The Science

18 years of R&D,
now in your pocket.

CuesHub is powered by Stress AI: 18 years of NIH and NSF funded biosignal research, including two NIH-funded national research centers, the MD2K Center of Excellence and the mDOT Center.

18years

of biosignal AI research

$50M

NIH & NSF research

400TB

of unique data

25+

universities

Stress AI

CuesHub's Stress AI

The CuesHub app is based on Stress AI, developed over 18 years of research funded by NIH and NSF, with $50 million, including two NIH-funded national research centers: the MD2K Center of Excellence and the mDOT Center.

Cortisol

Similar correlation to self-reported stress as cortisol.

Comparison with HRV

Most stress apps, watches, and rings use Heart Rate Variability (HRV) for stress tracking.

Peer-reviewed research has shown that the correlation between HRV and self-reported stress is 0.01 [1] due to noisy data collected by wearables in natural life. The correlation between cortisol and self-reported stress, on the other hand, is between 0.2 and 0.41 [2]. CuesHub's Stress AI achieves a similar correlation of 0.28 [3].

Even in clean lab conditions, CuesHub's Stress AI significantly outperforms HRV, achieving a true positive rate of 0.84 vs. 0.55 for HRV, while reducing false positives by half [4]. The world's current best-performing biosignal foundation model is by our team [6].

Shown to reduce stress by 10% in a nationwide study [5]

Citations

Peer-reviewed research.

Numbered in order of first appearance on this page. Foundational milestones (AutoSense, cStress, MOODS, Pulse-PPG) are noted in the bibliography.

  1. 1.Booth, B. M., Vrzakova, H., Mattingly, S. M., Martinez, G. J., Faust, L., & D'Mello, S. K. (2022). Toward robust stress prediction in the age of wearables: Modeling perceived stress in a longitudinal study with information workers. IEEE Transactions on Affective Computing, 13(4), 2201-2217
  2. 2.Caparros-Gonzalez, R. A., Lynn, F., Alderdice, F., & Peralta-Ramirez, M. I. (2022). Cortisol levels versus self-report stress measures during pregnancy as predictors of adverse infant outcomes: a systematic review. Stress, 25(1), 189-212
  3. 3.Neupane, S. (2025). Feasibility and Utility of AI-Triggered Prompts for Efficiently Capturing when and Why People Experience Stress in Natural Environments. Doctoral dissertation, The University of Memphis
  4. 4.cStressHovsepian, K., Al'Absi, M., Ertin, E., Kamarck, T., Nakajima, M., & Kumar, S. (2015). cStress: towards a gold standard for continuous stress assessment in the mobile environment. Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing, 493-504
  5. 5.MOODSNeupane, S., Saha, M., Ali, N., Hnat, T., Samiei, S. A., Nandugudi, A., ... & Kumar, S. (2024). Momentary stressor logging and reflective visualizations: Implications for stress management with wearables. Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems, 1-19

    “A 10% reduction in self-reported stress intensity over the course of the nationwide MOODS field study.”

  6. 6.Pulse-PPGSaha, M., Xu, M. A., Mao, W., Neupane, S., Rehg, J. M., & Kumar, S. (2025). Pulse-ppg: An open-source field-trained PPG foundation model for wearable applications across lab and field settings. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 9(3), 1-35
  7. 7.Gaye, B., Valentin, E., Xanthakis, V., Perier, M. C., Celermajer, D. S., Shipley, M., ... & Jouven, X. (2024). Association between change in heart rate over years and life span in the Paris Prospective 1, the Whitehall 1, and Framingham studies. Scientific Reports, 14(1), 20052

    “Ten days worth of heartbeats are lost per year to unmanaged stress.”

  8. 8.Van Puyvelde, T., Janssens, K., Spencer, L., D'Ambrosio, P., Ray, M., Foulkes, S. J., ... & La Gerche, A. (2025). Balancing Exercise Benefits Against Heartbeat Consumption in Elite Cyclists. JACC: Advances, 4(10_Part_2), 102140

    “Sustained psychological strain is an independent risk factor for cardiovascular events.”

  9. 9.Agorastos, A., & Chrousos, G. P. (2022). The neuroendocrinology of stress: the stress-related continuum of chronic disease development. Molecular Psychiatry, 27(1), 502-513
  10. 10.Almeida, D. M., Marcusson-Clavertz, D., Conroy, D. E., Kim, J., Zawadzki, M. J., Sliwinski, M. J., & Smyth, J. M. (2020). Everyday stress components and physical activity: examining reactivity, recovery and pileup. Journal of Behavioral Medicine, 43(1), 108-120
  11. 11.Battalio, S. L., Conroy, D. E., Dempsey, W., Liao, P., Menictas, M., Murphy, S., ... & Spring, B. (2021). Sense2Stop: a micro-randomized trial using wearable sensors to optimize a just-in-time-adaptive stress management intervention for smoking relapse prevention. Contemporary Clinical Trials, 109, 106534
  12. 12.Chen, X. J., Barywani, S. B., Hansson, P. O., Östgärd Thunström, E., Rosengren, A., Ergatoudes, C., ... & Fu, M. L. (2019). Impact of changes in heart rate with age on all-cause death and cardiovascular events in 50-year-old men from the general population. Open Heart, 6(1), e000856
  13. 13.Chiou, S. S., Hsu, Y., Chiu, Y. H., Chou, C. C., Gill, D. L., & Lu, F. J. (2020). Seeking positive strengths in buffering athletes' life stress-burnout relationship: The moderating roles of athletic mental energy. Frontiers in Psychology, 10, 3007
  14. 14.Doerr, J. M., Nater, U. M., Ehlert, U., & Ditzen, B. (2018). Co-variation of fatigue and psychobiological stress in couples' everyday life. Psychoneuroendocrinology, 92, 135-141
  15. 15.AutoSenseErtin, E., Stohs, N., Kumar, S., Raij, A., Al'Absi, M., & Shah, S. (2011). AutoSense: unobtrusively wearable sensor suite for inferring the onset, causality, and consequences of stress in the field. Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems, 274-287
  16. 16.French, K. A., Smith, C. E., Lee, S., & Chen, Z. (2025). Can allostatic load cross over? Short-term work and nonwork stressor pile-up on parent and adolescent diurnal cortisol, physical symptoms, and sleep. Journal of Applied Psychology
  17. 17.Jensen, M. T., Suadicani, P., Hein, H. O., & Gyntelberg, F. (2013). Elevated resting heart rate, physical fitness and all-cause mortality: a 16-year follow-up in the Copenhagen Male Study. Heart, 99(12), 882-887
  18. 18.Lean, Y., & Shan, F. (2012). Brief review on physiological and biochemical evaluations of human mental workload. Human Factors and Ergonomics in Manufacturing & Service Industries, 22(3), 177-187
  19. 19.Liu, Y. Z., Wang, Y. X., & Jiang, C. L. (2017). Inflammation: the common pathway of stress-related diseases. Frontiers in Human Neuroscience, 11, 316
  20. 20.Plarre, K., Raij, A., Hossain, S. M., Ali, A. A., Nakajima, M., Al'Absi, M., ... & Wittmers, L. E. (2011). Continuous inference of psychological stress from sensory measurements collected in the natural environment. Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks, 97-108
  21. 21.Marcora, S. M., Staiano, W., & Manning, V. (2009). Mental fatigue impairs physical performance in humans. Journal of Applied Physiology, 106(3), 857-864
  22. 22.Sun, H., Soh, K. G., Roslan, S., Wazir, M. R. W. N., & Soh, K. L. (2021). Does mental fatigue affect skilled performance in athletes? A systematic review. PLOS ONE, 16(10), e0258307
  23. 23.Wilhelm, F. H., & Roth, W. T. (1998). Using minute ventilation for ambulatory estimation of additional heart rate. Biological Psychology, 49(1-2), 137-150