Hi i'm Jinmo from the Media Lab and Hyundai Motor Company.
Today, Dr Neska El Haouij and I will present our work on Ambient Breath.
Before the pandemic people in the United States drive an hour a day on average commute.
This everyday driving holds many complexities that include stressors.
To improve stress management, we designed a just-in-time breathing
intervention that uses multi-sensory feedback.
We evaluated its efficacy in a driving simulator.
Voluntary regulation of breathing has long been used as a method for controlling affective states.
In-car breathing interventions have been proposed to regulate the breathing pattern of the driver
and to calm or maintain their calm state.
Parades et.al engaged drivers in a simulator with haptic stimulation
and voice guidance that influenced their breathing, facilitating slow
and regulatory breathing signals while maintaining safe driving performance.
However, Zepf et. al. found that excessive workload from driving and conscious breathing
practices can cause unwanted driving mistakes. Ghandeharioun and Picard proposed the possibility
of subconscious breathing influence of people under demanding tasks
in an office environment without degrading their working performance.
In this study, we developed a novel closed-loop breathing intervention system with three sensory
simulations: auditory, visual and wind. The present closed loop system recognizes
the driver's breathing rate using the BioHarness chest strap.
The system turns on sensory stimulations when a driver's breathing rate increases to higher than
120 percent of their mean breathing rate. When the intervention system is on,
it provides uni- or multi-stimulations which modulate at the mean breathing rate.
We proposed that the uninstructed subtle sensory feedback can
subconsciously guide the breathing pattern of the driver while maintaining safe driving behavior.
The following hypothesis contain the expected results comparing the multi- and uni-sensory
intervention with and without a driver's choice of intervention selection comparing manual and
autonomous driving and comparing giving the intervention with or without instructions.
To evaluate the proposed hypotheses, we designed two user studies. The first study
consisted of four driving segments in the manual driving modes with four different conditions
of the interventions: control, auditory, auditory+visual and auditory+wind intervention.
The second user study consisted of both manual driving as well as autonomous driving.
Before starting the driving task of this second study we provided
the session to each participant to choose their preferred pattern of the information.
Based on their selection we provided four driving sessions in a randomized order:
Manual driving without and with intervention, Autonomous driving without and with intervention.
Finally we disclosed how to consciously engage with the sensory simulations to
regulate breathing and provided a short training session. Then,
we conducted the fifth session testing manual driving with the intervention.
26 subjects participated in the first study and 36 and the second one.
We only consider the complete datasets for analysis here.
The table describes the two cohorts. Both studies involved a balanced cohort in terms
of gender, age ranges, and number of novice users of the simulator.
In this work, we analyze the number of crashes, infraction,
breathing rate, electrodermal activity and the post-study surveys.
Here we start by presenting evidence on how simulated driving mimics the real-world setting.
Actually, the car simulator has several features that make it somewhat realistic
and with that we offered as many training session as the participant wanted to get
used to the simulator so that any crashes were less likely to be due to its novelty.
Then we begin the studies where we examine the crashes and the serious offenses.
We found that they are not significantly different than zero
We then compared the efficacy of the intervention: the unisensory versus the multi-sensory one.
Examining safety, the infractions were significantly different
across the conditions, mainly higher for the auditory intervention compared to
the multi-sensory and control condition. No significant differences were found in
the normalized breathing rate, time duration below goal breathing rate
,reported workload and focus level, as well as the stress pleasure and energy levels.
When we asked the participants to select their preferred feedback more than half of them choose
the auditory and wind intervention indicating that the wind was soothing and refreshing.
We verified that giving the choice of selection did not
significantly improve their engagement here. However, the participant reported significantly
higher pleasure when comparing study 1 and 2. The intervention training helped increase
the driver engagement as you can see in the first row of box plots.
The affect arousal was significantly lower after the training.
This might be explained by the fact that the training session helped the
participant by reducing uncertainty and stress.
We were also interested in the influence of the automated driving. We thus compared the
aggregated data for manual and autonomous driving modes within the control condition.
We noticed that the breathing rate, workload, stress were significantly
lower for the automated condition, while the pleasure was the same.
We compared the data between autonomous driving with and without breathing guide. We found that a
significantly better engagement in the breathing for the autonomous compared to the manual one.
For future studies, we plan to consider different study designs and driving context
we notice in this work different engagement level depending on the driving context.
For example there was a better engagement with the breathing intervention after waiting at
the traffic light as you can see in the normalized breathing rate decrease here.
We want also to test if we can generalize our findings to the real-world setting.
Thanks.