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Zishi: A Smart Garment for Posture Monitoring

Authors:
  • Eindhoven University of Technology, Utrecht School of Arts, Saxion University of Applied Sciences, by-wire.net • fashion technology

Abstract and Figures

Zishi is a garment designed to support posture monitoring for the purposes of rehabilitation training. It has been designed with attention to presenting accurate and informative feedback to patients regarding their thoracic and shoulder posture as well as comfort, ease of use, wearability and aesthetics. Zishi can be useful during rehabilitation training for a variety of patient groups. So far, we have been concerned with two broad training scenarios a) for arm-hand (neurological) rehabilitation training after stroke or for MS and spinal cord injury patients. B) for shoulder patients. Zishi consists of a garment integrated with smart textiles and wearable electronics. It presents real-time feedback as a vibration delivered through the garment, visual and audio instructions through android-hand held device (smartphone or tablet).
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Zishi: A Smart Garment
for Posture Monitoring
Abstract
Zishi is a garment designed to support posture
monitoring for the purposes of rehabilitation training. It
has been designed with attention to presenting
accurate and informative feedback to patients
regarding their thoracic and shoulder posture as well as
comfort, ease of use, wearability and aesthetics. Zishi
can be useful during rehabilitation training for a variety
of patient groups. So far, we have been concerned with
two broad training scenarios a) for arm-hand
(neurological) rehabilitation training after stroke or for
MS and spinal cord injury patients. B) for shoulder
patients. Zishi consists of a garment integrated with
smart textiles and wearable electronics. It presents
real-time feedback as a vibration delivered through the
garment, visual and audio instructions through android-
hand held device (smartphone or tablet).
Author Keywords
Wearable; Intelligent Clothing; Motor Learning; Posture
Sensing; Rehabilitation; Smart Textiles
ACM Classification Keywords
H.5.2. [Information Interfaces and Presentation]: User
Interfaces---Input devices and strategies, Prototyping,
Interaction styles.
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CHI'16 Extended Abstracts, May 07-12, 2016, San Jose, CA, USA
ACM 978-1-4503-4082-3/16/05.
http://dx.doi.org/10.1145/2851581.2890262
Qi Wang
Department of Industrial
Design, Eindhoven University
of Technology, the Netherlands
q.wang@tue.nl
Marina Toeters
Fashion Technology
by-wire.net, Utrecht, The
Netherlands
marina@by-wire.net
Wei Chen
Fudan University, Shanghai,
w_chen@fudan.edu.cn
Annick Timmermans
Hasselt University, Hasselt,
Belgium,
annick.timmermans@uhasselt.be
Panos Markopoulos
Department of Industrial
Design, Eindhoven University
of Technology, the Netherlands
p.markopoulos@tue.nl
Introduction
Technology is often seen as a way to reduce the rising
costs of rehabilitation but also to improve the quality of
rehabilitation therapy through increasing the intensity
and the variability of training [4]. Researchers in the
field of human-computer interaction have often
explored training scenarios where technology provides
the opportunity for personalization, for making training
more fun, or by providing feedback to patients.
Especially in the case of stroke rehabilitation examples
include tangible technologies and serious games that
encourage patients to train longer and independently.
The evolution of sensing technology triggered the
growing research interests to support posture
monitoring with wearable technology, for example,
Alankus et al [1], proposed a Wii-based wearable
sensing system, the experiment proved the validity of
reducing compensation motions, while improved
wearability may enhance the experience. Beursgens et
al [2], developed a vest for monitoring the patient’s
posture while playing a serious game intended to
support arm-hand rehabilitation, however the loose
garment and not rigorous sensor placement can not
guarantee the accuracy. Integrating smart textiles and
miniaturized device represent the next generation of
soft electronics. Knitted smart textile act as stretch
sensor in the project Vigour [3], while the system
emphasis on aesthetic integration of smart textile and
feedback motivating people to be active rather than
reliable monitoring. To conclude, we note that
designing wearable system intended for supporting
rehabilitation, it is important to pay attention to
wearability and comfort next to accuracy.
This project concerns two types of rehabilitation
training: neurological rehabilitation where patients
engage in training to practice arm-hand skills after
stroke or spinal cord injury or because they suffer from
chronic condition such as multiple sclerosis or cerebral
palsy. While interactive technology often provide
appropriate training content in terms of the stimuli and
feedback provided to patients, a challenge that
characterizes many of these is that patients will engage
in compensatory movements where they can achieve
the task set to them by the rehabilitation technology,
while moving alternative muscle groups than the ones
that they wish to train. This compromises the
effectiveness of the training and it is typically a focal
point for the therapist who will provide feedback on the
posture of the patient and reminders to maintain it
during the training. Similarly for training patients with
shoulder pain, a set of movements involving the upper
extremities is given, but which require appropriate
posture to be maintained during the training. For these
reasons it is important to create technology that will
provide feedback to patients regarding their posture
during training.
System Overview
Zishi (see Figure 1) consists of a garment with
integrated smart textiles and wearable electronics and
android-based application. Users can easily follow the
visual guidance and adjust their posture to stay in the
personalized setting range. Figure 2 shows that when
the user’s shoulder posture is out of the range, real-
time feedback will be provided, in a way analogous to
how therapists monitor and correct posture of patients
during traditional physical therapy training sessions.
Iterative design process
We applied the approach of research through design,
the project is a result of iterative design process. Zishi
Figure 1: Back View of Zishi;
Model: Annet, Photo by Qi.
Figure 2: Training scenario.
was developed based on the knowledge learned and
reflections from former iterations[5].
§ First iteration provided the proof of the concept that
attached sensors on chest and shoulder could detect
compensation movement from torso and shoulder.
§ Second iteration explored more precise sensing
locations (vertebrae T1, T5 on the spine and
acromion on shoulder) suggested by therapists,
conductive fabric connection (integration, comfort)
pattern and visual feedback.
§ A comparison experiment with Optical system for
accuracy evaluation has been conducted with 7
subjects during the third iteration [6].
§ Two user experiments are currently under way to
evaluate the forth iteration of Zishi in Belgium and
China separately: 20 patients and 10 therapists have
tried out the jacket and provided feedback regarding
usability, acceptance, credibility and expectancy for
the support of therapy, and the motivational aspects
for posture detection during rehabilitation in patients
with shoulder pain. The results are currently being
analyzed.
Implementation
The implementation featured in the following parts:
§ Wearable Circuit Design
Sensor package for the back part contains two 9-dof
IMU sensors from Adafruit, an Arduino processor as the
central node, a 3v lithium battery and a Bluetooth
module for communication between garment and
smartphone. Sensor package for the shoulder part
contains one IMU module and a LilyPad Vibe Board.
§ Magnet Connection Design
Modular design is another feature of Zishi as one set of
sensor package can connect with any garment that
embedded conductive fabric patterns (see Figure 4). A
tiny magnet (3mm in diam) has been placed under
each of the small golden square fabric as the
connection point (see Figure 3). Two magnet strips
were sewed along the edges on both the fabric sensor
packages and garment. In this way, the connection is
easily, robust and smooth.
§ Smart textiles pattern
Figure 5: Conductive fabric circuit pattern
Aimed at exploring flexible and robust connections of
the sensing modules, we got the conductive fabric
pattern by Laser Cutting, the paths has been laminated
on normal fabric with adhesive film. Figure 5 shows the
connection pattern of the wearable circuits and Figure 5
shows the pattern on garment. The pattern design is a
result of balancing the resistance variation and
aesthetics. Pattern trials were evaluated from both
functional and stylish aspects.
§ Garment Design
The garment is easy to put on and take off with magnet
strip zippers in front. The turtleneck on the back part,
Figure 3: Conductive
connection Pattern for Sensor
package attachment.
Figure 4: Conductive fabric
circuit pattern.
slim fit cut and stretchable soft fabric support the
sensors stay in right position.
§ Application
Users can set personalized range of posture (shown in
Figure 6) based on their own condition and task
difficulties. Once over the range, audio notifications and
vibrations will remind the subjects, they can also check
the details on screen (see Figure7). During the clinical
evaluation, one of the patients expressed: “Watch the
pointer rotating when I moved my shoulder, finally I
can easily keep my shoulder down as what the
therapist told me before. ”
Relevance to CHI
Rehabilitation technology is an application domain that
is attracting increased interest in CHI over the last 5-10
years. Most related work has emphasized on serious
game designs, virtual reality applications, and tangible
interaction. To our knowledge this project is the first to
look at garments designed to support rehabilitation
scenarios. Within the context of rehabilitation
technology, there has been so far almost no interest in
wearability, comfort and aesthetics as the dominant
concerns tend to be precision, accuracy of monitoring
and the effectiveness of training applications created.
In this sense, Zishi lies in the intersection of CHI and
wearables community with the rehabilitation
engineering communities, and brings into these fields
concerns and competences from fashion design.
Future Work
The evaluation study that was recently has confirmed
the potential of Zishi, but has also identified a number
of requirements that are necessary to support
independent training by patients. With these
incremental improvemnets we plan to engage in clinical
trials that will establish the effectiveness of the device
in supporting training for different patient groups.
Regarding the functionality of the device in future
iterations, we are exploring how to integrate more
sensing possibilities that can support different training
scenarios; e.g., low back posture monitoring, lower arm
monitoring and secondly, pay more attention to multi-
modal output modalities including shape change as an
alternative haptic modality (instead of vibrations), etc.
Regarding the aesthetic design, Zishi clearly targets
female patients, we plan to also make a men’s version
of the garment.
References
[1] Alankus, G. and Kelleher, C. Reducing
compensatory motions in video games for stroke
rehabilitation. Proceedings of the SIGCHI
Conference on Human Factors in Computing
Systems, ACM (2012), 20492058.
[2] Beursgens, L., Timmermans, A., and Markopoulos,
P. Playful arm hand training after stroke. CHI’12
Extended Abstracts on Human Factors in
Computing Systems, ACM (2012), 23992404.
[3] ten Bhömer, M. and van Dongen, P. Vigour.
interactions 21, 5 (2014), 1213.
[4] Timmermans, A.A., Seelen, H.A., Willmann, R.D.,
and Kingma, H. Journal of NeuroEngineering and
Rehabilitation. Journal of neuroengineering and
rehabilitation 6, (2009), 1.
[5] Wang, Q., Chen, W., Timmermans, A.A.A.,
Karachristos, C., Martens, J.-B., and Markopoulos,
P. Smart Rehabilitation Garment for posture
monitoring. Engineering in Medicine and Biology
Society (EMBC), 2015 37th Annual International
Conference of the IEEE,(2015), 57365739.
Figure 6: Setting
personalized compensation
movement range of torso and
shoulder.
Figure 7: Visual notification
when posture is out of the
setting range.
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  • A A Timmermans
  • H A Seelen
  • R D Willmann
  • H Kingma
Timmermans, A.A., Seelen, H.A., Willmann, R.D., and Kingma, H. Journal of NeuroEngineering and Rehabilitation. Journal of neuroengineering and rehabilitation 6, (2009), 1.
Reducing compensatory motions in video games for stroke rehabilitation
  • G Alankus
  • C Kelleher
Alankus, G. and Kelleher, C. Reducing compensatory motions in video games for stroke rehabilitation. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, ACM (2012), 2049-2058.
Playful arm hand training after stroke. CHI'12 Extended Abstracts on Human Factors in Computing Systems
  • L Beursgens
  • A Timmermans
  • P Markopoulos
Beursgens, L., Timmermans, A., and Markopoulos, P. Playful arm hand training after stroke. CHI'12 Extended Abstracts on Human Factors in Computing Systems, ACM (2012), 2399-2404.
  • M Bhömer
  • Van Dongen
ten Bhömer, M. and van Dongen, P. Vigour. interactions 21, 5 (2014), 12-13.
Smart Rehabilitation Garment for posture monitoring
  • Q Wang
  • W Chen
  • A A A Timmermans
  • C Karachristos
  • J.-B Martens
  • P Markopoulos
Wang, Q., Chen, W., Timmermans, A.A.A., Karachristos, C., Martens, J.-B., and Markopoulos, P. Smart Rehabilitation Garment for posture monitoring. Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE,(2015), 5736-5739.