Teaching and Learning Innovation in Management of Technology and Innovation: Ringgy
Keywords:
Wearable Technology, Emotional Monitoring, Smart Ring, AI Health Assistant, Mental Well-beingAbstract
Ringgy is an AI-powered wearable ring designed to monitor users’ physical and emotional well-being in real time. Equipped with advanced biometric sensors, including PPG and IMU technology, it tracks heart rate, stress, fatigue, inactivity, and emergency incidents such as falls or fainting. Ringgy provides discreet feedback through gentle vibrations and LED indicators, reducing digital fatigue with its screen-free design. The device also features emergency hand signal recognition, enabling automatic SOS alerts and live location sharing via smartphone connection. With water-resistant, energy-efficient, and gender-neutral features, Ringgy supports daily use for professionals, elderly individuals, and wellness-focused users while promoting proactive health and safety management.
References
Alsubhi, A., Anaraky, R. G., & Babatunde, S. (2024). User-cantered perspectives on the design of battery less wearables: Implications for mental health support and emotional well-being. International Journal of Human–Computer Interaction. Retrieved from https://www.researchgate.net/publication/375844673_UserCentered_Perspectives_on_the_Design_of_Batteryless_Wearables
Chieng, K. F., & Mustapa, F. D. (2021). Smart Living Implementation in Malaysia: A Preliminary Overview. Journal of Information System and Technology Management, 24(12), 107–119.
Chisi, T. F. T. (2019). Determining the potential of wearable technologies within the disease landscape of sub-Saharan Africa (Master’s thesis, Stellenbosch University). Retrieved from https://scholar.sun.ac.za/bitstream/10019.1/105788/1/chisi_potential_2019.pdf
Collewijn, M. A. (2024). Designing an Extimate Wearable: Generative AI and biometric feedback in smart rings for well-being (Bachelor’s thesis, University of Twente). Retrieved from http://essay.utwente.nl/103182/
Cutrona, V., & Rozanec, J. M. (2024). Manufacturing workers fatigue: an exploratory study on predictive machine learning and cross-subject generalization with implications for work design. Smart Health, 30, 100216. Retrieved from https://research.rug.nl/files/1130049706/1-s2.0- S2405896324017002-main.pdf
Dehankar, P., & Das, S. (2025). Wearable health technology—a perspective. In P. Mishra et al. (Eds.), Navigating the landscape of intelligent technologies (pp. 27–42). Springer. https://doi.org/10.1007/978-3-031-76152-2_3
Dervis, V. (2025). Safety at the frontline: Innovative strategies for reducing health hazards in the gas and petroleum industry. Open Journal of Respiratory Diseases, 15(2), 152–166. Retrieved from https://www.scirp.org/pdf/ojrd2025152_22110280.pdf
Irshad, R. R., Hussain, S., Hussain, I., Nasir, J. A., & Zeb, A. (2023). IoT-enabled secure and scalable cloud architecture for multi-user systems: A hybrid post-quantum cryptographic and blockchain-based approach. IEEE. Retrieved from https://ieeexplore.ieee.org/abstract/document/10261941/
Liu, X., & Zhang, J. (2024). Continuous glucose monitoring in prediabetes management: A comprehensive perspective. Frontiers in Endocrinology, 15, Article 1472898. https://doi.org/10.3389/fendo.2024.1472898
Panadés, R., & Yuguero, O. (2025). Cyber-bioethics: The new ethical discipline for digital health. Frontiers in Digital Health, 5, Article 1523180. https://doi.org/10.3389/fdgth.2024.1523180
Sekhri, A., & Ranawat, R. (2024). Gender specific tools and technologies. ResearchGate. Retrieved from https://www.researchgate.net/publication/389441827_Gender_Specific_Tools_and_Technologies
Shalawadi, S. B. (2025). Shaping user privacy experiences in self-tracking and smart homes: A design artifact approach (PhD thesis, Aalborg University). Retrieved from https://vbn.aau.dk/files/784094476/PHD_SBS_ONLINE.pdf
Soh, P. J., Vandenbosch, G. A. E., & Mercuri, M. (2015). Wearable wireless health monitoring: Current developments, challenges, and future trends. Retrieved from IEEE. https://ieeexplore.ieee.org/abstract/document/7072588
Tran, N. D. T. (2024). Contactless and Scalable Approaches for Human Health and Performance Sensing (Doctoral dissertation, Singapore Management University). Retrieved from https://ink.library.smu.edu.sg/etd_coll/661/
Venugopal, E., & Kamalakhannan, S. K. (2025). Cascaded LSTM-XGBoost model for monitoring the health and safety of platform workers. In Proceedings of the 6th International Conference on Intelligent Systems and Control. IEEE. https://doi.org/10.1109/ICISC59008.2025.10883560
Wu, J. Y., Ching, C. T. S., Wang, H. M. D., & Liao, L. D. (2022). Emerging wearable biosensor technologies for stress monitoring and their real-world applications. Biosensors, 12(12), 1097. https://doi.org/10.3390/bios12121097
Yuniarti, D., & Ariyanti, S. (2022). Towards Indonesia's integrated broadcast-broadband implementation policy: A comparative analysis of Singapore, Japan and Malaysia. Journal of Digital Media & Policy, Retrieved from https://intellectdiscover.com/content/journals/10.1386/jdmp_00041_1
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Mariam Setapa, Maharizean Che Ismail, Normala Che Omar, Sazwani Hamzah, Siti Farah Haryatie Mohd Kanafiah, Norshaieda Abdullah @ Adnan

This work is licensed under a Creative Commons Attribution 4.0 International License.