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.

Hypnos

Summary

Our project aims to provide a solution to the problem of circadian misalignment and general sleep problems that contribute to a steady decline in productivity in the workplace. The application begins by retrieving information of the user beginning with basic information such as daily living habits like preferred sleeping hours, working hours, eating times, etc and ending with retrieving information from what role they will select next whether as crewmembers, mission control staff, personnel travelling internationally, or circadian misalignment. With the given information, through an algorithm, recommendations will be given to properly shift the sleep schedule of the user.

How We Addressed This Challenge

We developed a mobile application prototype where it tracks the daily activities, sleeping habits and cycles, exercising times, food intake, and team dynamics. Aside from the change in the flight conditions, we also considered the work-related assessment of the user and to the fellow crewmembers. The purpose of adding the work and team dynamics through an assessment is to provides us more information regarding one's work output. It is directly correlated with the level of stress and fatigue which affect's one's sleep cycle. One of the factors that might be overlooked in identifying the cause of Circadian Misalignment is the amount and quality of work-related performance of each individual and how they work as a team and communicate effectively.


Stages


Stage 1: User Profiling



  • Collection of person's personal information
  • Identifying the role as a user or admin
  • User roles: Crew Members and Travelers*
  • Admin roles: Flight Operation Officer, Health Supervisor/Physician, and Crew Support


Stage 2: Daily Assessment



  • Two types of assessment: Before and after sleep
  • Type A (After Sleeping): Sleep Quality, Mood, Nightmare and Snoring Check, Final Out of Bed Time (FOB), Initial in Bed Time (IIB)
  • Type B (Before Sleeping): Part 1: Self-Assessment and Part 2: Work Environment and Team Dynamics
  • Part 1: Level of Stress and Fatigue, Level of Sleepiness, Medications, and taken countermeasures
  • Part 2: Level of work-related stress, Assessment of workload of crewmembers and communication effectiveness


Stage 3: Analysis and Prediction

  • Use of machine learning to analyze the daily assessment patterns
  • Integration of pre-existing user data (Personal data, Flight schedule, Travel History, Medical Records) and daily assessment.


Stage 4: Recommendation System

  • Sleep shifting recommendations based on the analysis and prediction (Time to sleep, Temperature adjustment, Exercise duration, Eating duration, Screen time, Light scheduling and control)


Stage 5: Secondary Analysis

  • Tracking of the significant improvements of sleep cycle and circadian rhythm based on the recommendation systems


Stage 6: Intervention of Health Professionals

  • Recurring Circadian Misalignment
  • Detection of sleeping disorders and health-related issues



The application have the following main features:


A. Countermeasures Feature

The application addresses the sleep concerns of the user by first retrieving information that will allow the application to give appropriate countermeasures and recommendations. Each role will be asked specific types of information.


1.For Crewmembers

Crewmembers are individuals in high-risk occupations that have to perform optimally. There is a steady decline in productivity when these individuals experience lack of sleep or poor sleep quality. It recommends the user through processing data given by the user. The type of data specially requested for crewmembers is the nature of the mission whether landing, launching, docking, and undocking as well as the time table of the mission. 


2.For Mission Control

Mission control works on different shifts and their line of work can be detrimental to their sleep quality. With this in mind, the application retrieves the information specifically on their shifts. The dates and times of mission control shift work schedules as well as normal workload schedules.


3.For Personnel Travelling Internationally 

The information asked from personnel travelling internationally to complete missions are the following: Departure from (city and airport), Arrival to (city and airport), layover times, departure time, arrival time, and preferred sleep. 


With this information, the application can generate recommendations beforehand so that the user easily adapts their circadian rhythm to any changes. 


4.For Circadian Misalignment

Lastly for problems on circadian misalignment. Information asked will be a self-assessment survey regarding the quality of sleep known as the Pittsburgh Sleep Quality Index. The application will then give information to try and address the problems. However if problems persist, then the information provided may be vital in assisting health professionals assess the situation.


B. Prepare to sleep feature and Sleep History feature

The Prepare to Sleep gives the users the capability to give data on their sleep before and after. This allows users to assess the conditions before sleep, such as levels of fatigue, type of emotion felt, etc, and post sleep such as quality of sleep and hours of sleep. Over time this will form data which the user can check in the Sleep History feature which displays gathered data through graph form. In real time, this will affect the Countermeasure feature in terms of recommending effective techniques for the user.


C. Teams feature

This feature will allow entire teams to give their Sleep History data to a single supervisor or person-in-charge. This will encourage supervisors to have stronger footing in sleep leadership wherein they can compare their performance to their Sleep History as well as what countermeasures are being used. This will empower the supervisors to be able to detect any necessary changes or adjustments in order to further improve the wellbeing of the employees. 


Our project aims to provide a better structure for analyzing one's sleeping patterns through several datasets including

How We Developed This Project

We relate to the struggle of people trying to concentrate under conditions where sleep is scarce. Our entire group being made up of just students believe that proper management to one’s fatigue is important in any line of work. 


Tools used:


  • Framer for the interactive prototype
  • App.diagram for the wireframe
  • iMovie for the demonstration
  • Photoshop and Illustrator for the logos and illustrations


Our approach to this project is through first understanding how an autonomous system can assist busy working people that need to take up different roles. Our next approach is through understanding the dynamics of a working crew and how that could also affect their fatigue as a whole. 


Problems we encountered is lack of expertise and experience in developing working prototypes. Another problem we encountered is lack of data of the sleep of astronauts. Since almost all data will be coming from the real-time data that will be used for the predictive models, we had a hard time figuring out what kind of data which we will be integrating and utilizing. At the same time, it is very difficult to correlate these data without prior studies.


The assessment part which is divided into two parts composed of the self-assessment and team dynamics needed a standardized survey which may contain unreliable data because it is solely based on the astronaut’s opinion.


Given the problems that we encountered, there are some further recommendations that we need to address.


  • To understand the different datasets from the technologies present in the astronauts, specifically in the ISS, more to devise an effective analysis which will give a better prediction
  • To implement the similar method in a different setting such as normal travellers, high-risk jobs employees, and people who are adjusting to a new environment such as people working in extreme weather conditions (ex. Scientists in Antarctica)
How We Used Space Agency Data in This Project

In our project, there are two types of data that will be used for the predictive models for suggestion. The first type of data is coming from the user through the pre-existing data coming from the mission control regarding the crew member’s space mission schedule, daily activities, past travel history and medical records. Aside from these, the data from the assessments performed before and after sleeping will be continuously analyzed on a real time basis. Some past data from the previous space missions will also be integrated in the predictive models. 


  1. Evidence Report: Risk of Performance Decrements and Adverse Health Outcomes Resulting from Sleep Loss,Circadian Desynchronization, and Work Overload


The second type of data is coming from the technology and instruments available to NASA astronauts. 

Sleepwear 

  • Detection of cardiac mechanism including the relaxation and contraction times


Smartwatch 

  • Can be integrated with the mobile application in our project to give notifications for the recommendations and countermeasures


ISS Dynamic Lighting Schedule

  • Can be integrated to adjust the lighting for hues more appropriate for sleep


Respironics Actigraphy Sleep Data

  • Tracking of daily sleep log, quality of sleep, and ambient light levels


ISS Fit [application]

  • Tracking of daily food consumption 


Data from Cycle Ergometer, Treadmill, and Weight lifting machine

  • Tracking the daily exercise time through these equipment
  • Configuration of pre-programmed exercise based on the prescriptions


Project Demo

Demo [Youtube link]

Framer:https://framer.com/share/tykM6xrWIibisIyDUWXc/E66bpI8fS?fullscreen=1

Wireframe

Data & Resources

Sleepwear: https://www.nasa.gov/mission_pages/station/research/news/b4h-3rd/it-sleepwear-with-purpose


Treatment for Shift Work disorder:

https://www.sleepfoundation.org/shift-work-disorder/treatment


ISS Dynamic Lighting Schedule:

https://catalog.data.gov/dataset/the-iss-dynamic-lighting-schedule-an-in-flight-lighting-countermeasure-to-facilitate-circa


ISS Tracker:

http://www.isstracker.com/


An Astronaut's Work

https://www.nasa.gov/audience/forstudents/9-12/features/F_Astronauts_Work.html#:~:text=The%20ISS%20crew%20spends%20their,for%20long%20periods%20of%20time.


Sleep, performance, circadian rhythms, and light-dark cycles during two space shuttle flights

https://journals.physiology.org/doi/full/10.1152/ajpregu.2001.281.5.R1647?view=long&pmid=11641138&


Self Sleep Assessment Methods

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5971842/


Pittsburgh Sleep Quality Index

https://www.aurora.edu/documents/wellness/toolbox/assessment.pdf


Profiling

https://www.researchgate.net/figure/Age-distribution-for-astronauts-and-cosmonauts-all-nationalities-for-first-transit-to_fig3_266247037


Circadian misalignment affects sleep and medication use before and during spaceflight

https://www.nature.com/articles/npjmgrav201519.pdf?origin=ppub


Video References:

Bedtime in space - Canadian Space Agency

https://www.youtube.com/watch?v=yNgMzNN23kE&list=PLtwcmqkVIdCPtQD7Od5xO-85P9oUn1G4M&index=2


Falling Asleep in Church

https://www.youtube.com/watch?v=6B1V1PFsyho


Space Station Live: Space Zzzzzs - Nasa Johnson

https://www.youtube.com/watch?v=SDfTJA9KsXY&list=PLtwcmqkVIdCPtQD7Od5xO-85P9oUn1G4M&index=5


Tennis in Space - Nasa Johnson

https://www.youtube.com/watch?v=uE4k4P1nKuk&list=PLtwcmqkVIdCPtQD7Od5xO-85P9oUn1G4M&index=10


Sleeping in Space - Canadian Space Agency

https://www.youtube.com/watch?v=UyFYgeE32f0&list=PLtwcmqkVIdCPtQD7Od5xO-85P9oUn1G4M


Pizza Night! - NASA Johnson

https://www.youtube.com/watch?v=z74OwRy8o9I&list=PLtwcmqkVIdCPtQD7Od5xO-85P9oUn1G4M&index=11

4 Hours On Space Station - 3 Sunrises, 3 Sunsets | Time-Lapse Video

https://www.youtube.com/watch?v=18t3uQZD2po


Karen Nyberg Shows How You Wash Hair in Space - NASA Johnson

https://www.youtube.com/watch?v=uIjNfZbUYu8&list=PLtwcmqkVIdCPtQD7Od5xO-85P9oUn1G4M&index=13


Chris Hadfield’s Space Kitchen - Canadian Space Agency

https://www.youtube.com/watch?v=AZx0RIV0wss&list=PLtwcmqkVIdCPtQD7Od5xO-85P9oUn1G4M&index=3


Running in Space! - Nasa Johnson

https://www.youtube.com/watch?v=_ikouWcXhd0&list=PLtwcmqkVIdCPtQD7Od5xO-85P9oUn1G4M&index=9




Tags
#SleepShiftSchedulingTool #Manila #Hypnos #DreamCosmos #DreamCosmosHypnos
Judging
This project was submitted for consideration during the Space Apps Judging process.