informaatio- ja viestintäteknologia): MSc Fatemeh Sarhaddi
Aika
10.1.2024 klo 12.00 - 16.00
MSc Fatemeh Sarhaddi esittää väitöskirjansa ”Continuous IoT-based maternal monitoring: system design, evaluation, opportunities, and challenges” julkisesti tarkastettavaksi Turun yliopistossa perjantaina 10.01.2024 klo 12.00 (Turun yliopisto, Agora, XXII-sali, Turku).
Vastaväittäjänä toimii apulaisprofessori Frida Sandberg (Lundin yliopisto, Ruotsi) ja kustoksena professori Pasi Liljeberg (Turun yliopisto). Tilaisuus on englanninkielinen. Väitöksen alana on informaatio- ja viestintäteknologia.
Väitöskirja yliopiston julkaisuarkistossa: https://urn.fi/URN:ISBN:978-951-29-9582-0
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Tiivistelmä väitöstutkimuksesta:
This thesis presents a long-term IoT-based maternal monitoring system and explores its potential in maternal care. This system continuously provides maternal health monitoring services, such as stress monitoring, sleep monitoring, and physical activity monitoring, in everyday life. We evaluate the system’s feasibility, reliability, and energy efficiency. We also discuss the practical challenges of implementing the system.
We validate the heart rate (HR) and heart rate variability (HRV) parameters collected by the system. In addition, we propose a deep-learning-based method for quality assessment of HR and HRV parameters to discard unreliable data and improve health decisions. We use the system to collect data from 62 pregnant women during pregnancy and three-months postpartum. Then, the reliable HR and HRV parameters are used to track the trends during pregnancy and postpartum.
Finally, we investigate maternal loneliness as a major mental health problem. We develop two predictive models to detect maternal loneliness during late pregnancy and the postpartum period. These models use the objective health parameters passively collected by the system and achieve high performance.
Vastaväittäjänä toimii apulaisprofessori Frida Sandberg (Lundin yliopisto, Ruotsi) ja kustoksena professori Pasi Liljeberg (Turun yliopisto). Tilaisuus on englanninkielinen. Väitöksen alana on informaatio- ja viestintäteknologia.
Väitöskirja yliopiston julkaisuarkistossa: https://urn.fi/URN:ISBN:978-951-29-9582-0
***
Tiivistelmä väitöstutkimuksesta:
This thesis presents a long-term IoT-based maternal monitoring system and explores its potential in maternal care. This system continuously provides maternal health monitoring services, such as stress monitoring, sleep monitoring, and physical activity monitoring, in everyday life. We evaluate the system’s feasibility, reliability, and energy efficiency. We also discuss the practical challenges of implementing the system.
We validate the heart rate (HR) and heart rate variability (HRV) parameters collected by the system. In addition, we propose a deep-learning-based method for quality assessment of HR and HRV parameters to discard unreliable data and improve health decisions. We use the system to collect data from 62 pregnant women during pregnancy and three-months postpartum. Then, the reliable HR and HRV parameters are used to track the trends during pregnancy and postpartum.
Finally, we investigate maternal loneliness as a major mental health problem. We develop two predictive models to detect maternal loneliness during late pregnancy and the postpartum period. These models use the objective health parameters passively collected by the system and achieve high performance.
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