Overview of SleepSpace's Science and Technology

SleepSpace's Background and Ethos

SleepSpace believes in open science and that the revolution in sleep will happen when we start taking sleep detection algorithms out of their black boxes and sharing them with the research and clinical world. That is why we teamed up with the National Institute of Aging, Penn State, and the University of Arizona to create new sleep measurement technologies and publishing our findings in peer reviewed journals. Our primary interest is in using wearable and nearable sleep technology to accurately measure and then enhance sleep. Once we know what stage of sleep the person is in, our proprietary technology is designed to deliver sound, light, vibration, and temperature stimulation that enhances sleep. We are in the process of combining this technology with classic cognitive behavioral therapy for insomnia for the purpose of developing a new type of sleep improvement therapy. We call this new type of therapy, SleepSpace Cognitive Behavioral Therapy.

Our focus:

1) Using wearable devices like Oura Ring and Apple Watch to measure sleep.

2) Using sounds to increase delta waves.

3) How to measure peak physical and mental alertness using simple games.

Recent Publications in Peer Reviewed Journals

Here are two recent articles validating our sleep tracking and enhancing technology, published in leading peer reviewed journals. The first article, published in the journal Sleep describes how we can accurately measure sleep on the Apple Watch, and compares various wearables including the Apple Watch, Oura Ring, Spectrum Pro, GT3X, and gold standard Polysomnography.

Roberts, D. M., Schade, M. M., Mathew, G. M., Gartenberg, D. I., & Buxton, O. M. (2020). Detecting Sleep Using Heart Rate and Motion Data from Multisensor Consumer-Grade Wearables, Relative to Wrist Actigraphy and Polysomnography. Sleep. PDF

This article describes how sound can be used in a laboratory environment to increase the duration and power of delta waves, the brainwaves associated with deep sleep.

Schade, M. M., Mathew, G. M., Roberts, D. M., Gartenberg, D. & Buxton, O. M. Enhancing Slow Oscillations and Increasing N3 Sleep Proportion with Supervised, Non-Phase-Locked Pink Noise and Other Non-Standard Auditory Stimulation During NREM Sleep (2020). Nature and Science of Sleep. PDF

Open Data is Our Ethos

We believe in open data and science at SleepSpace. The below poster summarizes our sleep detection work, presented at the Behavioral Sleep Medicine first annual conference.

We have received grants from the National Science Foundation and the National Institute of Health to validate our innovative way of accurately measuring sleep and actually improving your sleep quality. We don’t believe in taking a cookie cutter approach to sleep improvement. Instead we give personalized feedback based on each person’s unique sleep situation. Whether that means figuring out their best schedule, helping them feel more alert throughout the day, or optimizing their sleep for intense physical performance. A good night’s sleep sets each person up for success the next day. Our app includes a new technique of making your sleep deeper with a special sound that we play at the right stage of your sleep. This helps you feel more rested and rejuvenated the next day.

Sleep is the Foundation

SleepSpace is changing sleep culture in our society and training people in how to apply the methods we’ve developed to improve their sleep. We aim to establish a new generation of analytically-minded sleep coaches and spread the idea of sleep being thought of as one of the three parts of the foundation of good health, along with diet and exercise.

Our innovative technology, scientific method, and holistic approach to sleep are what enable us to stand apart from the rest.

Custom Sleep Tools

With the constant stresses and hustle of life today, humans don’t know what sleep is anymore. More people have sleep problems today than ever before and many people try a lot of gimmicks to try to improve their sleep, which results in little improvement and more stress. SleepSpace helps these people understand their unique sleep needs and what they can do to improve their sleep health and well-being, while keeping each individual’s daily schedule demand and lifestyle in mind. We provide customized sleep improvement plans that fit each individual’s life.

Our Journal Articles

Gartenberg, D., Gunzelmann, G., Hassanzadeh-Behbahani, S., & Trafton, J. G. (accepted). Examining the role of task requirements in the magnitude of the vigilance decrement, Frontiers in Psychology (doi: 10.3389/fpsyg.2018.01504) PDF

Brunet, J. F., Dagenais, D., Therrien, M., Gartenberg, D., & Forest, G. (2017). Validation of sleep-2-Peak: A smartphone application that can detect fatigue-related changes in reaction times during sleep deprivation. Behavior Research Methods, 49, 4, 1460-1469. PDF

Youmans, R. J., Smith, M. A., Gartenberg, D., Sarbone, B., Liu, S., Higgins, J., Lee, P., Penaranda, N., & Liu, S. (2014). FleetTM: A distributed information gathering and processing system for the alleviation of commercial air travel anxiety. The Journal of Air Traffic Control, 56, 1, 32-38. PDF

Gartenberg, D., & Thornton, R., Mortazavi, M., Pfannenstiel, D., Taylor, D., & Parasuraman, R. (2013). Collecting health-related data on the smart phone: mental models, cost of collection, and perceived benefit of feedback. Pers Ubiquit Comput, 17, 3, 561-570. PDF

Dissertation

Gartenberg, D. (2016). A Comprehensive Computational Model of Sustained Attention (Doctoral dissertation). Retrieved from ProQuest Dissertations and Theses. Advisor: Greg Trafton, Committee: Glenn Gunzelmann, Tyler Shaw, & Patrick McKnight.PDF

Conferences, Chapters, and Posters

Roberts, D. M., Schade, M. M., Mathew, G. M., Gartenberg, D, & Buxton, O. H (2019). Development of a momentary sleep versus wake classification algorithm using balanced data from two multisensor consumer wearable devices. Birmingham, AL: Society of Behavioral Sleep Medicine. PDF

Schade, M. M., Roberts, D. M., Gartenberg, D, Mathew, G. M., & Buxton, O. H (2018). Auditory stimulation during sleep transiently increases delta power and all-night proportion of NREM stage 3 sleep while preserving total sleep time and continuity. San Diego, CA: Society for Neuroscience. PDF

Brunet, J., Therrien, M., Hebert, K., Tzivanapoulos, N., Gartenberg, D., & Forest, G (2015). Greater decline in reaction time performance on a smartphone application during sleep deprivation is linked to extraversion.In Proceedings of the 29th annual meeting of the Associated Professional Sleep Societies. PDF

Gartenberg, D., Gunzelmann, G., Veksler, B., & Trafton, J. G. (2015). Improving vigilance analysis methodology: Questioning the successive versus simultaneous distinction. In Proceedings of 59th annual meeting of the Human Factors and Ergonomics Society. PDF

Brunet, J., Therrien, M., Gartenberg, D., & Forest, G (2014). Validation of a smartphone psychomotor vigilance application: Preliminary Data. In Proceedings of the 28th annual meeting of the Associated Professional Sleep Societies. PDF

Gartenberg, D., Veksler, B., Gunzelmann, G., & Trafton, J. G. (2014). An ACT-R process model of the signal duration phenomenon of vigilance. In Proceedings of 58th annual meeting of the Human Factors and Ergonomics Society. PDF

Youmans, R. J., Smith, M. A., Gartenberg, D., Liu, S., Higgins, J., Penaranda, N., & Sarbone, B. (2013). FleetTM: A Distributed Information Gathering and Processing System for the Alleviation of Commercial Air Travel Anxiety. Proceedings of the 58th Air Traffic Control Association’s Annual Conference & Exposition, Washington, DC. PDF

Therrien, M., Hebert, M., Gartenberg, D., De Koninck, J., & Forest, G (2013). Awareness of reaction time variations with sleep schedule measured on a smartphone can improve sleep habits and performance. In Proceedings of the 27th annual meeting of the Associated Professional Sleep Societies. PDF

Hebert, M., Gartenberg, D., De Koninck, J., & Forest, G, Therrien, M. (2013). Alertness measured by average reaction time on a smartphone predicts physical performance. In Proceedings of the 27th annual meeting of the Associated Professional Sleep Societies. PDF

Gartenberg, D., Forest, G., & Therrien, M. (2012). A smartphone PVT application is successfully used to identify one’s sleep schedule associated with better daytime alertness. Associated Professional Sleep Societies.PDF

Therrien, M., Hebert, M., Gartenberg, D., De Koninck, J., & Forest, G (2012). High correlation and predictive value between alertness measured by reaction time and physical performance. Associated Professional Sleep Societies. PDF

Eisert, J., Gartenberg, D., Thornton, R., & Youmans, R. (2012). Optimal interface location and limits of gesture proficiency in an automobile. In Proceedings of 56th annual meeting of the Human Factors and Ergonomics Society. PDF

Gartenberg, D. McGarry, R., Phannenstiel, D., Cisler, D., Shaw, T., & Parasuraman, R. (2012). Development and evaluation of a neuroergonomic smart phone application to assess vigilance and arousal. 4th International Conference on Applied Human Factors and Ergonomics. PDF

Gartenberg, D. & Parasuraman, R. (2010). Understanding Brain Arousal and Sleep Quality Using a Neuroergonomic Smart Phone Application. In Marek, T., Karwowski, W., & Rice, V. (Eds.), Advances in Understanding Human Performance, 3rd International Conference on Applied Human Factors and Ergonomics (pp. 210-220). PDF