Sensors based Smart Pillow for Quality Sleep Detection

Sleep quality is a vital aspect of human health and well-being, with increasing interest in the development of non-invasive, cost-effective methods for monitoring sleep. Traditional methods of sleep analysis, such as polysomnography, are both costly and invasive, which has led to the growing demand for wearable and non-wearable alternatives. In this paper, we propose a smart pillow system designed to monitor sleep quality through the integration of Force Sensing Resistor pressure sensors and NTC thermistors. The system uses an ESP32 microcontroller to process pressure and temperature data and predict sleep stages. Results from a series of experiments show that the system can accurately detect sleep quality and provide real-time feedback through an Arduino IDE platform on a connected laptop. This paper presents the detailed design, methodology, results, and future implications for this system as a non-invasive, low-cost sleep tracking solution.

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Publication Details

Published
2025-04-07
DOI
https://doi.org/10.1109/ictmim65579.2025.10987932
Primary Topic
IoT-based Smart Home Systems
Type
article
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article

Sensors based Smart Pillow for Quality Sleep Detection

P. Subha Hency Jose, G. Gifta, N.A. Sam', S Pramod
IoT-based Smart Home Systems
article

Sensors based Smart Pillow for Quality Sleep Detection

P. Subha Hency Jose, G. Gifta, N.A. Sam', S Pramod
article en

Abstract

Sleep quality is a vital aspect of human health and well-being, with increasing interest in the development of non-invasive, cost-effective methods for monitoring sleep. Traditional methods of sleep analysis, such as polysomnography, are both costly and invasive, which has led to the growing demand for wearable and non-wearable alternatives. In this paper, we propose a smart pillow system designed to monitor sleep quality through the integration of Force Sensing Resistor pressure sensors and NTC thermistors. The system uses an ESP32 microcontroller to process pressure and temperature data and predict sleep stages. Results from a series of experiments show that the system can accurately detect sleep quality and provide real-time feedback through an Arduino IDE platform on a connected laptop. This paper presents the detailed design, methodology, results, and future implications for this system as a non-invasive, low-cost sleep tracking solution.

Karunya University (IN)
Affordable and clean energy
Openalex Percentile: Top 92%
IoT-based Smart Home Systems
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