1. Dynamic user profiling according to data sensors
Alireza Mozaffari
Advisors : Dr. Miquel Sánchez Marre , Dr. Cristian Barrue Subirana
Universitat Politécnica de Catalunya
[1] Giuliani B. Cortes U. Martınez-Velasco A. Barru´e C, The role of
i-Walker in post-stroke training, International Conference of the Catalan
Association of Artificial Intelligence (2012)
[2] Image courtesy of Universitat Politècnica de Catalunya, Intelligent
Walker (2008)
[3] Matthias Luber · Kai O. Arras · Christian Plagemann · Wolfram Burgard,
Classifying dynamic objects, (2009)
[4] Roman Y. Shtykhand QunJin, Capturing User Contexts: Dynamic
Profiling for Information Seeking Tasks, the Third International
Conference on Systems and Networks Communications
References*
 Stroke is one of the leading reasons and causes
of senior’s motor disabilities.
 Walkers are mobility aids usually used in the
rehabilitation context and also to support mobility
in post-stroke seniors.
 We use an Intelligent Walker as a device for
rehabilitation.
 Dynamically updating the profiles in robot
rehabilitation system is a technique to help post-
stroke seniors by monitoring their activities.
 Using dynamic profiling methods and clustering algorithms to
update the user’s information in the system dynamically to
adapt the recommendation actions provided by the system.
 Create and Update profiles according to the current user
status regards to data sensors to have a link between data
and clinical profiles in order to give the proper amount of help.
Introduction1
Objectives2
Thesis Plan3
Conclusion
 Post stroke senior people with gait
disabilities experience many difficulties in
daily life. I-walker is a device to help
elderly to confront gait disabilities.
 The present study introduce a method by
integrating useful dynamic profiling
approaches to investigate the
performance of stroke patients by
monitoring and updating their profile
status dynamically from the data sensors.
 The proposed method can classify each
ability of the user separately and make a
classification of the general situation of i-
walker user. Finding pattern recovery
according to profile users in different time
can be a future work .
5
Classifying
in two
concepts
classes
are not
defined
classes of
profiles
are
predefined
4 Methodology
 creating user profiles
 Identifying the clinical
status of the patient in gait
aspect
 Dynamic clustering to
cluster seniors and link
them to a proper group
 Recommend a proper
rehabilitation plan .
I-walker is a robotic
rollator to support
movement training
by its Actuators &
Sensors *[1,2]
 Monitoring the rate of rehabilitation by
representing the changes of the profiles in a
timeline as a rehabilitation process by a heat map
 Prediction of the improvement process using a
specific rehabilitation plan.
 case base reasoning method*[3]. Defined
classes {C1, C2…C10}. Defined data variable T
for each data kind of sensors'{t1, t2, t3…}
 Dynamic profiling with the ability of making new
clusters .profiles are multilayered. Each of layers
reflecting user interests temporarily*[4].