Noise + Signal
The Noise + Signal project was a research project which manifested in an installation at FACT in
September 2013 in which artist Daksha Patel used state of the art Biosensing technology in a unique
drawing project. EEG data from participants wearing headsets was sent via an arduino and wifi shields to
a computer. Participants moved around the building, whilst the computer (and artist) was in a separate
space. The artist wore biosensors (skin galvanometer or heart monitor), and signals from her sensors
interacted with the EEG signals creating a biofeedback loop and noise in the system. Creative coder Ben Lycett, worked in collaboration with artist Daksha Patel to explore different methods of visualizing the
live data. This data was projected upon a large drawing easel, upon which the artist drew, responding to
the noise and data.
"This final step involved converting this continuous stream of bodily response data from (mere) code to
something perhaps more aesthetically pleasing, and also more commonly interpretable. The computer
was connected to a digital projector throwing images onto the easel. As a backdrop to the resulting
visualizations, Daksha used an architectural blueprint or ‘base map’ (of FACT) to shape the pulse and
flow of the data. As responses flashed up onto the projected surface they moulded, dripped and slid along
some classic architectural forms. For example, in the drawings, doors were represented by the arced
movement they create. Other features such as walls and windows were also represented in their own
unique ways, further providing a kind of spatial structure to the otherwise abstract data. EEG readings are
usually displayed in a simple linear format flowing from left to right. In routing this data to a building plan,
Daksha married the environmentally-attuned nature of the readings with the visual form – providing a
contextual landscape for both herself and observers. As a result, the flashes and flows that projected onto
the easel come to life as tracings of everyday, human movement.
Although visually stimulating, the constant pulses fed through the software and projected onto the wall are
not stored; do not leave a residue, and cannot be replayed. They are otherwise lost remnants of ongoing
action. However, and this is the central point of the project, Daksha responded to these flashes of white
light and marks onto the easel with a marker pen. As multiple lines and traces take over the canvas,
Daksha has to react quickly. Even then, the flow of data is too agile and too unpredictable to be able to
capture and log every movement. Some participants took phone calls that stimulated the mind; the flows
were long, slow and continuous. Easy to draw. Others used the time to rest and contemplate; the visuals
sped up and provided scant opportunity for Daksha to capture and draw."
-Sam Hind discusses the Noise + Signal Project at the Cornerhouse in Manchester for The Semaphore
Line.
The Signal + Noise research project had its foundations in the status of noise in scientific studies.
Medical visualisation is always an incomplete set of data about the body. It is a combination of ‘signal’
and ‘noise’; the goal is to maximize the signal-to-noise ratio so that accurate conclusions can be drawn.
No scientific instrument is 100% accurate; ‘instrument noise’ cannot be completely eliminated.
Within the context of experimental observations, “dirty data’ is data which has missing or incorrect values
due to errors in measurement – rendering the data unusable in a scientific context. ‘Noise’ is
measurement without errors but which has unusual readings as a result of biological or physical
phenomenon such as movement. The ‘noise’ makes it difficult to judge the outcome of the measurement;
‘noise’ is synonymous with variations in the data.
The concept of ‘noise’ has been employed in physics for some time, but only relatively recently (last 12
years) in biology. In the past, the focus was upon understanding signals, not upon why they varied. There
are many different sources of ‘noise’ in biological systems, some can be accounted for, and some are
unknown. New sets of tools (using biology itself as a signal) are being developed to understand ‘noise’ in
biological systems. The measurement of ‘noise’ can help scientists to understand how biological systems
can vary.
Daksha's interest in ‘noise’ is to do with the contextual information about the body (and its interaction with
the environment) that it is registering. This information describes a wider ‘picture’ than the narrow
confines of most scientific studies. It includes the unknown with the known. To minimize the movement of
the body (internal and external) in order to maximize signal-to-noise ratios seems to me to exclude
valuable information. ‘Noise’ in the data raises philosophical questions about the meaning of
measurement.
Daksha's research is concerned with how the concepts of ‘signal’ and ‘noise’ may be valuable in relation
to understanding her drawing practice. She questions how can she create a methodology to experiment
with concepts of ‘signal’ and ‘noise’ when drawing in response to the medical body? Can drawing be
understood as data? Daksha Patel, in creating this work, sought to explore drawing as; data, as a
process which response to internal and external information, as an alternative method of measuring, as a
trace of experience and the relationship between drawing and the diagram.
You can watch a video of the performance on the right. (EMBED = https://vimeo.com/98648895) For
more information on Daksha Patel's work, you can visit her website.