Article
Monitoring Flexions and Torsions of the Trunk via
Gyroscope-Calibrated Capacitive Elastomeric Wearable Sensors
Gabriele Frediani
1
, Federica Vannetti
2
, Leonardo Bocchi
3
, Giovanni Zonfrillo
1
and Federico Carpi
1,2,
*
Citation: Frediani, G.; Vannetti, F.;
Bocchi, L.; Zonfrillo, G.; Carpi, F.
Monitoring Flexions and Torsions of
the Trunk via Gyroscope-Calibrated
Capacitive Elastomeric Wearable
Sensors. Sensors 2021, 21, 6706.
https://doi.org/10.3390/s21206706
Academic Editor: Pietro Picerno
Received: 15 September 2021
Accepted: 4 October 2021
Published: 9 October 2021
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Attribution (CC BY) license (https://
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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
IRCCS Fondazione don Carlo Gnocchi ONLUS, 50143 Florence, Italy; fvannetti@dongnocchi.it
3
Department of Information Engineering, University of Florence, 50121 Florence, Italy;
leonardo.bocchi@unifi.it
* Correspondence: federico.carpi@unifi.it
Abstract:
Reliable, easy-to-use, and cost-effective wearable sensors are desirable for continuous
measurements of flexions and torsions of the trunk, in order to assess risks and prevent injuries
related to body movements in various contexts. Piezo-capacitive stretch sensors, made of dielectric
elastomer membranes coated with compliant electrodes, have recently been described as a wearable,
lightweight and low-cost technology to monitor body kinematics. An increase of their capacitance
upon stretching can be used to sense angular movements. Here, we report on a wearable wireless
system that, using two sensing stripes arranged on shoulder straps, can detect flexions and torsions
of the trunk, following a simple and fast calibration with a conventional tri-axial gyroscope on board.
The piezo-capacitive sensors avoid the errors that would be introduced by continuous sensing with
a gyroscope, due to its typical drift. Relative to stereophotogrammetry (non-wearable standard
system for motion capture), pure flexions and pure torsions could be detected by the piezo-capacitive
sensors with a root mean square error of ~8
◦
and ~12
◦
, respectively, whilst for flexion and torsion
components in compound movements, the error was ~13
◦
and ~15
◦
, respectively.
Keywords: capacitive; elastomer; flexion; torsion; sensor; wearable; wireless
1. Introduction
In order to prevent and assess the risk of musculoskeletal injuries related to body
movements in various contexts, continuous measurements of flexions and torsions of the
human trunk are desirable. Indeed, a variety of jobs expose workers to incorrect and even
risky body postures and movements, characterized by excessive and/or repeated flexions
and/or torsions of the trunk. Accordingly, the movements of the trunk are usually adopted
as key indicators to assess risks in occupational health management [
1
–
4
]. Therefore,
the possibility of continuously monitoring, in a simple way, flexions and torsions of
the trunk could improve health management programs in workplaces. Especially, such
measurements should preferably be obtained via wearable sensors, ideally able to combine
comfort, ease of use, reliability and low cost.
Today, the gold standard to monitor human kinematics is represented by stereopho-
togrammetry, where markers arranged on the subject are tracked by external cameras [
5
].
The high accuracy of this methodology is counterbalanced by the need for bulky, complex-
to-use and expensive equipment, which also requires that the subject is confined within
an empty space, so as to enable continuous tracking by the cameras. As a result, in
several contexts, stereophotogrammetry is not usable, and wearable solutions [
6
] are prefer-
able/necessary. Among them, the most sensitive and most used are inertial measurement
units (IMUs), electrogoniometers and electromagnetic sensors, as briefly recalled below.
IMU devices host tri-axial accelerometers, gyroscopes and magnetometers within
a small integrated unit. The accuracy of accelerometers and gyroscopes is respectively
Sensors 2021, 21, 6706. https://doi.org/10.3390/s21206706 https://www.mdpi.com/journal/sensors
