References

[1] Abreu, C., Bédard, C., Lourme, J.-C., & Piro, B. (2026). Wearable sensors for health monitoring. Biosensors, 16(2), 93.
https://doi.org/10.3390/bios16020093

[2] Al-Haddad, S. A., et al. (2020). IoT-based health monitoring system using ESP32. Journal of Physics: Conference Series, 1502(1), 012005.
https://www.jetir.org/papers/JETIR2505636.pdf

[3] Al‑Qahtani, A. M., Ali, S., Khan, A., & Bermak, A. (2023). Performance optimization of wearable printed human body temperature sensor based on silver interdigitated electrode and carbon‑sensing film. Sensors, 23(4), 1869.
https://doi.org/10.3390/s23041869

[4] Berry, R. B., Budhiraja, R., Gottlieb, D. J., Gozal, D., Iber, C., Kapur, V. K., Marcus, C. L., Mehra, R., Parthasarathy, S., Quan, S. F., Redline, S., Strohl, K. P., Ward, S. L. D., & Tangredi, M. M. (2012). Rules for scoring respiratory events in sleep: Update of the 2007 AASM manual. Journal of Clinical Sleep Medicine, 8(5), 597–619.
https://doi.org/10.5664/jcsm.2172

[5] Birrer, V., Elgendi, M., Lambercy, O., et al. (2024). Evaluating reliability in wearable devices for sleep staging. npj Digital Medicine, 7, 74.
https://doi.org/10.1038/s41746-024-01016-9

[6] Charlton, P. H., et al. (2016). An assessment of algorithms to estimate respiratory rate from the electrocardiogram and photoplethysmogram. Physiological Measurement, 37(4), 610–626.
https://doi.org/10.1088/0967-3334/37/4/610

[7] de Zambotti, M., Cellini, N., Goldstone, A., Colrain, I. M., & Baker, F. C. (2019). Wearable sleep technology in clinical and research settings. Medicine & Science in Sports & Exercise, 51(7), 1538–1557.
https://doi.org/10.1249/MSS.0000000000001947

[8] Dinh-Le, C., Chuang, R., Chokshi, S., & Mann, D. (2019). Wearable health technology and EHR integration. JMIR mHealth and uHealth, 7(9), e12861.
https://doi.org/10.2196/12861

[9] Dobson, R., Stowell, M., Warren, J., Tane, T., Ni, L., Gu, Y., McCool, J., & Whittaker, R. (2023). Use of consumer wearables in health research: Issues and strategies. Journal of Medical Internet Research, 25, e52444.
https://doi.org/10.2196/52444

[10] Elgendi, M. (2019). The use of PPG for assessing hypertension. NPJ Digital Medicine, 2, 60.
https://doi.org/10.1038/s41746-019-0136-7

[11] Elgendi, M., Markov, K., Liu, H., et al. (2026). Wearable devices for anxiety assessment: a systematic review. Communications Medicine, 6, 20.
https://doi.org/10.1038/s43856-025-01234-6

[12] Espressif Systems — Embedded systems and battery monitoring application notes. Hercog, D., Lehrer, T., Truntič, M., & Težak, O. (2023). Design and implementation of ESP32-based IoT devices. Sensors, 23(15), 6739.
https://doi.org/10.3390/s23156739

[13] Evenson, K. R., Goto, M. M., & Furberg, R. D. (2015). Systematic review of the validity and reliability of consumer-wearable activity trackers. International Journal of Behavioral Nutrition and Physical Activity, 12, 159.
https://doi.org/10.1186/s12966-015-0314-1

[14] Fornelli, C., et al. (2024). Accuracy of Fitbit Charge 4, Garmin Vivosmart 4, and WHOOP versus polysomnography: Systematic review. JMIR mHealth and uHealth.
https://mhealth.jmir.org/2024/1/e52192

[15] Halder, J., et al. (2020). Microneedle array: Applications, recent advances, and clinical pertinence in transdermal drug delivery.
https://doi.org/10.1007/s12247-020-09460-2

[16] Henriksen, A., et al. (2020). Reliability and validity of commercially available wearable devices for measuring steps, energy expenditure, and HR: Systematic review. JMIR mHealth and uHealth.
https://mhealth.jmir.org/2020/9/e18694/

[17] Canali, S., Schiaffonati, V., & Aliverti, A. (2022). Challenges and recommendations for wearable devices in digital health: Data quality, interoperability, health equity, fairness. PLOS Digital Health, 1(10), e0000104.
https://doi.org/10.1371/journal.pdig.0000104

[18] Hu, X., et al. (2024). From lab to life: Evaluating the reliability and validity of psychophysiological data from wearable devices in laboratory and ambulatory settings. Behavior Research Methods.
https://link.springer.com/epdf/10.3758/s13428-024-02387-3

[19] Kashaninejad, N., Munaz, A., Moghadas, H., Yadav, S., Umer, M., & Nguyen, N.-T. (2021). Microneedle arrays for sampling and sensing skin interstitial fluid. Chemosensors, 9(4), 83.
https://doi.org/10.3390/chemosensors9040083

[20] Kim, J., Jeerapan, I., Imani, S., Cho, T. N., Bandodkar, A., Cinti, S., Mercier, P. P., & Wang, J. (2016). Noninvasive alcohol monitoring using a wearable tattoo-based iontophoretic-biosensing system. ACS Sensors, 1(1), 1011-1019.
https://doi.org/10.1021/acssensors.6b00356

[21] Kumar, S., Buckley, J. L., Barton, J., Pigeon, M., Newberry, R., Rodencal, M., Hajzeraj, A., Hannon, T., Rogers, K., Casey, D., O'Sullivan, D., & O'Flynn, B. (2020). A wristwatch-based wireless sensor platform for IoT health monitoring applications. Sensors, 20(6), 1675.
https://doi.org/10.3390/s20061675

[22] Lodewyk, K., Wiebe, M., Dennett, L., Larsson, J., Greenshaw, A., & Hayward, J. (2025). Wearables research for continuous monitoring of patient outcomes: A scoping review. PLOS Digital Health, 4(5), e0000860.
https://doi.org/10.1371/journal.pdig.0000860

[23] Lui, J. H. Y., et al. (2022). The Apple Watch for monitoring mental health–related physiological symptoms: Literature review. JMIR Mental Health.
https://mental.jmir.org/2022/9/e37354

[24] Ma, G., et al. (2023). Microneedle-based interstitial fluid extraction for drug analysis. TrAC Trends in Analytical Chemistry, 158, 116845.
https://doi.org/10.1016/j.trac.2022.116845

[25] Mohan, A. M. V., Windmiller, J. R., Mishra, R. K., & Wang, J. (2017). Continuous minimally-invasive alcohol monitoring using microneedle sensor arrays. Biosensors and Bioelectronics, 91, 574-579.
https://doi.org/10.1016/j.bios.2017.01.016

[26] Penttilä, T. (2018). Diabetes self-management application for Apple Watch [Bachelor's thesis, Metropolia University of Applied Sciences].
https://www.theseus.fi/bitstream/handle/10024/157531/penttila_topi.pdf

[27] Pimentel, M. A. F., et al. (2016). Toward a robust estimation of respiratory rate from pulse oximeters. IEEE Transactions on Biomedical Engineering, 63(8), 1975–1984.
https://doi.org/10.1109/TBME.2016.2530426

[28] Sanders, G. J., et al. (2022). Accuracy and precision of energy expenditure, HR, and steps measured by combined-sensing Fitbits against reference measures: Systematic review and meta-analysis. PMC.
https://pmc.ncbi.nlm.nih.gov/articles/PMC9047731/

[29] Sarkar, A. S., Biswas, D., Chatterjee, S., & Majumder, S. (2019). Wearable sensors for monitoring RR: A review. Journal of Medical Engineering & Technology, 43(7), 1–15.
https://pmc.ncbi.nlm.nih.gov/articles/PMC6426305/

[30] Sarkar, A. S., et al. (2022). The Use of Wearable Pulse Oximeters in the Prompt Detection of Hypoxemia: Diagnostic Accuracy Study. Journal of Medical Internet Research, 24(2), e28890.
https://www.jmir.org/2022/2/e28890

[31] Schmidt, P., Reiss, A., Dürichen, R., Marberger, C., & Van Laerhoven, K. (2018). Introducing WESAD, a multimodal dataset for wearable stress and affect detection. In Proceedings of ICMI 2018.
https://doi.org/10.1145/3242969.3242985

[32] Seneviratne, S., et al. (2017). A Survey of Wearable Devices and Challenges. IEEE Communications Surveys & Tutorials, 19(4), 2573–2620.
https://www.researchgate.net/publication/318717275

[33] Shaffer, F., & Ginsberg, J. P. (2017). An overview of HRV metrics and norms. Frontiers in Public Health, 5, 258.
https://doi.org/10.3389/fpubh.2017.00258

[34] Sinichi, T. (2025). Quality in question: Assessing the accuracy of four HR wearables and the implications for psychophysiological research. Psychophysiology.
https://onlinelibrary.wiley.com/doi/10.1111/psyp.70004

[35] SparkFun Electronics. (n.d.). SparkFun Pulse Oximeter and HR Sensor – MAX30101 & MAX32664 (Qwiic).
https://www.sparkfun.com/sparkfun-pulse-oximeter-and-heart-rate-sensor-max30101-max32664-qwiic.html

[36] Sun, Y., Chen, J., Ji, M., & Li, X. (2025). Wearable technologies for health promotion and disease prevention in older adults: Systematic scoping review and evidence map. Journal of Medical Internet Research, 27, e69077.
https://doi.org/10.2196/69077

[37] Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. (1996). HRV: Standards of measurement, physiological interpretation, and clinical use. Circulation, 93, 1043–1065.
https://doi.org/10.1161/01.CIR.93.5.1043

[38] Tehrani, F., et al. (2022). An integrated wearable microneedle array for the continuous sensing of hemodynamically relevant biomarkers. Nature Biomedical Engineering, 6(11), 1345-1357.
https://doi.org/10.1038/s41551-022-00955-3

[39] Tehrani, F., Teymourian, H., Wuerstle, B., Yao, J., Beyzavi, M., Lu, J., Haghayegh, S., Andrews, A. P., Chawla, M. S., Rogers, J. A., & Gutruf, P. (2022). An integrated wearable microneedle array for the continuous monitoring of multiple biomarkers in interstitial fluid. Nature Biomedical Engineering, 6(11), 1214–1224.
https://doi.org/10.1038/s41551-022-00887-1

[40] TensorFlow Lite Micro documentation. (n.d.). Warden, P., & Situnayake, D. (2019). TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers. O'Reilly Media.
https://books.google.ca/books?id=tn3EDwAAQBAJ

[41] The Momentum. (2025). Why health apps need native access to wearable data.
https://www.themomentum.ai/blog/why-health-apps-need-native-access-to-wearable-data

[42] Van Hees, V. T., et al. (2018). Estimating sleep parameters using an accelerometer without sleep diary. Scientific Reports, 8(1), 12975.
https://www.nature.com/articles/s41598-018-31266-z

[43] Vo, D.-K., & Trinh, K. T. L. (2024). Advances in wearable biosensors for healthcare: Current trends, applications, and future perspectives. Biosensors, 14(11), 560.
https://doi.org/10.3390/bios14110560

[44] Walch, O., Huang, Y., Forger, D., & Goldstein, C. (2019). Sleep stage prediction with raw acceleration and PPG, HR data derived from a consumer wearable device. Sleep, 42(12), zsz180.
https://doi.org/10.1093/sleep/zsz180

[45] Yang, J., Gong, X., Zheng, Y., Duan, H., Chen, S., Wu, T., Yi, C., Jiang, L., & Haick, H. (2025). Microneedle-based integrated pharmacokinetic and pharmacodynamic evaluation platform for personalized medicine. Nature Communications, 16(1), Article 6260.
https://doi.org/10.1038/s41467-025-61549-9

[46] Zhang, S., et al. (2021). A wearable wireless and skin-interfaced microfluidics sensing patch for on-site biomarker monitoring. Biosensors and Bioelectronics, 175, 112844.
https://www.sciencedirect.com/science/article/abs/pii/S0956566320308307