A major goal of this study is to address the use and functionality of the impaired arm through specific assessment, health application and wearable. So far Rehabilitation Gaming System Wearable (RGS-wear) has focused on the amount of movement. In this thesis, the aim is to enhance the current state and establish a novel measurement providing qualitative assessment of movement. Once understanding the rationale for motor learning, impairments and motor control I further developed, and validated features for the rehabilitation applied technology RGS-wear. The execution of this project was divided into three main stages. The first step included kinesthetic data acquisition and assessment, through the use of wearable sensors. Secondly, I performed motion evaluation, analyzed and compared non-dominant and dominant hand movement, in natural and constrained settings, studied patterns and extracted measures of motor function. Thirdly, I studied the functionalities of the wearable and evaluated the acceptability of the wearable as an evaluation tool. The goal of this project was to design and implement appropriate system features and strategies that can augment current rehabilitation protocols. The outcome I believe carries the potential to lead to new guidelines and recommendations for the development of wearable technologies for clinical practices especially in context of motor function.

1. MEASURING AND QUANTIFYING QUALITY OF
MOVEMENT
Enhancing evaluation and treatment techniques for rehabilitation of hemiparetic stroke patients
Justyna Ausareny
MASTER THESIS UPF- FINAL / 2015-2016
CENTER OF AUTONOMOUS SYSTEMS AND NEURO- ROBOTICS
DEPARTMENT OF INFORMATION AND COMMUNICATION TECHNOLOGIES
1

2. Introduction to stroke
2
➔ Referred to as a “brain attack”.
➔ Every year first-ever stroke incidents occur about
16 million (Mathers et al. 2006)
➔ Main causes of disability in the western world
(Dobkin, 2015).
➔ 55% to 75% of stroke patients suffer from motor
dysfunctions (Larsen et al. 2005)
About 60% of post stroke patients receive inappropriate care
(Atul Gawande, 2012)
State of Art

3. ❖ How exactly does the motor behavior change
after stroke?
3
❖ How can we can best represent it for better
evaluation and treatment?
State of Art

4. Introduction
to movement
4
Loss of
somatosensation
Paresis
Abnormal muscle
tone
Loss of
fractionated
movement
Movement planning
Coordination
Accuracy
Movement duration
Efficacy
Ease
Smoothness
Efficiency
Coordination
Range
State of Art

5. Clinical scales
Types of measures.
1) To evaluate impairment
2) Determine the impact of the impairment on daily
activities (ADL).
5
How can these impairments be addressed?
State of Art
The most popular test for motor impairment is
Fugl-Meyer Assessment (FM) (Crow et al 2008, Wei et
al 2011, Gladstone et al 2012)
Rowe/ Occupational Therapist, V. (2008, October 15). Fugl-Meyer
Assessment of Motor Recovery after Stroke [Video file]. Retrieved
from https://www.youtube.com/watch?v=B70qDfl3LyA

6. Clinical scales
6
➔ Robustness and Reliability
(Heppner et al. 2008 and French et al.
2001)
➔ Sensitivity
(Beebe et al 2008, Crow et al 2008,
Woodbury et al 2007, Thompson et
al 2015)
What are the issues?
How can we address
these problems?
State of Art

7. Problem statement
➔ clinical scales
➔ subjective tests
➔ difficult to generalize
7
So far, the Rehabilitation Gaming System Wearable (RGS-wear) has tackled
this issue by providing a wearable-based solution as an intervention tool,
focusing on the amount of movement.
State of Art
In this thesis, the aim is to enhance the current state and establish a novel
measurement providing qualitative assessment of movement

8. ➔ Ability to objectively and repeatedly measure movement in a way that
quantify motor recovery
Technology
8
State of Art
➔ Low cost
➔ Provide more access for measuring movement in an evaluation activity
➔ Accelerometer has been applied for the evaluation of stroke motor
recovery (Akay et al. 2003; Bonato et al. 2004).
➔ Allows for motor pattern analysis (Giansanti 2003).

9. Motion evaluation
9
State of Art
Motion analysis systems are collections of
algorithms that transform the data from
one abstraction level to another
(Sant'Anna and Wickstrom 2013).
These systems address 2 main questions:
1. What is being performed?
2. How the activity is being performed?
Retrieved from
http://what-when-how.com/medical-informatics/i

10. Assessment and treatment
➔ Reaching task is one of the
most popular activities has
been extensively studied also
present in everyday activities
ADL (Wagner et al 2007).
➔ Circle drawing is a relatively
new method that has shown to
be suitable for making
distinction between healthy
subjects and stroke survivors.
(Krabben et al 2011)
10
State of Art
➔ Task-oriented training can enhance functional
plasticity in cortical organization (Chollet et al.
1991).
➔ The key elements in motor recovery are quantity
and task specificity (Cirstea et al. 2007).
Retrieved from http://rgs-project.eu/sites/all/themes/danland/images/slideshows/header1.jpg

11. Hypothesis
The purpose of this study is to
11
Methods
1. Provide a technical validation of a methodology for the analysis of quality of movement of the hand,
based on data from inertial motion units (accelerometer and gyroscope), in 2 specific tasks: planar
reaching and planar circle drawing.
We hypothesize that our system/methodology for the analysis of quality of
movement is able to capture differences in performance and identify
movement deficits associated with stroke.

12. Apparatus
Primary system hardware:
➔ Open Metawear wearable (model RG)
with 6 axis of motion sensing
12
Methods
Secondary system hardware for
validation of position of Metawear:
➔ Reactable

13. Subjects
24 healthy subjects recruited from UPF
Poblenou campus. All subjects signed a
consent and approved the data acquisition
process.
Methods

14. Experiment
14
Methods
➔ Task 1. Reaching
➔ Task 2. Circle Drawing

15. Procedure
15
Methods

16. Reactable
16
Methods

17. Methods linear acceleration
17
Methods
Gravity compensation using AHRS sensor fusion algorithm (Seb Madgwick, 2013)
Retrieved from
http://what-when-how.com/medical-informatics/i

18. Methodstrajectories and trails
18
Methods
Trajectory reconstruction using modified AHRS sensor
fusion algorithm (Seb Madgwick, 2013)
Trail detection
Trial detection

19. Methods preliminary analysis
19
Methods
Example of a detected trial and analysis

20. Measures
20
Methods
Loss of
somatosensation
Paresis Abnormal muscle
tone
Loss of fractionated
movement
References:
Nordin et al (2011)
Iwamuro et al (2008)
Chang et al (2007)
Johnson (2011)
Balasubramania, (2015)

21. Results Dominant vs Non Dominant
21
Results

22. Results Non Constrained vs Constrained
22
Results

23. Correlations
23

24. Correlations
24

25. Correlations
25

26. Correlations
26

27. 27
Non constrained Constrained
Reaching Circle drawing Reaching Circle drawing
Dominant Non dominant Dominant Non dominant Dominant Non dominant Dominant Non dominant
Ease -
Temporal
Efficiency
0.0018 0.0001 0.0947 8.1947 e -0.5 0.0023 0.1052 0.127 0.0310
Smoothness -
Ease
0.0037 0.0134 2.5341 e -0.5 1.561 e -0.5 5.3489 e -0.5 1.3442 e -0.5 1.9739 e -0.5 8.8993 e -0.9
Smoothness -
Movement
Planning
4.9044 e -0.5 0.0134 1.0138 e -0.9 5.1486 e -0.6 0.0006 0.0155 0.0002 3.6502 e -0.7
Smoothness -
Temporal
efficiency
0.0037 0.0134 2.5341 e -0.5 1.561 e -0.5 5.3489 e -0.5 1.3442 e -0.5 1.9739 e -0.5 8.8993 e -0.9
Movement
Planning -
Temporal
efficiency
1.7202 e -0.5 4.1917 e -0.9 1.074 e -0.6 4.5677 e -0.9 0.0004 3.2163 e -0.7 2.4044 e -0.8 0.0002
Ease -
Movement
Planning
0.0650 0.0004 0.0572 0.003 0.0157 0.1047 0.1271 0.1313
P
values

28. Conclusions
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➔ We can objectively assess the quality of movement and repeatedly measure
it
➔ When evaluating only healthy subjects the difficulty of task must be taken
into account
➔ The motion systems should sample data at high frequency in order to
insure accuracy
➔ The connectivity and ease of use are the current constraints in the study
that should be addressed in future directions

29. The end
Thank you !
29

30. Usability
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➔ Overall Satisfaction and Ergonomics
➔ User Experiment - Interface Satisfaction
➔ Wearable System Usability Scale
➔ Perceived Usefulness of the Study
➔ Social and Technical Human Factors
Suggestions for future developments:
➔ Add heart rate skin conductance
➔ Different study populations
➔ Implementable devices
➔ Connectivity
➔ Easier to wear
➔ Instant feedback

31. Overall Satisfaction and Ergonomics
31
Agree
Agree

32. User Experiment - Interface Satisfaction
32
Comfortable

33. Wearable System Usability Scale
33ComfortableAgreeAgree
AgreeAgree

34. Perceived Usefulness & Socio -Technical Human Factors
34
Agree
Was there anything about the tool that surprised you?
Over 50% responded no,
Easier to wear
Not challenging
Discomfort when using only 1 hand
Smartphone
Uncomfortable bands
How did it feel for you to have your movement assessed by a
computer?
Over 50% responded fine,
More careful
Uncomfortable “felt like a robot”
Missing feedback
How did it feel to have no physical cues (body language
or verbal communication)
Over 50% responded fine,
Aroused curiosity
Similar to online course
Eliminates pressure of social interaction
Better for concentration
Boring “could have done a lot more things face to face”