Design and Implementation of a Multifunction Wearable Device to Monitor Sleep Physiological Signals

Abstract

<jats:p>We present a wearable device built on an Adafruit Circuit Playground Express (CPE) board and integrated with a photoplethysmographic (PPG) optical sensor for heart rate monitoring and multiple embedded sensors for medical applications—in particular, sleep physiological signal monitoring. Our device is portable and lightweight. Due to the microcontroller unit (MCU)-based architecture of the proposed device, it is scalable and flexible. Thus, with the addition of different plug-and-play sensors, it can be used in many applications in different fields. The innovation introduced in this study is that with additional sensors, we can determine whether there are intermediary variables that can be modified to improve our sleep monitoring algorithm. Additionally, although the proposed device has a relatively low cost, it achieves substantially improved performance compared to the commercially available Philips ActiWatch2 wearable device, which has been approved by the Food and Drug Administration (FDA). To assess the reliability of our device, we compared physiological sleep signals recorded simultaneously from volunteers using both our device and ActiWatch2. Motion and light detection data from our device were shown to be correlated to data simultaneously collected using the ActiWatch2, with correlation coefficients of 0.78 and 0.89, respectively. For 7 days of continuous data collection, there was only one instance of a false positive, in which our device detected a sleep interval, while the ActiWatch2 did not. The most important aspect of our research is the use of an open architecture. At the hardware level, general purpose input/output (GPIO), serial peripheral interface (SPI), integrated circuit (I2C), and universal asynchronous receiver-transmitter (UART) standards were used. At the software level, an object-oriented programming methodology was used to develop the system. Because the use of plug-and-play sensors is associated with the risk of adverse outcomes, such as system instability, this study heavily relied on object-oriented programming. Object-oriented programming improves system stability when hardware components are replaced or upgraded, allowing us to change the original system components at a low cost. Therefore, our device is easily scalable and has low commercialization costs. The proposed wearable device can facilitate the long-term tracking of physiological signals in sleep monitoring and related research. The open architecture of our device facilitates collaboration and allows other researchers to adapt our device for use in their own research, which is the main characteristic and contribution of this study.</jats:p>

Recent advances in wearable sensors and portable electronics for sleep monitoring

“…Figure 6 C shows an example of a wristband-type device that utilizes accelerometer-based ACT. The accelerometer also incorporates an ambient light sensor, temperature sensor, sound sensor, and finger-PPG sensor ( Liao et al., 2020 ). To evaluate the sleep-wake pattern, the device mainly looks at the movement and strength of ambient light.…”

“… (D) Plots showing measured activity, ambient light level, and detected sleep interval throughout the seven days of use. Reproduced with permission, from ref ( Liao et al., 2020 ), Copyright 2020, MDPI. (E) Low-power, flexible wearable device with an accelerometer to monitor infants' sleep posture and alert caregivers when a prone position is detected.…”

“… (D) Plots showing measured activity, ambient light level, and detected sleep interval throughout the seven days of use. Reproduced with permission, from ref ( Liao et al., 2020 ), Copyright 2020, MDPI. …”

Analysis of Data from Wearable Sensors for Sleep Quality Estimation and Prediction Using Deep Learning

“…Rofouei et al [39] propose a wearable neck cuff tool to monitor physiological data in real time. Recently, Liao et al [40] present a wearable portable light weight, scalable and flexible wearable device to monitor sleep physiological signals. RestEaZe, a multi-sensor ankle band that captures leg move- 1 National Sleep Research Resource: www.sleepdata.org.…”

Continuous monitoring of Physiological parameters using PPG

“…Several researchers have developed a remote health monitoring system using wireless sensors technology and IoT to monitor several patients at a time (44)(45)(46) . Blood pressure was estimated using pulse arrival time of PPG signal (47) and machine learning techniques (48) .…”