Citation: Pranjoto, H.; Miyata, A.F.;
Agustine, L. Combining 10 Matrix
Pressure Sensor to Read Human
Body’s Pressure in Sleeping Position
in Relation with Decubitus Patients. J.
Sens. Actuator Netw. 2022, 11, 16.
https://doi.org/10.3390/jsan11010016
Academic Editors: Alvaro
Araujo Pinto and Hacene Fouchal
Received: 11 January 2022
Accepted: 22 February 2022
Published: 25 February 2022
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Journal of
Actuator Networks
Sensor and
Article
Combining 10 Matrix Pressure Sensor to Read Human Body’s
Pressure in Sleeping Position in Relation with
Decubitus Patients
Hartono Pranjoto * , Andrew Febrian Miyata and Lanny Agustine
Department of Electrical Engineering, Faculty of Engineering, Widya Mandala Surabaya Catholic University (WMSCU),
Surabaya 60114, Indonesia; andrew.m@ukwms.ac.id (A.F.M.); lanny.agustine@ukwms.ac.id (L.A.)
* Correspondence: pranjoto@ukwms.ac.id
Abstract:
This work uses piezoresistive matrix pressure sensors to map the human body’s pressure
profile in a sleeping position. This study aims to detect the area with the highest pressure, to visualize
the pressure profile into a heatmap, and to reduce decubitus by alerting the subject to changes in
position. This research combines ten matrix pressure sensors to read a larger area. This work uses
a Raspberry Pi 4 Model B with 8 GB memory as the data processor, and every sensor sheet uses
ATMEGA 2560 as the sensor controller for data acquisition. Sensor calibration is necessary because
each output must have the same value for the same weight value; the accuracy between different
sensors is around 95%. After the calibration process, the output data must be smoothed to make
visual representations more distinguishable. The areas with the highest pressure are the heel, tailbone,
back, and head. When the subject’s weight increases, pressure on the tailbone and back increases,
but that on the heel and head does not. The results of this research can be used to monitor people’s
sleeping positions so that they can reduce the risk of decubitus.
Keywords: decubitus; piezoresistance; matrix pressure sensor; monitoring; heatmap
1. Introduction
Matrix pressure sensors are common for robotic skin and biological sensing. Several
mechanisms are applied to pressure sensors, namely, organic field transistors (OFET) [
1
],
piezoresistance [
2
], piezoelectricity [
3
], and capacitors [
4
]. In this paper, the matrix pressure
sensor uses piezoresistance with a pressure range of 0–20 kPa. Sensors were used to
map the pressure of human body areas, and were mainly tested on human subjects in a
sleeping position.
A bedridden subject with a high risk of decubitus lay on the sensor sheets, and then the
system mapped body pressure [
5
]. Decubitus occurs because there is continuous pressure
on one area of the body [
6
]. Decubitus in immobilized patients in developing countries
is prevented by manually moving the patient’s body position at certain time intervals [
7
].
This method is still widely used today. Improvements in the technique and technologies
developed to improve the quality of patient care, especially in the economic aspect, make it
less expensive and easy to manufacture so more patients in need of this medical help can
use them [
8
–
10
]. Some related studies have focused on moving the patient continuously
using airbags [
11
]; however, this paper focuses on pressure monitoring. By monitoring
pressure rather than moving the patient continuously, we only move the patient when
needed so less disturbance occurs. Monitoring patients can also be a fail-safe method
by which to indicate if an airbag cannot move a given pressure point. This paper is a
continuation of research into graphical pressure mapping. It uses a single sensor with a
sensing area 32
×
37.5 cm
2
and can detect as many as 2288 points [
12
]. This paper will
discuss methods combining ten sensors with different sensor controllers using USB. There
are ten collective sheets of sensors, creating a surface which is capable of measuring the
J. Sens. Actuator Netw. 2022, 11, 16. https://doi.org/10.3390/jsan11010016 https://www.mdpi.com/journal/jsan
