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Hairware: Conductive Hair Extensions as
a Capacitive Touch Input Device
Katia Vega
Marcio Cunha
Hugo Fuks
Pontifical Catholic University of Pontifical Catholic University of Pontifical Catholic University of
Rio de Janeiro
Rio de Janeiro
Rio de Janeiro
Rua Marquês de São Vicente,
Rua Marquês de São Vicente
Rua Marquês de São Vicente,
225 - Gávea, Rio de Janeiro 225 – Gávea, Rio de Janeiro –
225 - Gávea, Rio de Janeiro RJ, Brazil
RJ, Brazil
RJ, Brazil
[email protected]
[email protected]
[email protected]
a)
Non–conductive
hair extensions
b)
c)
Layer 1
Layer 2
Layer 3
Conductive Hair
Figure 1 – Designing Hairware as an input device. a) Changing capacitance by a three layers approach. b) Hair extensions during
chemical process. c) Visual feedback while touching the hair.
ABSTRACT
Our aim is to use our own bodies as an interactive platform.
We are trying to move away from traditional wearable
devices worn on clothes and accessories where gestures are
noticeable and remind cyborg looking. We follow Beauty
Technology paradigm that uses the body’s surface as an
interactive platform by integrating technology into beauty
products applied directly to one’s skin, fingernails and hair.
Thus, we propose Hairware, a Beauty Technology
Prototype that connects chemically metalized hair
extensions to a microcontroller turning it into an input
device for triggering different objects. Hairware acts as a
capacitive touch sensor that detects touch variations on hair
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IUI'15 Companion, Mar 29 - Apr 01, 2015, Atlanta, GA, USA
ACM 978-1-4503-3308-5/15/03.
http://dx.doi.org/10.1145/2732158.2732176
and uses machine learning algorithms in order to recognize
user’s intention. In this way, we add a new functionality to
hair extensions, becoming a seamless device that recognizes
auto-contact behaviors that no observers would identify.
This work presents the design of Hairware’s hardware and
software implementation. In this demo, we show Hairware
acting as a controller for smartphones and computers.
Author Keywords
Hairware; Conductive Hair; Beauty Technology; Wearable
Computing; gesture recognition.
ACM Classification Keywords
H.5.2 Information interfaces and presentation: User
Interfaces; Haptic I/O.
INTRODUCTION
When embedding technology into everyday life objects,
Weiser envisioned it functioning in an invisible and
unobtrusively way [14]. For that reason, minimizing
awareness while interacting with technology, continue to be
an important guideline in Ubiquitous Computing. Our
concern with this vision is that users are not consciously
aware that these pieces of technology are gathering data and
processing it for them. In contrast, we propose interactions
that the user is consciously aware of and intends to generate
them, though in a concealed way, by enacting auto-contact
behaviors.
Even though the billionaire beauty business market is
mostly supported by women and most women wear makeup
everyday [4], beauty products have not yet been thoroughly
explored in relation to their use as wearable computing.
Beauty Technology [10,11,12] disrupts this frontier by
placing technology directly on the body surface allowing
women to use beauty products to control their environment
through technology in a personal, seamless and fashionable
way.
This work proposes the use of Hairware as a novel
electronic device to be used in wearable computing. We use
a chemical platting technique that makes the artificial hair
extensions conductive but, at the same time, remains
looking like regular human hair. This paper introduces
Hairware, a capacitive touch sensor that detects a variety of
touches for the triggering of different devices. Section 2
identifies previous work on body technologies as input
devices. Section 3 presents the hardware and software
implementation to detect touch on Hairware. Section 4
shows the model used for learning and recognizing touches
on hair. Section 5 presents the evaluation results and
reviews the lessons learned using Hairware. Conclusion and
future work are shown in the last section.
materials that stick to the skin, replacing conventional
eyeliners, conductive fake eyelashes sense blinking.
Wigs could be used either as apparel or to fulfill cultural or
religious obligations. SmartWig [9] is a wearable device
that uses a wig for hiding electronics that communicates
wirelessly with other external devices. SmartWig suggests
applications that could fulfill a number of functions, from
acting as a health care device that monitors users’ vital
signs to helping blind people navigate roads, or changes
slides in a presentation by tapping their sideburns, under
which buttons are hidden. A further potential improvement
of the wig may use ultrasound waves to detect objects
around a user. Hair accessories that vary from clips to
corsages, designed to give every look a final flourish, could
also be used for creating discreet and fashionable gadgets
attached to the hair. First Sign Hair Clip [8] is an electronic
hair clip that communicates with a mobile application to
automatically call for help and collect evidence when the
user is in danger. By using accelerometers and gyroscopes,
it detects head impacts associated with violent crimes,
automatically triggering an alarm, while evidence is
collected by a microphone.
DESIGNING HAIRWARE
Our prototype combines hardware (hair extensions, circuit
and microcontroller) and software (machine learning
algorithm).
RELATED WORK
Hardware
Wearable computing changed the way individuals interact
with computers, intertwining natural capabilities of the
human body with processing apparatus [14]. Most of this
technology has been designed just for clothing or
accessories. However, some works place technology on the
body’s surface. Thus, the skin and its regenerative
appendages (i.e. hair and nails) not just play a crucial role
in human beings but also embeds electronics to act as input
devices. For example, Skinput [2] uses a bioacoustics
microphone to sense the vibration that occurs when the
body is tapped. Another example is Senskin [5], a wearable
device that uses multiple IR reflective sensors implanted in
an armband to allow the skin to be used as a soft input
interface by comparing the actual force and the sensor
values using an elastic model of the human skin. Touché [6]
is a sensing technology that proposes a Swept Frequency
Capacitive Sensing technique by using bracelets that detects
touches on different parts of the body by sensing the
impedance variability between electrodes. Thus, the user
could put the phone into silent mode by making a “shih”
gesture bringing her index finger to the lips.
Hairware is artificial hair extensions that are chemically
metalized for acquiring electrical conductivity and keeping
a natural coloration. The chemical process is carried out in
two phases: Activation and Electrolysis (Figure 1b). We
used a Hairware strand of approximate 1.5 by 25cm and
with a surface resistivity of less than 5 ohm/sq.
In previous Beauty Technology prototypes, Conductive
Makeup [8,9] was presented as an interface for detecting
voluntary blinking. Conductive Makeup includes
conductive eyeliner and chemically metalized fake
eyelashes that act as blinking switches. While conductive
eyeliners connect sensors and actuators by using conductive
Hairware is connected to a circuit to work as a capacitor
sensor. This circuit creates a delay in the pulse that is the
time the capacitor takes to charge and discharge. In this
way, Hairware is used as a conductive surface that detects
when another conductive surface approximates to it.
Therefore, as the human body is conductive, the average
internal resistance of a human trunk is ~100 Ω [13],
touching Hairware will affect its capacitance and result in a
different charging time.
We use hair clips for attaching the circuit to the hair
extensions in order to make it easily removable and
replaceable. A wire connects the conductive hair extensions
to the microcontroller, in this way, the conductive hair
extension keeps rounded by the non-conductive hair and are
not directly in contact with the user’s nape. In addition, this
approach makes it possible to put the circuit in different
accessories such as headbands, brooches, hats and the top
of the hair extensions.
Figure 1a shows three layers of non-conductive hair
extensions added for isolating the hair from the skin and
nape. In addition, these layers improve the capacitor sensor
values. Each time the user touches the top, middle or tip,
the capacitor sensor differentiates these values. The circuit
compares an output that transmits the pulse and an input,
which receives the pulse. When a finger touches Hairware,
it creates a delay in the pulse, and the Arduino
microcontroller recalculates this delay. The circuit has four
1MΩ resistors and one 100pF capacitor. The resistors
selects the sensitivity, bigger the resistor, the farther away it
detects a human. With 4MΩ resistor between the output and
input pins, the circuit is tuned to start to respond one inch
away, just the sufficient to overcome the non-conductive
hair layer. The small capacitor (100 pF) placed from sensor
pin to ground improves stability and repeatability. Some
LEDs were added to the system to give feedback to the user
whenever a touch is detected (Figure 1c).
Software
For classification, we use a decision tree implementation
provided by BigML [1]. Each transmission from the sensor
contains a capacitive charging time in milliseconds, which
we extract for classification. Currently, we can classify five
touches interaction in the Hairware: no touch, touch on the
top, touch on the middle, touch on tip and straightening.
When trained, the decision tree build an actionable model
that we use as an Arduino function to classify the
interaction in real time. Each node represents the
confidence action from the read value. The key feature to
recognize touch on the hair is not to detect the touch itself,
but the circuit must be fined tune to detect small
capacitance charge variation along the hair.
As expected, the touch on the tip has the higher value due
to the fact that layer of non-conductive hair is the thinner
one (layer 3). The charging value will decrease when the
interaction gets near the top where there are more nonconductive hair layers acting as a filter. The straightening
action has the lowest values due to its continuous contact
time with the sensor. Noise appeared on the readings given
that the hair was in direct contact with the skin. However,
our algorithm recognizes it as noise and obtains 92%
accuracy on the five trained touch gestures.
EVALUATION
For our evaluation, we aim to identify the exposure of the
technology in Hairware and we measure the accuracy in
replaying the hair straightening, top, middle, and tip touch.
We recruited five female participants, ranging in age from
28 to 35. The study took approximately 30 minutes per each
participant and included a gratuity. Given that Hairware is a
proof of concept of the technology, evaluations were taken
in the same laboratory under the same conditions
(temperature, humidity and pressure). At the beginning, we
conducted pre-questionnaires to identify the participants’
profiles. All participants were right handed. They do not
own any wearable technologies but every day they use
other electronic devices like smartphones and tablets. None
had used hair extensions before but they all knew what they
were and they have seen them applied to other person. All
of them expressed that they touch their hair when they feel
anxious, thoughtful and nervous. Three of them noticed
them using their hair as a flirting tool.
We interview the participants before they observed and
used the wearable device. We asked them questions related
to Hairware visibility and their use of hair extensions.
While showing Hairware, we asked them about their
impressions about it, if they could identify any difference
between these hair extensions, and normal or artificial hair.
Then we showed a non-conductive artificial hair extension
and asked about the differences they could detect between
this and Hairware.
After 2 minutes of training on the different tasks, we asked
them to perform the five different touches. They performed
each touch 10 times. Finally, we conducted an interview
asking for recommendations and future uses.
RESULTS AND DISCUSSION
After listening to the answers of the first interview, we
identified that, at first sight, Hairware wasn’t noticed as a
technological device and they weren’t aware of its
conductivity. Most of the participants thought it was natural
hair extensions and comparing it to artificial hair, they
noticed that the artificial hair extension was more shining
and had a smoother texture. They also expressed that, when
Hairware was attached to someone’s hair, the difference
between it and natural hair was not noticeable.
During the tests, we observed that, although our algorithm
differentiated each touch, a previous calibration was
necessary for each user. Differences in skin capacitance and
hand position could made the capacitor sensor identify
different values for each user. We also noticed that other
feedback must be designed. LEDs won’t be noticed if the
user is wearing Hairware. We will replace this feedback by
vibration motors.
After using Hairware, they expressed that adding layers of
non-conductive artificial hair extensions, gave the device a
shiny look and it was smooth to touch. They also expressed
that, if the circuit is hidden into the hair or into an
accessory, an external observer won’t notice the device.
Future versions of Hairware will add other touches that the
participants exposed that they usually perform like twirling
their hair and passing the fingers through the head.
During the final interview, participants expressed that they
would use Hairware for specific purposes like a security
device. That is, whenever they feel in danger, they would
like to send a message to the police or to someone they trust
without anyone around noticing that they were doing it.
Another suggestion was to use it as an input device for
triggering house appliances. Another suggestion was to
trigger a reminder whenever they are continuously touching
their hair as a nervous tick. In addition, it could be used as a
therapy tool for relaxing when the device noticed they are
stressed.
CONCLUSION AND FUTURE WORK
REFERENCES
Hairware fosters a seamlessly looking approach to
wearables. It is artificial hair extensions that are chemically
metalized to maintain a natural coloration and when
connected to a microcontroller could be used as an input
device. Thus, not just the technology is seamless but also
the action of touching her hair that trigger devices are
hardly noticed by an external observer. This paper
explained our processes in designing the interface, creating
the hardware and implementing the algorithm for detecting
touches on the top, middle, tip, straightening the hair and no
touch. A study case was conducted with five participants to
identify if the technology is noticeable by an observer and
for testing our gesture recognition system. Possible uses for
it would be any kind of communication without being
noticed. A security device could trigger messages with the
user’s location and recording the event. Customized actions
on the phone could make a call, record an audio, send a
default message and take a picture. Artistic performers
could use Hairware to turning on lights and devices on
scene. Also secret agents could start filming and
communicate with other agents.
1.
2.
Future works will include the use of beard Hairware in
order to explore the masculinity side of the equation. In
addition, it will be used as both, input and output devices.
Actuators as LEDs, speakers and vibration motors could be
used to explore Hairware as an output device. Another input
interface could be an array of involuntary acts to sense and
control anxiety and stress in users.
Other sensors, such as accelerometers and gyroscopes will
be integrated on the hair extensions to make combinations
of movements and hair touch. A potential improvement
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user [3]. Other movements like curling Hairware with
fingers may be explored when using Hairware as flex
sensors [7].
ACKNOWLEDGMENTS
Marcio Cunha (grant 163066/2013-2) and Hugo Fuks
(grant 302230/2008-4) are recipients of grants awarded by
the National Research Council (CNPq). This work was
partially financed by Research Support Foundation of the
State of Rio de Janeiro-FAPERJ/INCT (E-26/170028/2008)
and CNPq/INCT (557.128/2009-9). Katia Vega is a
postdoctoral fellow with grant funding from PNPD/CAPES
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