Effectiveness of Three-Dimensional Kinematic Biofeedback on the
Performance of Scapula-focused Exercises
Ana Antunes
1
, Inês Filipe
1
, Sara Cordeiro
1
, Joana Rosa
1
, Filomena Carnide
1
and Ricardo Matias
1,2,3
1
Neuromechanics of Human Movement Research,
Group of the Interdisciplinary Centre for the Study of Human Performance, University of Lisbon, Lisbon, Portugal
2
School of Healthcare, Setúbal Polytechnic Institute, Campus do IPS, Estefanilha - Edifício da ESCE, Setúbal, Portugal
3
Pattern and Image Analysis Group of the Instituto de Telecomunicações, Instituto Superior Técnico,
University of Lisbon, Lisbon, Portugal
Keywords: Biofeedback, Scapulothoracic Stability, Motor Relearning, Physiotherapy.
Abstract: Three-dimensional (3D) kinematic biofeedback can help identify scapular movement disorders and assist
the subjects' motor relearning process by facilitating changes in physiological and biomechanical function
through real-time knowledge of performance and result during or immediately after a task execution. This
study assessed the effectiveness of 3D kinematic biofeedback on the quality of the scapula-focused
exercises execution, and motor learning transfer during shoulder flexion and a daily activity. Thirty healthy
adults with no history of shoulder pain or dysfunction were randomly distributed into two groups. Skin-
mounted sensors allowed tracking of the thorax, scapula and humerus, and scapulothoracic and
glenohumeral 3D angles were computed after reconstructing upper-extremity motions during daily activities
and exercises for different phases of a motor relearning process. The results of this study demonstrate that
the execution quality of scapula-focused exercises benefits of real-time 3D kinematic biofeedback and that
transfer of learning occurs with a specific motor training intervention.
1 INTRODUCTION
Shoulder pain and dysfunction are among the most
frequent problems of patients with mechanical
musculoskeletal disorders seeking health
professionals (e.g. Physical therapists), which
usually affect functional ability and life quality,
resulting in a significant economic impact (Cunha-
Miranda et al., 2010).
Scapular dysfunction (or dyskinesis) seems to be a
common denominator across the most prevalent
shoulder dysfunctions. Although a consistent body
of literature addresses how shoulder impingement
symptoms are affected by scapular dysfunction, the
role of the latter is not clearly defined in creating or
exacerbating shoulder dysfunctions (Kibler et al.,
2013; Struyf et al., 2013). Potential biomechanical
contributors have been divided into two main
groups: musculoskeletal alterations at rest (postural)
and movement alterations (dynamic); such as pain,
soft tissue tightness, muscle dynamics, muscle
strength imbalances and fatigue, and thoracic
posture (Michener et al., 2003).
Some emerging evidence suggests that a scapula-
-focused treatment is effective to restore an accurate
scapular motion and stability, considered essential
for a normal shoulder function (Hanratty et al.,
2012; Kibler et al., 2013; Struyf et al., 2013). The
conclusions on the effectiveness of exercise in the
treatment of people with shoulder dysfunctions are
challenged by the heterogeneity of the exercise
interventions. Still, it has been extensively accepted
the assumption that these patients need to go through
a motor relearning process such as the proposed by
Fitts and Posner (1967). Real-time biofeedback has
been used to enhance the learning ability of an
individual (Holtermann et al., 2008). 3D kinematic
biofeedback is a valid method that can reliably
identify scapular movement disorders (Tate et al.,
2009) and can facilitate the physiological and
biomechanical function through the reception of
feedback information in real-time during or
immediately after a task (Vedsted et al., 2011).
173
Antunes A., Filipe I., Cordeiro S., Rosa J., Carnide F. and Matias R..
Effectiveness of Three-Dimensional Kinematic Biofeedback on the Performance of Scapula-focused Exercises.
DOI: 10.5220/0004928701730178
In Proceedings of the International Conference on Physiological Computing Systems (PhyCS-2014), pages 173-178
ISBN: 978-989-758-006-2
Copyright
c
2014 SCITEPRESS (Science and Technology Publications, Lda.)
The biofeedback is effective in multiple contexts,
showing satisfactory results by obtaining maximum
performance (Egner and Gruzelier, 2003; Huang et
al., 2013; Markovska-Simoska et al., 2008; Pop-
Jordanova and Cakalaroska, 2008; Tsao and Hodges,
2007). Scapula motion analysis contributes to the
understanding of the shoulder dysfunction and has
been considered very suitable to the daily clinical
context (Tate et al., 2009).
The aim of this study was to assess the
effectiveness of 3D kinematic biofeedback during
scapula-focused exercises on: (i) motor learning
transfer during shoulder flexion task and one daily
activity (simulating drinking a glass of water); (ii)
the quality of the exercise execution during a
cognitive phase and (iii) associative phase of a
shoulder motor relearning process.
2 MATERIALS AND METHODS
2.1 Participants
A non-probabilistic sample of 30 participants (10
male and 20 female), 26 right-handed and 4 left-
handed. Subjects were randomly and equally
distributed into two groups: control (CG) and
experimental (EG) groups. The mean age was 21.57
± 4.14 years, with a mean weight and height of 63 ±
10.37 kg and 1.68 ± 0.08 m, respectively.
Participants were selected following specific criteria
(checklist), applied by physical therapists properly
instructed and aware of the study purposes. Healthy
young participants were included with no history of
pain or dysfunction of the shoulder. The exclusion
criteria were: to be aged over 60 years; to have signs
of complete rupture of the rotator cuff tendon or
acute inflammation; to have been submitted to a
physical therapy or any other treatment during the
study and/or in the past 12 months that could have
effect on dependent variables; to perform regular
sport activity in the last six months (at least three
times per week); to have diagnosis of cervical
radiculopathy or neurological changes, visceral or
systemic pain, positive Thoracic Outlet syndrome,
any rheumatic diseases, history of shoulder, neck or
spine high surgery and history of dislocation,
subluxation or shoulder fractures.
The ethics committee of the School of Healthcare,
Setúbal Polytechnic Institute, approved the study
and all participants gave their written informed
consent.
2.2 Instrumentation
Bony segment landmarks 3D coordinates were
collected using an electromagnetic system
trackSTAR (Ascension Technology, Burlington,
Vermont) and “The MotionMonitor” software
(Innovative Sports Training, Chicago, Illinois). This
allowed synchronising the tracking of four sensors
with a sampling rate of 100 Hz per sensor. Static
accuracy has been reported at 1.8 mm and 0.5°
(Milne et al., 1996).
2.3 Procedures
All research procedures were conducted by two
experienced and trained physical therapists. After
reading a letter explaining the study procedures and
goals, data collection began with a questionnaire of
the subject characteristics, including age, gender,
height, weight and dominant side. The participants
were randomly distributed in CG and EG. The figure
1 summarises the study procedure.
Figure 1: Study flow chart.
TrackSTAR sensor 1 was attached on a transparent
acrylic – stylus - and three electromagnetic sensors
were attached over the skin: of the spinous process
of the first thoracic vertebra (sensor 2); of the flat
surface on the superior acromion (sensor 3) and on
the lateral side of the humerus (sensor 4), using
double-sided tape. The humeral sensor fixation was
30 participants
Control Group
n= 15
Experimental Group
n=15
Randomiza
t
ion
Shoulder flexion up to 45°
Mimic drinking a glass of water
Baseline for transfer assessment
Scapula relocation towards ST-NP
Cognitive Phase exercises
Shoulder flexion up to 45°
Mimic drinking a glass of water
Transfer assessment
Scapula relocation towards ST-NP + Flexion
Associative Phase exercises
Outcome Data
BP distance, ST-NP distance and Execution time
Statistical Methods
Intra- and Inter-group outcomes analysis
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174
reinforced with a velcro strap. Tape was also placed
strategically over the sensor cables to reduce any
motion artefacts.
The protocol of 3D kinematics data collection of the
thorax, scapula and humerus followed previously
published procedures (Matias and Pascoal, 2006)
and the International Society Biomechanics
recommendations for reporting upper extremity
joints motion (Wu et al., 2005).
Scapulothoracic neutral position (ST-NP) was
defined according to Mottram (1997) and scapula's
Euler angles (internal rotation, upward rotation and
posterior tilt) recorded.
ST-NP was set out for each subject, providing visual
and tactile feedback. This position was assumed as
the ST target position during the exercises.
Each subject performed the following sequence of
movements:
a) Shoulder flexion up to 45°;
b) Mimic drinking a glass of water;
c) From the initial (postural) position relocate the
scapula towards the ST-NP;
d) From the initial (postural) position relocate the
scapula towards the ST-NP and while holding
this position preform shoulder elevation in the
scapular plane;
e) Repeat a);
f) Repeat b).
This exercise sequence was intended to study the
effectiveness of 3D kinematic biofeedback on the
performance of scapula-focused exercises in a
cognitive (c) and associative (d) phases of motor
relearning and if any immediate transfer occurs to an
control shoulder flexion task (e) and to a daily
activity task (f).
In each movement, a set of trigger signals
synchronised with the kinematic data were used to
identify (i) the beginning of data collection, (ii)
when the subject verbalised that it reached the ST-
NP and (iii) after 3 seconds from the latter.
In the experimental group, participants were asked
to focus on the data show to access the biofeedback
information.
This process happens in real-time, where the patient
tries to move the yellow cross (that responds
instantaneously to the shoulder movements,
represented in Figure 2) into a static square (Figure
2), which appears always in the same position,
according to the number of variables (coordinates)
relevant to the study.
Figure 2: Example of Biofeedback display.
In the control group (group 1) participants have not
access to the biofeedback system information. For
both cases, the exercise ended when the participants
reached the goal (i.e. when the ST reached the NZ)
or after 15 seconds even if the participant could not
achieved the objective.
Five repetitions for each exercise were performed,
with an established interval of two minutes rest
between them, in order to prevent muscle fatigue
(Wilmore et al., 2008). The same physiotherapist
provided a verbal instruction for each repetition.
The effectiveness of the exercise execution was
determined by the following parameters:
-The distance to the BP: computed as the mean of
the root mean square distances of scapula orientation
values in each time frame to the BP;
-The distance to the ST-NP: transformed by
the mean of the root mean square distances of the
scapula orientation values, also in each time frame to
the ST-NP.
-Execution time: time spends from the first to the
second trigger.
2.4 Statistical Methods
All data were analysed using the MATLAB (version
2012a) and IBM-SPSS (version 21.0).
A visual pre-screening of the records was made, to
rule out abnormal data acquisition sessions for a
Gaussian distribution and additionally tested with
the Shapiro-Wilk test. Appropriate descriptive
statistics were calculated for each variable (mean,
standard deviation and mode).
Differences between groups were performed through
Student’s t or Mann Whitney tests (when normal
distribution was not verified). The within-groups
association analysis was calculated with paired t-
test’s or Wilcoxon’s test (for non-normal
distribution of variables). The level of significance
used in this study was set for p < 0.05 (two-tailed).
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175
3 RESULTS
It was found statistical significant differences within
the experimental group on the Euclidean distance to
the best path results (z= -2.22; p= 0.027), with an
execution quality increased by 1.25º when compared
to the pre-exercise condition (table 1).
Table 1: Descriptive statistics (mean±sd) and associations
test results between pre and pos- exercise conditions
(FLEX- flexion; ADL-activity daily living).
n=30
Pre
exercise
Pos
exercise
F
L
X
Distance to the
BP
CG 8.41±3. 48 9.21±3.33
EG 9.16±3.04
8.22±2.43
*
Distance to the
ST-NP mode
CG 8.07±4.76 7.79±4.37
EG 9.73±6.54 9.33±7.06
A
D
L
Distance to the
BP
CG 5.11±1.27 4.79±1.40
EG 4.73±1.52 4.89±1.68
Distance to the
ST-NP mode
CG 8.41±4.52 8.16±6.20
EG 9.49±7.16 9.56±7.33
*p<0.05
No statistical significant differences were found in
any of the measured variables related to the
cognitive phase exercises. On the contrary, for the
associative phase exercises, statistical significant
differences were found between groups in Euclidean
distance to the best path results (t= 3.91; p= 0.001),
and the mean Euclidean distance to the ST neutral
position (u= 58.0; p= 0.014) (table 2).
Table 2: Descriptive statistics (mean±sd) and associations
tests results between control and experimental groups.
n=30 CG EG
COGNITIVE
Distance to the BP 1.56±0.81 1.70±0.86
Distance to the ST-NP 3.44±2.00 2.95±1.88
Time 3.25±1.25 3.93±1.25
ASSOCIATIVE
Distance to the BP 4.19±1.17 2.68±0.89*
Distance to the ST-NP 5.00±2.00 3.63±1.63*
Time 2.81±0.66 2.62±1.00
*p<0.05
4 DISCUSSION
In a motor relearning process the variability
of the practice consists in repeating variations of the
same task in which the parameters are changed,
providing variations around the same skill. This
study rely its intervention model in the extensive
known, considering three stages motor relearning
process that consists on the sequential cognitive,
associative and autonomous phases (Fitts and
Posner, 1967). The duration of the first phase is
limited from a few minutes to a few days, while the
second learning phase can last for weeks or even
months (Schmidt, 2003; Sherwood and Lee, 2003;
Summers and Anson, 2009) . According to this
model for patients to improve their motor
performance the exercise intervention must go
through scapula-focused exercises aiming the
awareness of the scapulothoracic neutral zone and
normalisation of the scapulohumeral rhythm, by
facilitating the central nervous system's ability to
efficiently control the inter-segmental motion of the
upper limb (Hess, 2000; Cools et al., 2003; Cowan
et al., 2003).
In this study the exercise exposure period was the
same of an average time of a physiotherapy
session at an early stage of motor relearning process
with emphasis on the cognitive and associative
stages.
The results of this study demonstrate that real-time
3D kinematic biofeedback is an effective solution to
correctly perform scapula-focused exercises during
the progressive phases of learning a new skill,
notably when the complexity of the task increases
(Jones and French, 2007). The latter become
particularly relevant to the associative phase
where the quality of the movement becomes more
important than the amount of practice itself
(Schmidt, 2003; Sherwood and Lee, 2003; Summers
and Anson, 2009). The results also provide
preliminary evidence that after one physiotherapy
session, immediate transfer of learning (Issurin,
2013; Maslovat et al., 2009) occurs when
performing a similar task, with an increase in the
execution quality. Given the obtained results, we
believe that successful learning can be more
expressive if we raise the time and volume of
practice.
These preliminary findings corroborate other
published results on the immediate effect of a
specific motor training intervention (Tsao and
Hodges 2007; Sturmberg et al. 2013).
Future studies are needed to address the effect of
exercises volume and specificity on the execution
performance quality, and its effects on the learning
retention and transfer. In addition, it would be
relevant to determine whether the magnitude of
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these changes are clinical meaningful, particularly in
patients' functionality.
5 CONCLUSIONS
The real-time 3D kinematic biofeedback, proved to
be an effective tool for improving the quality of the
exercises’ execution. Based on this study results
subjects who had access to kinematic biofeedback
improved 3D motion control of the ST during the
analyzed tasks, corroborating results from previous
studies. Such a tool can help subjects achieve
rehabilitation motor (re)learning goals, and improve
rehabilitation decision-making process by
quantifying human movement performance.
ACNOWLEDGEMENTS
This study was a non-profit project and had no
financial support. The authors would like to
acknowledge all the participants that kindly accepted
to participate in this study.
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