Behavioral and Physiological Metrics - Measuring the User Experience: Collecting, Analyzing, and Presenting Usability Metrics - page 177

Rana el Kaliouby, Ph.D., cofounded Affectiva in
April 2009 to commercialize technologies devel-
oped at the MIT research group. The first prod-
ucttocomefromAffectivaiscalledtheQSensor
(see Figure 7.12 ).

The Q Sensor is a device worn on the wrist
that measures the electrical conductance of the
skin known as electrodermal activity (EDA). EDA
increases when you sweat—small increases in
moisture are associated with increased sympa-
thetic nervous system activity indicating emotional
activation or arousal. Three types of activation can
lead to increases in arousal: increases in cogni-
tive load, affective state, and/or physical activity.
Emotional states associated with EDA increases include fear, anger, and joy. Arousal
increases are also associated with cognitive demands and may be seen when you are
engaged in problem-solving activity. Our state of arousal—and hence the conduc-
tivity of our skin—is lower when we are in a relaxed state or bored.

Figure 7.12 Affectiva's Q Sensor, a wearable, wireless biosensor.

ResearchersinanumberoffieldsareusingtheQSensortomeasuresym-
pathetic nervous system activity objectively. One of the initial use cases for the
Q Sensor has been in understanding the emotional state of students on the
autism spectrum. Individuals with autism spectrum disorders often present neu-
tral facial expressions, despite feeling threatened, confused, or otherwise emo-
tionally distressed. Researchers working with autistic students are reviewing
EDAdatacapturedwiththeQSensortobetterunderstandthetriggersforemo-
tional outbursts. Eventually, the technology will make its way into the classroom
where it will serve teachers by providing early warning signals that students are
becoming stressed without outward displays of duress. This will enable teachers
to respond to their students in a timely and appropriate way.

In the area of user experience research, the Q Sensor can be used to help
pinpoint moments of excitement, frustration, or increased cognitive load experi-
enced by the participant. The UX researcher establishes a baseline for each partic-
ipant. Experiences are then compared to their baseline, with particular attention
given to the peaks, or places where there was a peak level in arousal.

While it is helpful knowing what may have triggered an increased level of
arousal, it does not tell the researcher whether the experience was positive or neg-
ative. This is known as valence. Picard recognized the need to measure valence
objectively as she brought Affectiva cofounder el Kaliouby to MIT in January
2007. El Kaliouby's research had been focused on measuring facial expres-
sions using computer-vision and machine-learning techniques. This technology
matured and was incorporated into Affectiva's second product, the Affdex facial
expression recognition system. Affdex is a passive web-based platform that can
take streaming video as an input and predict the presence of facial expressions in
close to real time. Affdex is being used to measure emotional response to media