Keywords
Full-scenario adaptation
Multimodal fusion
Rehabilitation assistance
Submitted : 2026-03-01
Accepted : 2026-03-16
Published : 2026-03-31
Abstract
In the context of accelerating global aging and the expanding population of individuals with physical disabilities, the demand for efficient assistive devices has become increasingly urgent. Addressing this pressing need, our project integrates AI technology with medical applications to develop an intelligent exoskeleton equipped with a GSM communication module and a dual-mode Beidou + GPS positioning unit. This innovative device not only enables precise posture adjustment and active safety protection but also collects real-time physiological data and gait characteristics, automatically generating rehabilitation assessment reports. To ensure technology truly serves people, we have established a user profiling database leveraging big data, enabling modular design and personalized customization for versatile applications in hospitals, communities, and homes. Through industry-academia-research collaboration, our integrated online-offline sales strategy aims to achieve financial balance by the third operational year. We are committed to helping mobility-impaired individuals regain their freedom of movement and injecting new momentum into the development of intelligent walking assistive devices.
References
World Health Organization, 2023, Global Report on Disability, visited on January 24, 2026, https://www.who.int/news-room/fact-sheets/detail/disability-and-health.
Zhang M, Li H, 2022, Analysis of the Limitations of Traditional Mobility Aids and Improvement Directions. China Journal of Rehabilitation Medicine, 37(2): 89–93.
Liu J, Wang Q, 2021, Advances and Challenges in the Application of Artificial Intelligence in Medical Rehabilitation. Journal of Artificial Intelligence, 3(4): 345–358.
Ekso Bionics, 2022, Exoskeleton Technology White Paper. Ekso Bionics Holdings, Inc., visited January 24, 2026, https://eksobionics.com/ekso-health/.
International Organization for Standardization, 2021, ISO 13485:2016 Medical Devices – Quality Management Systems. International Organization for Standardization, visited on January 24, 2026, https://standards.iteh.ai/catalog/standards/cen/2bc4b1af-f4c0-4278-9937-836553f2dbec/en-iso-13485:2016.
Ekso Bionics, 2022, Exoskeleton Technology White Paper. Ekso Bionics Holdings, Inc., visited on January 24, 2026, https://23579226.fs1.hubspotusercontent-na1.net/hubfs/23579226/German_Whitepaper_EN_Digital-2023%20(1).pdf.
Liu J, Wang Q, 2021, Advances and Challenges in the Application of Artificial Intelligence in Medical Rehabilitation. Journal of Artificial Intelligence, 3(4): 345–358.
Zhao J, Liu S, Yang H, 2023, Carbon Fiber-Titanium Alloy Composites for Lightweight Exoskeleton Structures. Composite Structures, 301: 116345.
Chen Y, Zhang X, Wang Y, 2022, A Review of Lower Limb Exoskeletons for Rehabilitation: Mechanisms, Control Strategies, and Clinical Applications. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 30: 1245–1258.
Xu M, Wang Z, Li X, 2021, Human-Machine Interaction in Rehabilitation Exoskeletons: A Systematic Review. Journal of Rehabilitation Research and Development, 58(3): 345–362.
Wang L, Li T, Zhao H, 2021, Multimodal Sensor Fusion for Gait Intent Recognition in Exoskeleton Systems. Journal of Biomechanics, 123: 110689.
Liu Z, Wang J, Li C, 2021, Integration of Beidou/GPS Positioning in Assistive Devices for Elderly Safety. Sensors, 21(19): 6542.
Wang P, Zhang Y, Chen G, 2022, GSM-Based Emergency Communication Systems for Wearable Medical Devices. Journal of Medical Systems, 46(8): 1–9.
Zhang H, Chen L, Yang Y, 2022, Dynamic Time Warping-Based Gait Recognition for Exoskeleton-Assisted Walking. IEEE Internet of Things Journal, 9(17): 14321–14330.
Li S, Liu H, Zhang Q, 2023, Federated Learning for Privacy-Preserving Gait Data Sharing in Rehabilitation. Journal of Medical Internet Research, 25(4): e45678.