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Supporting Information
Lab-on-Mask for Remote Respiratory Monitoring
Liang Pan‡, Cong Wang‡, Haoran Jin‡, Jie Li, Le Yang, Yuanjin Zheng, Yonggang Wen, Ban Hock Tan, Xian Jun Loh* and Xiaodong Chen*
Supplementary Methods
Fabrication of the embedded sensor
1) PDMS Fabrication: To embed the sensor with soft PDMS, liquid PDMS with the PMDS curing
agent with a ratio of 10:1 were mixed. The mixture was then stirred until it was homogeneous by
using a centrifugal mixer. The mixture was next placed inside a vacuum chamber to eliminate air
bubbles.
2) Embedding sensor: The sensors for HR, BP, SpO2 and T were placed in a mould. A sliver paper
was added on the LED to avoid the influence of PDMS. Next, the degassed PDMS was infused
into the mould, followed by a heat treatment at 60 °C for 12 hours. The embedded sensors were
wired on to the mask with internal MCU and wireless Bluetooth circuit.
Vital signs collected and comparison
For SpO2, a pulse oximeter from ANDON HEALTH Co., LTD. was used for comparison measurements.
We collected the SpO2 from the artery of the index finger of a healthy person under resting state. We
recorded the data every 2 minutes over a period of 10 to 15 minutes. For HR and BP, an electrical
blood pressure monitoring from Omron was used for comparison measurements. Here, we collected
the HR and BP from the artery in the wrist. Similarly, we recorded the relative data at the same time.
To calibrate the temperature of LOM, we measured the forehead temperature as body temperature by
an infrared thermometer. There is a compensation value of ~2.9 °C between the LOM and body
temperature from Figure S3.
Design of circuit
The non-contact LOM mainly integrates three modules: signal-receiving, data processing, and
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Bluetooth modules. The signal-receiving module utilizes near-infrared (880nm) and red light (660nm)
to monitor the optical absorptions of arterial blood; uses green light (550nm) to record pulse waves, and
employs a highly sensitive thermometer to measure the human temperature. These received signals
are sent to an MCU (STM32F103C8T6) via IIC, UART, and unique one-wire communication protocols,
respectively. MCU is responsible for calibrating and analyzing the raw data to extract the oxygen
saturation, blood pressure, heart rate, and temperature information, and then pushing the vital signs into
the Bluetooth module. The wireless Bluetooth (HC-05) broadcasts these vital signs to various
terminals such as mobile phones and PCs. During measuring, MCU not only reads the data sent from
the sensors but also monitors the status of mask-wearing. Once the mask has been re-worn, MCU will
automatically recalibrates the optical properties of tissue and blood to ensure the accuracy of
measurements. Also, it guarantees the LOM can adapt to different individuals and be repeatedly used.
Vital signs visualization and analysis
Aside from the embedded sensors, we also have a mobile application for data visualization and analytics.
The communication protocol between the LOM and smart phone is Bluetooth, which is released in 2004
and widely used in IoT area. For the detailed implementation of our mobile app, firstly we developed
Bluetooth related functions including search, connect and disconnect functions. To better display the
data, on the one hand we display both the values in numbers with certain precisions, and a round
progress bar to intuitively show the status of the measured parameters.
In terms of the data analytics, features such as the warning of abnormal heart rate and blood pressure
would allow users to be notified directly via their phone’s built-in notification. Additionally, these
measured data can be sent to our centralized database of the remote monitoring system for further
analysis by getting machine learning algorithms involved. With a large number of samples, it would
be possible to predict the healthy status of the patients and track their progress. Hence, the remote
monitoring system will benefit the overall progress of defending against respiratory pandemics such as
the COVID-19.
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Figure S1. (a) Details of sensor parts and data processing part of the LOM. For experiments, we used a 9V rechargeable Li-battery with 880 mAh which make the LOM work more than 80 hours. (b) Real-time monitoring of HR, BP, SpO2, and T, through an app of a mobile phone.
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Figure S2. Coefficient of data dispersion, c, of HR (a), SpO2 (b), T (c) and PB (d) based on LOM and different commercial products.
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Figure S3. The temperatures of the interior of the LOM and the forehead. There is a compensation temperature of 2.9 °C between them.
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Figure S6. The temperatures of 10 healthy persons based on the interior temperature of the LOM and forehead temperature measured by IR-T.