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Rukmini PG, Hegde RB, Basavarajappa BK, Bhat AK, Pujari AN, Gargiulo GD, Gunawardana U, Jan T, Naik GR. Recent Innovations in Footwear and the Role of Smart Footwear in Healthcare-A Survey. SENSORS (BASEL, SWITZERLAND) 2024; 24:4301. [PMID: 39001080 PMCID: PMC11243832 DOI: 10.3390/s24134301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Revised: 06/16/2024] [Accepted: 06/27/2024] [Indexed: 07/16/2024]
Abstract
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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Affiliation(s)
- Pradyumna G. Rukmini
- Department of Electronics & Communication Engineering, NMAM Institute Technology, NITTE (Deemed to be University), Nitte 574110, India; (P.G.R.); (R.B.H.); (B.K.B.); (A.K.B.)
| | - Roopa B. Hegde
- Department of Electronics & Communication Engineering, NMAM Institute Technology, NITTE (Deemed to be University), Nitte 574110, India; (P.G.R.); (R.B.H.); (B.K.B.); (A.K.B.)
| | - Bommegowda K. Basavarajappa
- Department of Electronics & Communication Engineering, NMAM Institute Technology, NITTE (Deemed to be University), Nitte 574110, India; (P.G.R.); (R.B.H.); (B.K.B.); (A.K.B.)
| | - Anil Kumar Bhat
- Department of Electronics & Communication Engineering, NMAM Institute Technology, NITTE (Deemed to be University), Nitte 574110, India; (P.G.R.); (R.B.H.); (B.K.B.); (A.K.B.)
| | - Amit N. Pujari
- School of Physics, Engineering and Computer Science, University of Hertfordshire, Hertfordshire AL10 9AB, UK;
- School of Engineering, University of Aberdeen, Aberdeen AB24 3FX, UK
| | - Gaetano D. Gargiulo
- School of Engineering, Design and Built Environment, Western Sydney University, Penrith, NSW 2751, Australia; (G.D.G.); (U.G.)
- The MARCS Institute for Brain, Behaviour, and Development, Western Sydney University, Penrith, NSW 2751, Australia
- Translational Health Research Institute, Western Sydney University, Penrith, NSW 2751, Australia
- The Ingham Institute for Applied Medical Research, Liverpool, NSW 2170, Australia
| | - Upul Gunawardana
- School of Engineering, Design and Built Environment, Western Sydney University, Penrith, NSW 2751, Australia; (G.D.G.); (U.G.)
| | - Tony Jan
- Centre for Artificial Intelligence Research and Optimization (AIRO), Design and Creative Technology Vertical, Torrens University, Ultimo, NSW 2007, Australia;
| | - Ganesh R. Naik
- Centre for Artificial Intelligence Research and Optimization (AIRO), Design and Creative Technology Vertical, Torrens University, Ultimo, NSW 2007, Australia;
- College of Medicine and Public Health, Flinders University, Adelaide, SA 5042, Australia
- Design and Creative Technology Vertical, Torrens University, Wakefield Street, Adelaide, SA 5000, Australia
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Wang H, Basu A, Durandau G, Sartori M. A Wearable Real-time Kinematic and Kinetic Measurement Sensor Setup for Human Locomotion. WEARABLE TECHNOLOGIES 2023; 4:e11. [PMID: 37091825 PMCID: PMC7614461 DOI: 10.1017/wtc.2023.7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Current laboratory-based setups (optical marker cameras + force plates) for human motion measurement require participants to stay in a constrained capture region which forbids rich movement types. This study established a fully wearable system, based on commercially available sensors (inertial measurement units + pressure insoles) that can measure both kinematic and kinetic motion data simultaneously and support wireless frame-by-frame streaming. In addition, its capability and accuracy were tested against a conventional laboratory-based setup. An experiment was conducted, with 9 participants wearing the wearable measurement system and performing 13 daily motion activities, from slow walking to fast running, together with vertical jump, squat, lunge and single-leg landing, inside the capture space of the laboratory-based motion capture system. The recorded sensor data were post-processed to obtain joint angles, ground reaction forces (GRFs), and joint torques (via multi-body inverse dynamics). Compared to the laboratory-based system, the established wearable measurement system can measure accurate information of all lower limb joint angles (Pearson's r = 0.929), vertical GRFs (Pearson's r = 0.954), and ankle joint torques (Pearson's r = 0.917). Center of pressure (CoP) in the anterior-posterior direction and knee joint torques were fairly matched (Pearson's r = 0.683 and 0.612, respectively). Calculated hip joint torques and measured medial-lateral CoP did not match with the laboratory-based system (Pearson's r = 0.21 and 0.47, respectively). Furthermore, both raw and processed datasets are openly accessible (https://doi.org/10.5281/zenodo.6457662). Documentation, data processing codes, and guidelines to establish the real-time wearable kinetic measurement system are also shared (https://github.com/HuaweiWang/WearableMeasurementSystem).
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Affiliation(s)
- Huawei Wang
- Department of Biomechanical Engineering, University of Twente, Enschede, the Netherlands
| | - Akash Basu
- Department of Biomechanical Engineering, University of Twente, Enschede, the Netherlands
| | - Guillaume Durandau
- Department of Mechanical Engineering, McGill University, Montreal, Canada
| | - Massimo Sartori
- Department of Biomechanical Engineering, University of Twente, Enschede, the Netherlands
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Yang Y, Wei Y, Guo Z, Hou W, Liu Y, Tian H, Ren TL. From Materials to Devices: Graphene toward Practical Applications. SMALL METHODS 2022; 6:e2200671. [PMID: 36008156 DOI: 10.1002/smtd.202200671] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Indexed: 06/15/2023]
Abstract
Graphene, as an emerging 2D material, has been playing an important role in flexible electronics since its discovery in 2004. The representative fabrication methods of graphene include mechanical exfoliation, liquid-phase exfoliation, chemical vapor deposition, redox reaction, etc. Based on its excellent mechanical, electrical, thermo-acoustical, optical, and other properties, graphene has made a great progress in the development of mechanical sensors, microphone, sound source, electrophysiological detection, solar cells, synaptic transistors, light-emitting devices, and so on. In different application fields, large-scale, low-cost, high-quality, and excellent performance are important factors that limit the industrialization development of graphene. Therefore, laser scribing technology, roll-to-roll technology is used to reduce the cost. High-quality graphene can be obtained through chemical vapor deposition processes. The performance can be improved through the design of structure of the devices, and the homogeneity and stability of devices can be achieved by mechanized machining means. In total, graphene devices show promising prospect for the practical fields of sports monitoring, health detection, voice recognition, energy, etc. There is a hot issue for industry to create and maintain the market competitiveness of graphene products through increasing its versatility and killer application fields.
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Affiliation(s)
- Yi Yang
- School of Integrated Circuits & Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
| | - Yuhong Wei
- School of Integrated Circuits & Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
| | - Zhanfeng Guo
- School of Integrated Circuits & Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
| | - Weiwei Hou
- School of Materials Science and Engineering, Tsinghua University, Beijing, 100084, China
| | - Yingjie Liu
- School of Materials Science and Engineering, Tsinghua University, Beijing, 100084, China
| | - He Tian
- School of Integrated Circuits & Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
| | - Tian-Ling Ren
- School of Integrated Circuits & Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
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