Hello! I'm An Liang, a PhD student in media and arts technology at Queen Mary University of London.
Today I'm going to introduce our paper: knit stretch sensor placement for body movement sensing.
Motion capture technology is widely used in movement-related human-computer interaction,
especially in digital arts such as digital dance performance.
Our interest is in the design of a textile based tangible system for dance performance.
In this paper, we present a knit stretch sensor based dance leotard design to evaluate the
locations where the sensors could best capture the movement on the body. There are two studies
are undertaken: expert interviews and sensor placement study. First study, expert interviews,
is to gather target users requirements to determine the system requirements including
what dancers actions should be sensed and what part of the body should be tracked while dancing.
Then building on the result of the interviews, we did a sensor placement study.
We designed a dance leotard with sensor groupings to examine where to place the sensors.
To gather target users ideas, requirements, and expectations of various aspects
of digital dance performance, we conducted a qualitative interview study
with 10 professional dancers, choreographers, and technologists. Most of our participants
had backgrounds in multiple relevant areas. The table 1 shows the background of interviewees.
And the interviews were semi-structured with two sets of open questions:
one for the interviewees with dance background and another one is for the technologists.
For interviewees who had experience with both dance and technology background we included
all the interview questions for them. The interviews were carried out either in person
or online and each lasting between 45 to 90 minutes and were video recorded. Then the video
data was transcribed manually and analyzed used thematic analysis with the software
maxQDA. From the result of the interviews, we found that technologists all had a similar background in
researching e-textiles within the field of human computer interaction. They shared their experience
of working with dancers, designing for the body, and development of motion-related projects.
The most challenging aspects they found in designing a textile sensing system
is the sensor's robustness and consistent output. All the dancers and choreographer interviewees
works in contemporary dance or modern dance, they described this dance style as incorporating
many other dance styles and allows for more freedom in the interpretation of the movements.
The dance leotard is the most commonly worn clothing for dancers, it not only needs to
feed the body perfectly but it also allows for full range of motion without restriction.
And dancers and choreographers prefer long sleeves and dark colours in rehearsal.
The centre of the body was mentioned many times
as dancers treat the center of the body as to where all the movements comes from.
The torso is clearly identified as the preferred location in order to track the dancer's movement.
Building on the result of the interviews, we designed a leotard with knit stretch sensors
to measure torso movements. The leotard is used to address the reliability and robustness concerns
that the technologists expressed. In particular, we examine how the performance of the stretch sensor
measuring body movements is affected by the location of those sensors on the body.
For the dance leotard design, we made a long-sleeve leotard
using black euro jersey fabric. The the garment is made for women who wear UK size
8 but it actually feeds from size 6 to 12 as the fabric itself is very stretchy.
And we placed multiple sets of sensors close to each other to allow for a comparison. For
the construction of the sensor, we choose to use a commercially produced silver-plated conductive
knit fabric, Technik-tex P130B, as it has been found to be suitable for small scale movements.
Then the sensors were bonded to the black Eurojersey fabric.
This picture shows groups of sensors placed around the torso. There are group of long sensors along the
spine are designed to capture the movement for the spine, and there are four groups of
two sensors across to each other around the waist, is aimed to capture twisting from two directions.
In the centre front, a long sensor covers the front zipper
and secures in place at the neck using a press-on snap.
Also, there are four groups of short sensors placed on each side of the front chest
and upper back to capture the movement of the upper torso. As for the method of movement capture,
we chose a set of movements that dancers and choreographers mentioned in the interviews
as the basic movement focusing on the torso. A set of six movements were captured all while standing,
they are: rolled down, lean back, side bend, c curve, back arch and waist twist.
Each movement was repeated 30 times by 10 female participants and we use the VICON
motion capture system to measure the changes in the leotard and underlying body shape.
We place the reflective markers along the stretch muscles to get the approximate changes in length
that occurred throughout the movement. We used an Arduino-based microcontroller
to measure the sensor's electrical resistance and the VICON blade software recorded
each marker positions in the x y and z axis. And we used 120hz sample rate for the data collection.
The figures on the right show the connected sensors and reflective marker setup for each
movement section. The connected sensors showing the green, the red dots are reflective marker sets
and the red line shows the approximate length and changes of the target part of the torso.
We're dividing each cycle of the movement into a stretching and relaxation portion,
then the correlation coefficient is calculated between each sensor's resistance and the length
of the markers for that part of the cycle. Then we take the median of the
correlation coefficient across the 30 cycles for either the stretching or relaxation portion.
As for the data analysis, we're treating the VICON data as the ground through
body position data, the analysis look at how well the electrical resistance of the
stretch sensor correlates with the VICON capture of the movement of the body the distance between
each reflective markers along the body are calculated and summed for each movement.
The changes in these lengths are treated as the approximate stretch of the body. Then we compare
the correlation coefficient between the length of the markers and the electrical resistance
of the sensors to examine the effectiveness of the sensors for measuring the body movements.
Here the table shows the performance of each group of sensors and corresponding movement section,
we highlighted the sensors perform the best in each movement.
From the result, we found the sensors which are constantly under tension perform better
and has higher success rate. The lower back and the chest are not an ideal place
for placing sensors due to the garment fitting problem. The dance leotard design
was found to capture the movements of standing lane back and standing waist twist the best.
In conclusion, we did two studies look at how a textile tangible interface could be improved
for motion sensing in live dance performance. A set of interviews gather the feedback
from technologists and the system requirements from the dancers and choreographers.
We made a dance leotard with groupings of senses to capture a set of movements around the torso.
We found the placement on the body and the fit of the garment
plays a key role in the sensor's performance. We found only the stretched sensors that were
under constant tension and stretched more than 30 percent will successfully capture the movement.
However, the studies only examined isolated groups of sensors for a particular
corresponding movement. The further work would be combining groups of sensors and
investigating more advanced movements in the contemporary dance. Thanks for listening!
Thanks for listening!