Sleep quality is a key indicator of an individual's health status, particularly for vulnerable or elderly subjects and those with pre-existing medical conditions. Sensors are used to monitor various parameters, including respiratory rate and heart rate. This study aims to perform the static calibration of a sleep band equipped with piezoresistive pressure sensors. The sensor is low-cost, low-power, and non-invasive. Static calibration was carried out using a device with established metrological characteristics—the BioHarness 3.0—as a reference. A preliminary qualitative test was conducted in which the sleep band was divided into several equidistant points to determine the optimal positioning for subsequent tests. Subsequently, experimental tests were performed to acquire data from two different sensors: the sleep band and the BioHarness 3.0. The measurement protocol involved two stages: the first stage allowed for sensor stabilization to ensure accurate data acquisition, while the second stage required the subject to lie in a supine position. The tests were conducted in the Living Lab's bedroom environment, with both sensors recording data simultaneously. The timestamps from the tests were synchronized by trimming the initial stabilization phase; finally, automated processing was performed using Python to create a unified dataset of respiratory and heart rate readings from both the sleep band and the BioHarness 3.0. Based on the methodological analysis, the expanded combined uncertainty, Pearson correlation coefficient, and R² coefficient were calculated for both respiratory rate and heart rate. These results indicate that the sleep band's readings do not yet provide a sufficiently reliable solution for everyday use, highlighting very low accuracy. This study lays the groundwork for future developments, including increasing the number of test subjects and monitoring during extended overnight tests.
La qualità del sonno rappresenta un indicatore fondamentale per lo stato di salute di un individuo, in particolare di soggetti fragili, anziani e con patologie pregresse. Vengono usati sensori per il rilevamento di vari parametri, tra cui frequenza respiratoria e frequenza cardiaca. Il presente studio ha come obiettivo la taratura statica di una sleep band che è dotata di sensori piezoresistivi di pressione. Il sensore è low cost, low power e non invasivo. La taratura statica è stata effettuata usando come riferimento uno strumento già metrologicamente caratterizzato: il BioHarness 3.0. Preliminarmente è stato effettuato un test qualitativo in cui la sleep band è stata divisa in più punti equidistanti tra di loro affinché si potesse capire quale posizione adottare per i successivi test. Successivamente, sono stati condotti test sperimentali nei quali sono stati acquisiti dati provenienti da due sensori diversi: la sleep band e il BioHarness 3.0. Il protocollo di misura adottato prevedeva due stazioni: la prima stazione serviva per la stabilizzazione del sensore affinché potesse correttamente rilevare i dati, e la seconda stazione prevedeva che il soggetto si distendesse in posizione supina. Le prove sono state condotte nell’ambiente camera da letto del Living Lab, dove entrambi i sensori acquisivano simultaneamente. I timestamp delle prove condotte sono stati sincronizzati, tagliando la prima stazione di stabilizzazione e infine in Python vi è stata l’elaborazione automatizzata per la creazione del dataset unificato di frequenza respiratoria e frequenza cardiaca della sleep band e del BioHarness 3.0. Dall’analisi condotta a livello metodologico sono stati calcolati l’incertezza combinata estesa, il coefficiente di Pearson ed il coefficiente R^(2 )sia per la frequenza respiratoria che per la frequenza cardiaca. Questi risultati indicano che i valori della sleep band rappresentano una soluzione non ancora sufficiente per un utilizzo affidabile nella quotidianità sottolineando un’accuratezza molto bassa. Questo studio pone le basi per sviluppi futuri che riguardano l’ampliamento del numero di soggetti testati ed inoltre il monitoraggio durante test notturni prolungati.
CALIBRAZIONE DI UN SENSORE PER IL MONITORAGGIO DELLA QUALITÀ DEL SONNO
BONANNI PARAGALLO, GIUSEPPE
2025/2026
Abstract
Sleep quality is a key indicator of an individual's health status, particularly for vulnerable or elderly subjects and those with pre-existing medical conditions. Sensors are used to monitor various parameters, including respiratory rate and heart rate. This study aims to perform the static calibration of a sleep band equipped with piezoresistive pressure sensors. The sensor is low-cost, low-power, and non-invasive. Static calibration was carried out using a device with established metrological characteristics—the BioHarness 3.0—as a reference. A preliminary qualitative test was conducted in which the sleep band was divided into several equidistant points to determine the optimal positioning for subsequent tests. Subsequently, experimental tests were performed to acquire data from two different sensors: the sleep band and the BioHarness 3.0. The measurement protocol involved two stages: the first stage allowed for sensor stabilization to ensure accurate data acquisition, while the second stage required the subject to lie in a supine position. The tests were conducted in the Living Lab's bedroom environment, with both sensors recording data simultaneously. The timestamps from the tests were synchronized by trimming the initial stabilization phase; finally, automated processing was performed using Python to create a unified dataset of respiratory and heart rate readings from both the sleep band and the BioHarness 3.0. Based on the methodological analysis, the expanded combined uncertainty, Pearson correlation coefficient, and R² coefficient were calculated for both respiratory rate and heart rate. These results indicate that the sleep band's readings do not yet provide a sufficiently reliable solution for everyday use, highlighting very low accuracy. This study lays the groundwork for future developments, including increasing the number of test subjects and monitoring during extended overnight tests.| File | Dimensione | Formato | |
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tesi BONANNI PARAGALLO-3.pdf
embargo fino al 16/04/2028
Descrizione: Calibrazione di un sensore per il monitoraggio della qualità del sonno
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2.01 MB | Adobe PDF |
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https://hdl.handle.net/20.500.12075/29398