Article
Wearable Detection of Trunk Flexions: Capacitive Elastomeric
Sensors Compared to Inertial Sensors
Gabriele Frediani
1
, Leonardo Bocchi
2
, Federica Vannetti
3
, Giovanni Zonfrillo
1
and Federico Carpi
1,3,
*
Citation: Frediani, G.; Bocchi, L.;
Vannetti, F.; Zonfrillo, G.; Carpi, F.
Wearable Detection of Trunk Flexions:
Capacitive Elastomeric Sensors
Compared to Inertial Sensors. Sensors
2021, 21, 5453. https://doi.org/
10.3390/s21165453
Academic Editors: Andrea Mannini,
Clive D’Souza and Pietro Picerno
Received: 25 July 2021
Accepted: 9 August 2021
Published: 12 August 2021
Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims in
published maps and institutional affil-
iations.
Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
1
Department of Industrial Engineering, University of Florence, 50121 Florence, Italy;
gabriele.frediani@unifi.it (G.F.); giovanni.zonfrillo@unifi.it (G.Z.)
2
Department of Information Engineering, University of Florence, 50121 Florence, Italy;
leonardo.bocchi@unifi.it
3
IRCCS Fondazione don Carlo Gnocchi ONLUS, 50143 Florence, Italy; fvannetti@dongnocchi.it
* Correspondence: federico.carpi@unifi.it
Abstract:
Continuous monitoring of flexions of the trunk via wearable sensors could help various
types of workers to reduce risks associated with incorrect postures and movements. Stretchable
piezo-capacitive elastomeric sensors based on dielectric elastomers have recently been described as a
wearable, lightweight and cost-effective technology to monitor human kinematics. Their stretching
causes an increase of capacitance, which can be related to angular movements. Here, we describe
a wearable wireless system to detect flexions of the trunk, based on such sensors. In particular, we
present: (i) a comparison of different calibration strategies for the capacitive sensors, using either
an accelerometer or a gyroscope as an inclinometer; (ii) a comparison of the capacitive sensors’
performance with those of the accelerometer and gyroscope; to that aim, the three types of sensors
were evaluated relative to stereophotogrammetry. Compared to the gyroscope, the capacitive sensors
showed a higher accuracy. Compared to the accelerometer, their performance was lower when
used as quasi-static inclinometers but also higher in case of highly dynamic accelerations. This
makes the capacitive sensors attractive as a complementary, rather than alternative, technology to
inertial sensors.
Keywords: capacitive; elastomer; flexion; sensor; wearable; wireless
1. Introduction
Many types of workers have to deal with tiring, incorrect, and even risky body
postures and movements, which involve excessive and/or repeated flexions of the trunk
while accomplishing duties. This can cause pain and increase the risk of musculoskeletal
injuries, such that the trunk’s flexion is a key variable to assess risks associated with
incorrect and dangerous postures in occupational health management [
1
–
4
]. Therefore, a
continuous monitoring of body flexions could help to adopt corrective measures, especially
to prevent injuries.
The gold standard to measure human body kinematics is represented by stereopho-
togrammetry, which uses external cameras to track the position of markers arranged on
the subject [
5
]. Although this technique has a high accuracy, it is not always applicable to
monitor workers. Indeed, not only does it require bulky, complex-to-use, and expensive
equipment, but it also requires the subject to be confined within an empty space, so as to
enable continuous tracking by the cameras.
Therefore, in order to increase the ease of use and versatility, the ideal sensor should
be fully wearable.
Among conventional wearable technologies available to monitor body motions [
6
], the
most sensitive and most used are inertial measurement units (IMUs), electrogoniometers,
and electromagnetic sensors.
Sensors 2021, 21, 5453. https://doi.org/10.3390/s21165453 https://www.mdpi.com/journal/sensors
