Lighting and Fitness
Can humans harness different hues of lighting to improve physical performance? Can we be faster, sharper, stronger in spaces lit with warm tones instead of cool tones?
If so, I might have some serious home-renovating to do… Read on for answers to these colorful questions.
Ubiquitous Computing (INFO 4120) | Cornell University | May 2018
Key Responsibilities: Literature Review, Experimental Design and Implementation, User Research, Final Paper and Poster Authoring
Background
Rome wasn’t built in a day, but it’s safe to say Rome was built in daylight.
Light begets productivity. As humans, our working hours, socializing hours, creating and exerting and Rome-building hours are all during peak access to sunlight (ideally) or artificial light that allows us to see, feel, and interact with our environments.
It’s natural to wonder, then: in a given realm of human activity, does one type of lighting catalyze better performance than others?
My classmate Milam Milhouse and I explored this question while at Cornell University. All too familiar with the challenge of juggling physical fitness and a rigorous college curriculum, we became curious if altering the lighting around us could improve our performance during workouts. This had the potential to optimize gym sessions for ourselves and several of our friends, who, like us, adhered to strict schedules and had few openings to integrate fitness.
Milam and I partnered on programming health-tracking devices to study the effects of red- and blue-hued lighting on our peers’ physical performance. We conducted a literature review, defined a hypothesis and testing methodology, curated our findings, and arrived at a glimmer of hope for college-goers worldwide.
Hypothesis and Support
Red light will drive increased physical performance, and conversely, blue light will drive decreased physical performance.
Studies suggest that exposure to bright lights influences alertness and sleepiness [1].
There are correlations between blue lights and accelerated post-stress relaxation. Research on the calming properties of blue light [2] indicates a potential relationship between color of lighting and physical performance.
Research on music and physical performance suggests that music synchronous with movement has a positive effect on the ability to execute physical tasks [3]. Other studies note that intensity of music also corresponds to heightened physical performance.
The LIFX light bulb has the ability to dynamically respond to inputs from paired devices (like, say, Fitbits) by adjusting lighting color and intensity.
The Fitbit Flex captures various physiological data points. In our study, we measured our participants' step counts and transmitted them to LIFX light bulbs for responsive lighting adjustments.
Barry's Bootcamp in Virginia is an example of a fully immersed and lighting-adaptive fitness center that could optimize workout performance.
Experimental Design
The goal of our study was to analyze the relationship (if any) between lighting hue and physical performance. To do this, we programmed LIFX lightbulbs to change colors (using Python) based on a Fitbit wearer’s activity levels, and we observed the number of jumping jacks that each participant could perform in different lighting hues. We ran this study across 15 participants. The materials needed were 1 Fitbit Flex, 2 LIFX lightbulbs, and access to a Python programming interface as well as a room in which to conduct trials.
Adaptive Lightbulb Configuration
Conceptually, this is how we set up our Python script to link the Fitbit Flex with the LIFX lightbulbs:
Authenticate with the Fitbit cloud dashboard through a POST request. This should trigger a GET request to extract data from the Fitbit.
Loop through a recurring 1-minute data collection phase that extracts the number of steps that the participant has taken during the observed minute, with distinct starting and post-1-minute step counts.
Categorize the participant’s activity level based on step count into one of these five buckets:
Sedentary, if 0-66 steps in a minute
Low Activity, if 67-211 steps in a minute
Moderately Active, if 212-300 steps in a minute
Highly Active, if 301-450 steps in a minute
Dangerously Active, if 450+ steps in a minute
Trigger a change in lightbulb color based on participant’s activity level through a PUT request, as follows:
If Sedentary, then display the neutral color white
If between Low to High Activity (67-450 steps), then display the color red
If Dangerously Active, then display the color blue
Pilot Study Structure
We invited each participant to an experimental study room in Gates Hall at Cornell University and requested that they wear our programmed Fitbit Flex for the duration of the study. The room was chosen carefully for its size, as we intended to produce an immersive effect when lighting the room with our LIFX color-changing lightbulbs. Before asking a participant to complete the study, we recorded his or her name, email address, and whether he or she was colorblind. After each session, we recorded the number of jumping jacks performed under each lighting condition. We amassed data from 15 participants, only 1 of whom was colorblind.
In our pilot, we asked each participant to do as many jumping jacks as possible in a 2-minute timespan, first in red, then blue, then white light, with a 5-minute break between each lighting transition. For both the pilot and final studies, we created and followed a script to allow for a standardized testing environment.
Final Study Structure
In the next and final iteration of our study, we reduced the jumping jack timeframe to a quarter of the original time, from 2 minutes to 30 seconds. Secondly, we realized that asking the user to perform jumping jacks under 3 different lighting conditions revealed our purpose: testing for a relationship between lighting hue and workout performance. To make our experimental purpose less obvious, after each 30-second jumping jack session in the final study, we gave participants a 2-minute break during which they were asked to read select chapters from The Girl with the Dragon Tattoo. We then only pretended to note down how much of a chapter each participant was able to get through.
The last major change to our experimental design was randomizing the order of lighting color each participant was exposed to, in hopes of reducing experimental error caused by participant fatigue. For example, one participant completed jumping jacks in the order of red light, blue light, white light, while another followed the order of blue light, white light, red light.
Results and Future Work
The results of our final study supported our original hypothesis, albeit with a very small sample size. Red light was conducive to higher physical performance, while blue light lowered physical performance.
Given the limited pool of 15 participants, however, it is difficult to say from this study alone whether different hues of lighting were actively causing or simply correlated to fluctuations in physical performance. Ideally, at least 30 participants would be necessary for a more thorough statistical analysis. There is also potential to layer in participant heart rate data (instead of step count data) and modify the experimental design (e.g., by sourcing a different set of participants for each type of lighting rather than exposing a single participant to all types of lighting) in order to gain additional insight into the relationship between lighting and fitness.
37.9
Average Number of Jumping Jacks in Blue Light
40.4
Average Number of Jumping Jacks in Red Light
38.9
Average Number of Jumping Jacks in White Light