SnoozeSHIFT - Space Apps Challenge

SnoozeSHIFT| Sleep Shift Scheduling Tool

Awards & Nominations

SnoozeSHIFT has received the following awards and nominations. Way to go!

Global Nominee

Sleep Shift Scheduling Tool

Sleep loss and fatigue may lead to reduced performance and an increased risk to safety during many activities, including spaceflight. Your challenge is to develop an operational sleep shift scheduling tool that provides autonomous customization of a schedule for sleep, exercise, and nutrition to manage fatigue.

SnoozeShift | An all-in-one Sleep Correction and Shifting Tool based on the Linear Shift Model

Summary

More than 120M adults across the globe need to shift their sleep-wake cycles. These can include spaceflight passengers and directors, passengers traveling across time-zones via air, shift workers, and even individuals who wish to correct their sleep routines. SnoozeShift is a cross-platform, mobile-first, easy to use app that caters to this very need. It collects user data inputs such as original sleeping time, new timezone (or target sleeping time in case of routine correction), preferred sleeping duration, and the total time dedicated for the circadian shift. Using this, it prepares a schedule using a linear sleep-shift model and displays it as a visually appealing Gantt Chart.

How We Addressed This Challenge

The aim was to develop a sleep shift schedule that provides an “autonomous scheduling for sleep routine, exercise and nutrition to manage fatigue”.

Product: Our answer to this problem is SnoozeShift. The application integrates sleep, exercise and nutrition to provide a more holistic approach in fighting fatigue and sleep loss as part of sleep shifting. Although the challenge was specific to space-based applications, SnoozeShift can also be used by people in the non-space industry. Especially people who suffer from jet lag while traveling across distant time zones. The application can also be used by shift workers who work in night/evening shifts or millennials who follow unhealthy sleeping routines. The crux is that all of them need to shift their sleeping routine in one form or the other.

Working: SnoozeShift takes in some basic input of the user, i.e. standard sleep time, wake time, targeted time zone. It takes the user’s standard sleep time as a circadian marker. A linear shift of the circadian marker over the shift duration (difference in current and targeted time zones) was executable and optimal, as per research.

Our algorithm takes into consideration the following factors:

The application then makes a customized routine on how to shift the sleep user’s cycle. It monitors caffeine intake, blue light exposure and exercise to obtain the shift required. SnoozeShift maps this out to a Linear Shift Model, and displays it up as a Gantt Chart on the App Screen.

The algorithm is smart enough to suggest relevant supplements based on the conditions faced:

If the schedule requires timelines to be stretched, supplements include naps and caffeine as subtle supplements and alertness drugs as severe supplements
If it requires timelines to be shrinked, then supplements advised are shades, music/white noise and reading times as subtle supplements and melatonin and other hypnotics as severe supplements.

The use of subtle and severe supplements (as mentioned above) are guided by conditions mentioned in our artwork shown below: (Note that the tolerance levels shown are per unit day)

The application also takes in feedback from the users after completion of every routine, in an attempt to better suit the routine to its user. This promotes a more personalized experience.

Mission: We hope that we can get this app on play store, in an attempt to help solve the problems faced by people everyday.

How We Developed This Project

Motivation: There is no preamble required to state that sleep is crucial for sustainable work efficiency. We identified that it is not just spaceflight passengers or directors who need sleep shift scheduling, but also international travelers on Earth who suffer from jet lag and shift workers, especially those prone to Shift Work Sleep Disorder (SWSD). In fact, being millennial students, we ourselves have an unhealthy sleeping routine and yearn to shift to a healthy one.

Approach: To make a schedule for sleep-wake cycle acclimatization, we firstly gathered insights on possible models of sleep-shifting. A Research Paper (Optimal Schedules of Light Exposure for Rapidly Correcting Circadian Misalignment; Kirill Serkh and Daniel B. Forger; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3983044/) was particularly helpful in comparing such models. We chose to go with the linear shift model and then moved to identify the least amount of variables we needed to create such a schedule, emphasizing primarily on placing sleep and light exposure times at the right place. We then anchored Exercise and Meal timings to sleep timings and made logical conditions on when should medical supplements (Alertness drugs, hypnotics, etc.) be administered.

Development: We designed, tinkered, and prototyped with our model using Figma (A web-based, collaborative Design Studio for UX). The app development was done in Dart Language, using Google’s Flutter Framework that renders native applications for iOS, Android, and the Web from a single codebase. For the database and authentication purposes, we used Google’s Firestore and Firebase suite.

Journey: In the process, we encountered many hassles. Primarily, generalizing and simplifying the cases we considered was a huge task at hand. Every situation we considered, brought along with it a new set of challenges and possibilities. Some of the most noteworthy were:

What if a user forgets a particular task mentioned in the schedule?

We came up with a feature’s idea (called Empathy Adjuster) that would dynamically adjust the schedule as the user keeps updating which all action items the user could successfully perform, and which she failed to.

How would this app run?

For any solution to be sustainable, it has to have a practical revenue stream. We associated with it a Freemium Model, wherein all features are available to the general audience for free of cost, but in case people have severe or specific cases of Circadian Misalignments, they can be connected to verified Medical Experts through a paid channel.

How We Used Space Agency Data in This Project

https://www.nasa.gov/mission_pages/station/research/astronauts_improve_sleep

The aforementioned article gave us a basic sense of sleep in space, and the several methods that are already being used to ensure optimum sleep.

“Molecular Mechanisms of Circadian Regulation During Spaceflight; https://ntrs.nasa.gov/citations/20110020662”

This article reinvigorated the fact that the use of light is the most efficient method of circadian entrainment. Also, it gave us an idea for further selection of foods that are high in antioxidants to reduce oxidative stress.

“Effects of consuming various foods and nutrients on objective and subjective aspects of human performance and behavior; https://ntrs.nasa.gov/citations/19860020037”

The paper played a central role in integrating nutrition into our algorithm. One hallmark of it would be understanding the effects of caffeine on performance. Caffeine plays a central role in sleep or lack thereof. Hence, this helped in tweaking the algorithm to better integrate caffeine into our routines.

“Characterization of International Space Station Crew Members’ Workload Contributing to Fatigue, Sleep Disruption and Circadian Desynchronization; https://ntrs.nasa.gov/citations/20205006969 “

The aforementioned paper helped in understanding the effect of stressors on quality as well as quantity of sleep. It showed how stress leads to a shift in circadian rhythm. This led to using exercise in moderation.

The following article was pivotal in understanding the type of exercise and the duration spent by an astronaut exercising, which helped in choosing the optimal time of exercise in the overall schedule for a better quality of sleep.

“Use of the International Space Station as an Exercise Physiology Lab; https://ntrs.nasa.gov/citations/20140002851”

Project Demo

https://drive.google.com/file/d/1fpvOEHV8tF-u5Uz30XcyGcjrgFO_SK39/view?usp=sharing

Project Code

https://github.com/arshdeeptaneja/NSAC-SnoozeShift

Data & Resources

Optimal Schedules of Light Exposure for Rapidly Correcting Circadian Misalignment; Kirill Serkh and Daniel B. Forger;

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3983044/

David F Dinges, Mathias Basner, Adrian J Ecker, Pamela Baskin, Smith L Johnston, Effects of zolpidem and zaleplon on cognitive performance after emergent morning awakenings at Tmax: a randomized placebo-controlled trial, Sleep, Volume 42, Issue 3, March 2019, zsy258, https://doi.org/10.1093/sleep/zsy258

Wu, B., Wang, Y., Wu, X. et al. On-orbit sleep problems of astronauts and countermeasures. Military Med Res 5, 17 (2018). https://doi.org/10.1186/s40779-018-0165-6

Waterhouse J, Reilly T, Atkinson G, Edwards B. Jet lag: trends and coping strategies. Lancet. 2007 Mar 31;369(9567):1117-29. doi: 10.1016/S0140-6736(07)60529-7. PMID: 17398311.

Ji X, Grandner MA, Liu J. The relationship between micronutrient status and sleep patterns: a systematic review. Public Health Nutr. 2017;20(4):687-701. doi:10.1017/S1368980016002603

Kline CE. The bidirectional relationship between exercise and sleep: Implications for exercise adherence and sleep improvement. Am J Lifestyle Med. 2014;8(6):375-379. doi:10.1177/1559827614544437

Ker K, Edwards PJ, Felix LM, Blackhall K, Roberts I. Caffeine for the prevention of injuries and errors in shift workers. Cochrane Database Syst Rev. 2010;2010(5):CD008508. Published 2010 May 12. doi:10.1002/14651858.CD008508

Wirz-Justice A, Kräuchi K, Cajochen C, Danilenko KV, Renz C, Weber JM. Evening melatonin and bright light administration induce additive phase shifts in dim light melatonin onset. J Pineal Res. 2004;36(3):192-194. doi:10.1111/j.1600-079x.2004.00117.x

Sharkey KM, Eastman CI. Melatonin phase shifts human circadian rhythms in a placebo-controlled simulated night-work study. Am J Physiol Regul Integr Comp Physiol. 2002;282(2):R454-R463. doi:10.1152/ajpregu.00135.2001

Leena Tähkämö, Timo Partonen & Anu-Katriina Pesonen (2019) Systematic review of light exposure impact on human circadian rhythm, Chronobiology International, 36:2, 151-170, DOI: 10.1080/07420528.2018.1527773

Karen T. Stewart, Benita C. Hayes & Charmane I. Eastman (1995) Light Treatment for NASA Shiftworkers, Chronobiology International, 12:2, 141-151, DOI: 10.3109/07420529509064509

Physiology of Circadian Entrainment; Diego A. Golombek, and Ruth E. Rosenstein

https://doi.org/10.1152/physrev.00009.2009