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Smart shoes have ushered in a new era of personalised health monitoring and assistive technologies. Smart shoes leverage technologies such as Bluetooth for data collection and wireless transmission, and incorporate features such as GPS tracking, obstacle detection, and fitness tracking. As the 2010s unfolded, the smart shoe landscape diversified and advanced rapidly, driven by sensor technology enhancements and smartphones' ubiquity. Shoes have begun incorporating accelerometers, gyroscopes, and pressure sensors, significantly improving the accuracy of data collection and enabling functionalities such as gait analysis. The healthcare sector has recognised the potential of smart shoes, leading to innovations such as shoes designed to monitor diabetic foot ulcers, track rehabilitation progress, and detect falls among older people, thus expanding their application beyond fitness into medical monitoring. This article provides an overview of the current state of smart shoe technology, highlighting the integration of advanced sensors for health monitoring, energy harvesting, assistive features for the visually impaired, and deep learning for data analysis. This study discusses the potential of smart footwear in medical applications, particularly for patients with diabetes, and the ongoing research in this field. Current footwear challenges are also discussed, including complex construction, poor fit, comfort, and high cost.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11243832 | PMC |
http://dx.doi.org/10.3390/s24134301 | DOI Listing |
Sci Rep
August 2025
School of Computing, Ulster University, Belfast, BT15 1ED, United Kingdom.
A robotic exoskeleton enables individuals with limited or no mobility to engage in moderate exercises, thereby promoting physical fitness and overall well-being. However, exoskeletons alone do not provide comprehensive insights into gait pattern monitoring and analysis over time. This study proposes the integration of smart insoles as a cost-effective and non-invasive tool for gait assessment in exoskeleton-assisted rehabilitation.
View Article and Find Full Text PDFACS Appl Mater Interfaces
August 2025
George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.
Individuals experiencing gait dysfunction─such as the elderly, those with peripheral nervous system damage, or individuals with Parkinson's disease─face a heightened risk of physical injury due to imbalanced weight distribution. Despite recent advancements in wearable movement trackers, there remains a significant need for a reliable long-term plantar pressure monitoring system. While some existing devices measure pressure characteristics, many are hindered by limitations in spatial resolution, sensitivity, and the presence of bulky peripherals.
View Article and Find Full Text PDFBiosens Bioelectron
November 2025
Department of Mechanical Engineering, Kyung Hee University, Yongin, 17104, South Korea; Department of Mechanical Engineering (Integrated Engineering Program), Kyung Hee University, Yongin, 17104, South Korea. Electronic address:
In this study, an Electrical grid-independent Machine learning-assisted Wearable device for Gait analysis (EMWG) with a ground reaction force sensor is presented. For gait analysis, a multi-layer perceptron is identified as the optimal model among various Artificial Intelligence (AI) algorithms in terms of analysis performance (accuracy of 88 % and model conversion rate of 84.22 %) and power consumption (operation for 1 h 47 min with a 110 mAh battery) when deployed on a microcontroller.
View Article and Find Full Text PDFIEEE Int Conf Rehabil Robot
May 2025
Smart environments can play a crucial role in providing personalized assessment protocols for individuals. This study proposes a wearable telemonitoring system for noninvasively collecting and tracking mobility and mental effort parameters. The system consists of sensorized glasses, insoles, and AI algorithms for evaluating key metrics.
View Article and Find Full Text PDFACS Appl Mater Interfaces
May 2025
State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou 510006, China.
In recent years, wearable displays have garnered considerable attention as a crucial component of future wearable devices. Among various types of display devices, electrophoretic display (EPD) is a promising candidate for wearable devices because of its ultralow power consumption, bistability, and flexibility. However, the conventional power management scheme fails to satisfy the demands of convenience in wearable scenarios, owing to frequent charging.
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