WIMU: WEARABLE INERTIAL MONITORING UNIT
A MEMS-based Device for Swimming Performance Analysis
Ana S. Silva, Antonio J. Salazar, Miguel F. Correia
Institute for Systems and Computer Engineering of Porto (INESC Porto), Rua Dr. Roberto Frias, 378, Porto, Portugal
Carla M. Borges
Faculdade de Engenharia da Universidade do Porto (FEUP), Rua Dr. Roberto Frias, s/n, Porto, Portugal
Keywords: Wearable, Monitoring device, Biomechanical parameters, MEMS, Swimming analysis.
Abstract: Advances in sensor technology, electronic textile integration, and integrated circuits have introduced a
paradigm shift in the way most researchers approach signal monitoring. In recent years, devices such as
body sensor networks (BSN) allow for direct on-body physiological and biomechanical parameters
measurements. Such technology allows for a more in depth analysis of an athlete’s performance, without
affecting the results due to awkward wires or uncomfortable carry-on devices. Miniaturization and other
achievements allow a more seamless interaction with the individual, permitting a more natural behaviour
during the monitoring session. The project BIOSWIM (Body Interface System based on Wearable
Integration Monitorization) is a joint multidisciplinary effort of a number of Portuguese universities which
seeks a pervasive monitoring solution for performance, physiological and biomechanical signals from a
swimmer under normal training conditions. In order to achieve such an undertaking a swimsuit prototype
was developed with truly integrated EKG textile sensors; which will work in conjunction with a wearable
inertial monitoring unit (WIMU) and a wearable chemical monitoring unit. This article focuses on the
WIMU, which serves as the biomechanical data processing unit of the system.
1 INTRODUCTION
In order to evaluate an athlete’s performance,
coaches and trainers have been dependent on visual
markers and inferred biomechanical data for years.
Nowadays, the development of miniaturized low-
powered accelerometers and gyroscopes allow their
inclusion on wearable monitoring alternatives,
closing the gap between the athlete’s perception and
that of his/her trainers. In fact recent advances, such
as micro-electromechanical systems (MEMS), have
introduced a viable alternative, which unlike many
of its counterparts; can be made to be wearable and
water friendly, as to be used on swimming analysis.
Electronic textiles, interactive textiles, smart
garments and wearables are terms expressing one of
the most recent research trends in textile science and
technology. From late 1990’s until now investigators
from research centers and companies proposed
several approaches and solutions for many different
problems, from technical applications to leisure.
While the fastest developments started with
multimedia applications, very soon the scientific
community understood the potential of these
technologies on other areas, like in medicine and
sports. Literature describes a large number of
projects intended to remotely measure physiological
parameters on mainly heart failure patients, such as
MyHeart and Wealthy projects (Pacelli et al., 2006),
VTAMN (Noury et. al, 2004) and more recently
BIOTEX (Coyle et al., 2010) and Vital Jacket
(Cunha et al., 2010).
Although the wearable inertial monitoring unit
(WIMU) is still at a prototype stage, preliminary
data reveals the promise of such a device.
2 BIOSWIM PROJECT
The BIOSWIM project is inspired in all these
emerging technologies and intends to apply them in
a smart garment which can allow the measurement
87
S. Silva A., J. Salazar A., F. Correia M. and M. Borges C..
WIMU: WEARABLE INERTIAL MONITORING UNIT - A MEMS-based Device for Swimming Performance Analysis.
DOI: 10.5220/0003172700870093
In Proceedings of the International Conference on Biomedical Electronics and Devices (BIODEVICES-2011), pages 87-93
ISBN: 978-989-8425-37-9
Copyright
c
2011 SCITEPRESS (Science and Technology Publications, Lda.)
of vital signs and other significant signals both for
health and particularly for sport athletes, thus
contributing for more knowledge in these areas. The
wearable equipment combining comfort properties
together with sensing devices will fit on an
individual in an optimal way without the need of
using unpleasant methods for fixing sensors on the
athletes. Electromyography, cardiac rhythm,
respiratory effort, oxygen consuming taxes, motion
capture, wrist and arm accelerations and rotations,
speed, hydrodynamics’ pressure constitute some of
the parameters of interest of this research project and
intended to be collected at simultaneous time using
the same wearable, thus consisting in a major
breakthrough in the sport sciences (see Figure 1).
This project is a multidisciplinary effort of three
major Portuguese institutions: Centre of Textile
Science and Technology of the University of Minho,
INESC Porto (Institute for Systems and Computers
Engineering of Porto) and the Faculty of Sports of
the University of Porto.
Figure 1: BIOSWIM project's monitoring objectives.
The main goals of the BIOSWIM are the
development of wearable prototypes for measuring
several biological parameters, critical for sport
performance and health purposes, oriented for
regular sport and for in-pool (or underwater
depending of the sports) activity. Moreover, the
wearable must be design with maximum comfort,
comprehending the best combination of textile
material with embedded microelectronics for signal
acquisition and data transmission. Also, an universal
electronic system for power supply, data acquisition,
processing, management, and communication
working for both inside and outside water
environments and embedded on textile substrate is
expected to be developed.
An immediate application of this wearable is in
sports, for competition athletes, sport amateurs, and
body maintenance. While for the less demanding
activities some of the actual systems provide the
essential information, the same may not apply when
it is intended to evaluate performance on athletes.
The main goal in this situation is the improvement of
their performance in order to achieve better results.
Proper movement inside water will definitely
contribute for higher speed. Beyond vital signs,
other signals are crucial for optimizing the athlete
effort and thus reduce the human fatigue when
subjected to intensive training or competition
charges.
The development of wearable monitoring
devices for sports practitioners can present several
noticeable repercussions in sportive community,
both with reference to the optimization of the
training process of elite athletes, as well as to the
promotion of safety in rehabilitation and leisure
sports. The idea behind the BIOSWIM project is to
produce an elite training evaluation wearable station,
allowing the most innovative monitoring,
ambulatory registration, real-time visualization and
post-exercise display of both physiological and
biomechanical relevant data for training (heart-rate,
respiratory frequency, oesophageal temperature,
sweat, arm tri-axial acceleration, body vertical
acceleration).
Important repercussions are expected both for
practitioners, coaches and scientists, allowing an
increased safety in physical activity, an augmented
objectivity – and efficiency - of the elite training
process, and an easy data collection for scientific
research in neuro-physiology and biomechanics of
sport.
3 ARCHITECTURE OVERVIEW
Within this article, monitoring systems will be
considered divided in three main sections:
• Sensing section.
• Processing section.
• Transmitting section.
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The mentioned sections can be found separate,
intermixed or integrated depending on the design,
but the objectives of their functions can be readily
separated if needs be.
3.1 Sensing Section
Advances in micro-fluidics, material science, nano-
structures, micro-electromechanical devices,
bioelectrical interfaces, and others; have contributed
to a new generation of wearable and implantable
sensors and monitoring devices. Healthcare has
greatly benefitted from the development of
biosensors (also referred to as chemical sensors)
(Patel et al., 2006) and physiological sensors. Such
achievements have paved the way for truly pervasive
monitoring strategies, which will benefit patients
and reduce the load to health-care facilities. From a
sport monitoring perspective, non-invasive,
minimally intrusive sensors are the preferred choice,
and consideration of their positioning, calibration,
noise, offset, deviation, etc., are concerns (Yang and
Shouqian, 2007). There exist a wide array of
commercially available sensors and even more
experimental devices and concepts waiting their
turn.
3.2 Processing Section
In today’s market, the competition to claim to be the
lowest powered microcontroller is fierce. Depending
of the complexity required by the application and the
feature extraction methods to be applied, an array of
Reduced Instruction Set Computer (RISC) or
Advanced RISC Machine (ARM) architecture based
microcontrollers offer different features which
accommodate varying solutions. Based on the
popular “motes” designs and further research in the
area (unpublished work from the authors), there
seems to be a preference for Texas Instrument
MSP430 ultra-low power, Atmel’s ATMEGA ultra-
low power, and the Microchip’s extreme-low-power
(XLP) PIC microcontrollers. Using the power
specifications, indicated on the datasheet of each
microcontroller, as a base for comparison, can
sometimes lead to problems and confusion; careful
attention must be paid to the conditions in which
each manufacturer measures their devices power
consumption.
3.3 Transmitting Section
When referring to WMS, it is unavoidable to
consider a wireless component for interfacing with
the system; either be it for real-time (or continuous)
or sporadic updating to a remote processing node, or
for downloading the collected stored data, or even
for transmitting the data from a sensor node to the
on-body or remote processing unit. The presence of
cables or the need for physical removal of the device
for data download represents an alternative that
while permissible at prototyping and troubleshooting
stages, is impractical at more advance stages of
design and implementation.
A number of alternatives exist for mid-range
wireless communication including common
protocols (GSM, WiMAX, UMTS, WLAN, etc.) and
upcoming 4G mobile communication solutions.
From a more local point of view the IEEE 802.15
Workgroup has introduced and arrays of solutions.
Among the favorite standards one counts with the
IEEE 802.15.1, known as Bluetooth, and the IEEE
802.15.4, also referred to as Zigbee. The number of
low-power short-range transceivers in the market
today is enough to overwhelm even experienced
researchers. It seems every brand offers their
particular RF solution, claiming low-power
transmission; companies such as Texas Instrument,
Atmel, Semtech, Maxim and Microchip (to mention
a few), offer interesting and varying solutions.
4 WIMU
For years, numerous devices and setups have been
implemented in order to assist on swimming
performance analysis. Many of these devices were
based on video analysis, while others made direct
measurement and signal capturing through awkward
setups, generally uncomfortable for the swimmer
and thus affecting hers/his performance. Advances
in a number of fields have allowed for compact
wearable monitoring devices, greatly improving the
data gathering process and closing the gap for a truly
seamless biomechanical signal monitoring solution.
Although there is a relatively reduced number of
biomechanical signal monitoring systems being used
for swimming performance analysis today
(particularly when compared to the number of
wearable monitoring devices for healthcare or even
for land based sports), a shift on the approaches for
swimming analysis is being noted. Different
strategies have been applied by the mentioned
systems, however a common element seem to be
their dependence on accelerometers. Some systems
worth mentioning are the ETH Zurich Wearable
Computing Laboratory’s SwimMaster (Bächlin et
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89
al., 2009) and Imperial College BSN device (Pansiot
et al., 2010).
4.1 Design Overview
The WIMU – Wearable Inertial Measurement Unit –
was designed in the scope of the BIOSWIM project.
The goal was to develop a MEMS-based wearable
device for assessing biomechanical parameters of a
swimming athlete. The inertial unit comprises a tri-
axial accelerometer for linear acceleration and a
gyroscope for angular velocity measurements. In
addition, a microcontroller for signal acquisition,
conversion and wireless transmission is used. A 3D
schematic and a picture of the overall system are
depicted in Figure 2.
(a)
(b)
Figure 2: (a) Tri-dimensional view of the WIMU. (b) Top
view of the system.
Both inertial sensors used are MEMS devices.
Micromachined inertial sensors have a huge
potential for applications in the biomedical field.
They fulfill the requirements of small volume,
portability, low power consumption and they are
available at low cost
To extract the acceleration value, the
accelerometer has a movable mass which is
connected to a fixed frame via spring structures. An
external acceleration will displace the mass from its
rest position, proportionately to the input movement.
The micromachined gyroscope used relies on a
mechanical structure that is driven into resonance
and excites a secondary oscillation in either the same
structure or in a second one, due to Coriolis force.
The amplitude of this secondary oscillation is
directly proportional to the angular rate signal to be
measured.
Commercially available evaluations boards were
used to integrate the MEMS sensors into the WIMU.
The accelerometer evaluation board is a small circuit
board intended to be used for evaluating the
MMA7260QT accelerometer and developing
prototypes quickly without requiring a PCB to be
designed. It also provides means for understanding
the best mounting position and location of this
accelerometer. Similarly, the IDG-300 gyroscope is
integrated in an evaluation board along with the
electronics necessary for application-ready
functionality
In order to integrate both the accelerometer and
the gyroscope into the inertial unit, a microcontroller
was selected from the many commercially available
devices. The one chosen is the eZ430-RF2500
development tool from Texas Instrument. The
eZ430-RF2500 uses the MSP430F2274
microcontroller which combines 16-MIPS
performance with a 200-ksps 10-bit ADC and 2 op-
amps and is paired with the CC2500 multi-channel
radio-frequency (RF) transceiver designed for low-
power wireless applications. This board is a
complete wireless development tool that includes all
the hardware and software required to develop an
entire wireless project. One reason for choosing this
board is its low-power consumption characteristic.
The wireless communication uses the SimpliciTI
protocol which belongs to Texas Instruments and is
a low-power RF (2.4 GHz) protocol aimed for
simple and small RF networks. It was designed for
easy implementation with minimal microcontroller
resource requirements.
The WIMU behaves like an End Device in a
sensor network topology. It is responsible for
acquisition and conversion of the sensor signals and
posterior wireless transmission to a remote station
for post-processing and analysis. It was designed so
that multiple WIMUs could be used in different
body segments in a truly body sensor network.
4.2 WIMU Architecture
As mentioned above, the WIMU consists of a 3-
axial accelerometer, a gyroscope, a microcontroller
and a power supply unit. The architecture of the
WIMU is represented in Figure 3.
The acceleration and angular velocity signals are
acquired and converted sequentially by the 10-bit
ADC integrated in the MSP430F2274 micro-
controller at a sampling frequency of approximately
50 Ksps. A time-stamp is then retrieved from the
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system and added to a sensor packet containing the
3-axis accelerations and angular velocity. Therefore,
the final packet frame consists of sensor signals
together with a time-stamp, which is then ready to
be sent by the CC2500 radio frequency to a remote
station where the sensor data can be analysed and
processed.
Figure 3: WIMU architecture.
The WIMU weights approximately 65.6 grams
and measures 57x90.5x24 mm. This way the device
can unobtrusively be worn by the swimmer without
affecting his/her performance during swimming.
With two AA batteries the system can operate
continuously up to four hours.
5 EXPERIMENTAL RESULTS
In this study, the sensor was placed on the upper
back of the swimmer as can be seen on Figure 4.
Before entering the pool, the swimmer was asked to
perform a number of flexibility related movements
routines in order to determine if she felt movement
constraints. Once in the pool, she was asking to
swim, submerge and perform various movements in
order to asses if the WIMU’s presence represented
an obstruction to her movements. In both cases
(outside and inside the pool) the swimmer reported
that the unit did not affect her movements in any
manner. Several more fast submersions and from
wall impulses were performed as to determine the
waterproofness of the package, proving to function
adequately. Finally, the swimmer was told to
complete several sets of laps using free-style (i.e.
crawl) technique, then a number of laps with
breaststroke, and finally butterfly. For all styles
indicated the end of pool turn was perform through a
vertical turnaround (i.e., stop-touch wall-
turnaround), reversing direction without flipping
under water (in order to avoid signal loss).
(a)
(b)
Figure 4: (a) WIMU positioned at the upper back of the
athlete. (b) The athlete swimming with the WIMU.
The signals are captured and buffered, and
although there is the potential for signal conditioning
at this point, the raw data is sent to the base station
as is. Synchronization between the base station and
the WIMU allow for missed data marking, in order
to apply signal restoration strategies. Such data is
compensated through cubic interpolation when
necessary and then smoothed by a convolution
approach. At this point, the crawl technique requires
of no compensation (i.e., interpolation) for missed
data points since no link loss occurs for a significant
period (except for horizontal flip at the end of a pool
lap). Although the butterfly and breaststroke
technique do present gaps due to momentary loss of
signal they do not represent a significant number of
points as to deteriorate the signals core; some
resulting data can be observed on Figures 5 and 6.
Observing the graphs concerning each swimming
technique, it was possible to differentiate between
styles, each stroke, and end of pool. For example,
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Figure 5: Two laps using Crawl technique signals.
Figure 6: One lap captured signals for each performed technique.
free style can be readily distinguish from
breaststroke and butterfly by the signal provided by
the accelerometer in Y-axis. The referred signal
presents large variations for the crawl technique,
while for the other presented styles these variations
are comparatively small. Alternatively, the butterfly
and breaststroke technique can be differentiate from
the data produced by the accelerometers in the X and
Z axes; which in the case of the butterfly samples
they are both almost double the frequency when
compared to the angular velocity. In the meanwhile
the breaststroke samples show all these three signals
at nearly equal frequency.
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It is still early in this project to produce
conclusive results regarding feature extraction for
performance analysis, and there is a clear need for
accumulating data of diverse swimmers of different
genders and competitive level, however these first
steps are quite promising. A more comprehensive
analysis of the data gathered up to now and future
collections, as well as feature extraction strategies
for performance analysis will be presented in future
works.
6 CONCLUSIONS AND FUTURE
WORK
In this paper, we present a prototype for swimming
performance analysis monitoring based on
accelerometers and gyroscopes, referred to as
WIMU. The WIMU is one of the objectives of a
much more ambitious multi-disciplinary effort of a
group of Portuguese universities known as the
BIOSWIM project. Such project seeks to
characterize swimming through physiological and
biomechanical signal capturing at points distributed
throughout the athlete’s body. Although the device
presented is still at the initial stages of development
it was capable of providing promising data under in-
pool normal conditions. The current version of the
WIMU serves as a basis for future implementation
that will focus on wearability, energy harvesting,
and integration within the BIOSWIM’s project
swimsuits.
ACKNOWLEDGEMENTS
The authors would like to acknowledge the
Foundation for Science and Technology of Portugal
for their support of the BIOSWIM project
(PTDC/EEA-ELC/70803/2006) and of some of the
PhD students involved in this article
(SFRH/BD/61396/2009 and SFRH/BD/60929
/2009). Additionally the authors would like to
acknowledge the contribution of Barbara Mota, main
testing swimmer.
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