Laser-Induced Graphene Sensors for Wearable Gait Recognition

In a recent paper published in Microsystems & Nanoengineering, researchers have successfully integrated a pressure sensor array made from laser-induced graphene (LIG) into wearable gait recognition sensors and exoskeleton robots, enhancing the functionality and effectiveness of these devices.

Laser-Induced Graphene Sensors for Wearable Gait Recognition
Study: Laser-Induced Graphene Sensors for Wearable Gait Recognition. Image Credit: Gorodenkoff/Shutterstock.com

Exoskeletons Robotics and Gait Recognition Technology

Exoskeleton robots are increasingly utilized across various fields, such as freight transport, healthcare, disaster relief, and rehabilitation, primarily due to their ability to enhance human capabilities. Among these, lower-limb-assisted exoskeleton robots are particularly noteworthy as they are designed to mimic the leg movements of the wearer and assist in load-bearing tasks.

Unlike industrial robotic arms, the motion trajectory of lower limb exoskeleton robots is tailored to the wearer's movement intentions and specific assistance needs rather than being rigidly preprogrammed. This customization makes gait recognition a crucial component for effective human-robot cooperation in using these devices.

For accurate gait analysis, it is essential to employ wearable sensors that gather data on pressure, velocity, and acceleration from the human foot. The advancement of flexible sensors, especially those developed using laser direct writing technology, has facilitated the creation of these wearable devices. Sensors based on LIG have significantly improved the precision of gait data, enhancing the interaction between humans and robots. This improvement is particularly valuable in the realm of rehabilitation medicine, where precise movement tracking can greatly influence therapeutic outcomes.

Fabrication of LIG-based Recognition Sensor

In this research, the team utilized a one-step laser ablation process to fabricate pressure sensors from polyamide films, using LIG. The LIG was then transferred onto various soft polymers, such as polydimethyl siloxane, ecoflex, and hydrogels, to create composites suitable for flexible devices.

For the laser ablation process, a Universal Laser System VLS 350 was employed, operating at a laser fluence ranging between 4.3 to 6.91 J/cm2 with a wavelength of 10.6 µm. This precision allowed for the efficient creation of LIG, which is critical for the sensor's performance.

To construct the intelligent insole component, silver electrodes were screen-printed onto polyamide material. The insole-shaped sensors were then shaped using a laser-cutting technique. Additionally, a specialized Input Signal Amplification (ISA) unit was developed. This unit was designed to convert and amplify the resistance measurements from the pressure sensor units across all channels into a readable voltage signal, enhancing the sensor’s functionality for gait recognition in wearable technology.

Characterization and Data Analysis

The morphology of the laser-textured LIG surface was analyzed using a thermal field emission scanning electron microscope (FE-SEM) and a 3D measuring laser microscope. Additionally, Raman spectra were obtained using a 532 nm wavelength. Electric current measurements of the pressure sensors were conducted with a digital multi-meter (Keysight, 34470A), while the pressure exerted on the sensors was dynamically measured using a compression testing machine.

Five healthy adults aged 23-31 participated in the study, with a sampling and control frequency of 100 Hz. The size of the input signal amplifier (ISA) was 20 mm×24 mm, with each module containing two amplification processing units. The authors utilized four pressure sensor units and amplified their signals.

The analog-to-digital converter (ADC) module, which included a power supply and voltage acquisition module, collected and transmitted voltage signals to the sensor network via the controller area network (CAN) bus. It measured 24 mm×50 mm, featured a 16-bit resolution, and simultaneously collected signals from eight channels within a range of -10 V to 10 V.

Gait recognition and exoskeleton robot test data was then gathered using the ISA and ADC, and data analysis was performed using MATLAB 2020b and a microcontroller unit (MCU). The study protocol received approval from the ethical committee of Zhejiang University's College of Biomedical Engineering & Instrument Science.

Observations

The study investigated a system consisting of seven strategically positioned pressure sensor units intended for monitoring plantar pressure changes throughout various gait phases, including initial contact (IC), loading response (LR), mid-stance (MS), terminal stance (TS), and swing (SW). These sensors are constructed with three layers: a PI film featuring LIG patterns, laser-textured LIG on a polydimethylsiloxane (PDMS) layer, and a poly(ethylene terephthalate) (PET) encapsulation layer, allowing for real-time identification of gait phases.

The sensing mechanism functions by detecting changes in electric current resulting from variations in the contact area between the sensor components under pressure. Through laser texturing, the pressure sensors undergo optimization for sensitivity and enhanced performance. Furthermore, thorough characterization ensures stable performance of the flexible pressure sensors over numerous cycles.

Integration of multiple LIG pressure sensor units into an intelligent insole, embedded within the shoes of an exoskeleton robot, facilitated real-time feedback on plantar pressure. The hardware system, comprising an ISA, ADC, and MCU, supports signal amplification, acquisition, and processing.

The study employed a gait recognition model based on the support vector machine (SVM) algorithm, achieving high prediction accuracy. Real-time walking experiments validated the system's effectiveness across various gait frequencies, highlighting its potential for practical applications in exoskeleton robotics.

Conclusion

In conclusion, this study introduces a wearable sensor system designed to support human-robot interaction through an exoskeleton, featuring a responsive feedback gait phase function. By employing a rapid and customized laser processing technique, the researchers successfully developed an embedded pressure sensor unit. This method enables the consistent fabrication of conductive LIG patterns on a large scale.

The integration of multiple sensor units and a printed circuit board within the insoles allows for pressure mapping, facilitating the reflection of the wearer's gait by the exoskeleton robot. Utilizing an SVM-based recognition algorithm, the system aims for highly precise gait recognition. Experimental results indicate an impressive accuracy rate of 99.85 % for the gait recognition sensor system, further confirmed by real-world exoskeleton applications, highlighting its reliability and potential impact.

Journal Reference

Sun, M., Cui, S., Wang, Z., Luo, H., Yang, H., Ouyang, X., & Xu, K. (2024). A laser-engraved wearable gait recognition sensor system for exoskeleton robots. Microsystems & Nanoengineering, 10(1), 1-9. https://doi.org/10.1038/s41378-024-00680-xhttps://www.nature.com/articles/s41378-024-00680-x

Bethan Davies

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Bethan Davies

Bethan has just graduated from the University of Liverpool with a First Class Honors in English Literature and Chinese Studies. Throughout her studies, Bethan worked as a Chinese Translator and Proofreader. Having spent five years living in China, Bethan has a profound interest in photography, travel and learning about different cultures. She also enjoys taking her dog on adventures around the Peak District. Bethan aims to travel more of the world, taking her camera with her.

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