In a new development that could help clinicians improve the recovery of patients with movement disorders, a team of researchers at the Singapore University of Technology and Design have created a flexible knee wearable that is able to track joint motion in real-time. The new device has integrated circuitry in its structure, allowing it to track joint movement in real time. The knee wearable has the potential to help clinicians diagnose, monitor, and treat disorders affecting the musculoskeletal system, and can thus improve the quality of care for such patients in the future.
At the Singapore University of Technology and Design, a team of medical researchers have recently created a wearable device that can measure and track real-time joint movements. The team is passionate about helping people with mobility disorders and limitations, which can significantly impair people’s quality of living. Their solution is a novel one in that it is wearable, mobile, and accurate.
Typically, solutions used to track movement disorders in these patients have been non-wearable devices. While these devices are reliable and effective, their utility is not applicable outside clinical settings — non-wearable devices must be operated by clinicians and are used in controlled laboratory environments. Therefore, they are impractical in real-world situations.
On the other hand, proposed wearable solutions are known to have challenges of their own. The older systems have tended to be heavy and inflexible, limiting applicability in effective measurement of parameters in patient motion. Newer solutions are tending towards soft, lightweight conductive fabric. Conductive fabric (CF) is more malleable and mobile, but it tends to become prone to errors if it is displaced from its original location. Additionally, their working range and sensitivity is limited, as they rely on external components for the functionality of their sensors.
Taking these factors into consideration, the team has designed a functional wearable that has significant functional and design freedom. A significant concern when designing the wearable was the accuracy and specificity of the sensor, as well as solving the challenges that predecessor devices had faced. This meant that the device had to rely on as few external components as possible.
From their efforts, the team was able to devise a highly stretchable, mobile, and flexible wearable device that could be made from a single piece of fabric. The device is designed for the knee — which is critical in lower limb mobility — and forms a functional sensing circuit. Creating the circuit requires significant technical skill, which the researchers acknowledged in their report, but it is essential to the working of the device.
Associate Professor Hong Yee Low, a senior author and corresponding researcher on the study, commented on the importance of “the synergy of yarns with different electrical and mechanical properties to achieve high signal sensitivity and high stretchability.” Low holds a PhD in Macromolecular Science from Case Western Reserve University, and she currently serves as an Associate Professor at Singapore University of Technology and Design where she carries out research on micro and nano-fabrication process developments, functional surfaces based on micro- and nanoscale textures, and applications of functional surfaces.
The team published their research in the March 2023 edition of the Wiley journal Advanced Healthcare Materials. In the paper, which is titled, ‘All Knitted and Integrated Soft Wearable of High Stretchability and Sensitivity for Continuous Monitoring of Human Joint Motion,’ the researchers detailed how they created the wearable device, integrated it with suitable electrical components, and used it to measure movement.
The product is centred around the development of the e-textile, a broad group of materials which incorporate soft fabrics with embedded stretchable circuits. To develop the fabric, the researchers combined an electrically conductive yarn with a dielectric yarn using various patterns of stitching. This allowed them to incorporate multiple properties into a material of various stitch patterns, enabling both conductivity and stretchability in a single, continuous piece of fabric.
To affix the wearable to the knee — which is crucial for lower limb motion — the researchers customized the wearable to each participant’s leg, with all the components forming a unit composite that could provide data for the experiment. The sensors, interconnects, and resistors formed a stretchable circuit on the fully knitted wearable, allowing real-time measurement of data from the subjects.
Each sensor was needed to produce a large change in resistance upon application for significant sensitivity, with the interconnects and resistors providing a fixed resistance. The interconnects and resistors, respectively, were required to provide highest and lowest values of resistance against which the sensors’ changes in resistance could be measured. To achieve this, the researchers chose yarn compositions and stitch types that could optimize these properties, connecting the yarns to a central circuit board from which real-time updates could be obtained.
To test the functionality and performance of the wearable, the subjects were required to carry out a series of motions, including extension, flexion, walking, jogging, and staircase activities. The response time was about 90 milliseconds for a step input, which is enough time to effectively measure motion in real-time. Additionally, the sensors could detect angle changes as small as 0.12°, which showed strong correlation with data from the motion capture system.
The members of the team that carried out this work include Ujjaval Gupta, Jun Liang Lau, Pei Zhi Chia, Ying Yi Tan, Alvee Ahmed, Ngiap Chuan Tan, Gim Song Soh, and Associate Professor Hong Yee Low. Ujjaval Gupta, a corresponding author on this project, is a mechatronics scientist and foremost researcher that is passionate about devising cutting-edge solutions to help people with musculoskeletal disorders improve their quality of life. He is a former research fellow at the National University of Singapore, and served as a lead researcher on this project.
Gim Song Soh, another corresponding author on this project, is an associate professor at the Singapore University of Technology and Design and is a founding member of the Robotics Innovation Laboratory at the university. His research interests cut across kinematics, robotics, additive manufacturing, and biomechanics.
Movement disorders constitute a significant challenge in patients across the world, with mobility disorders acting as major signs of decline. Long-term monitoring with solutions such as theirs can help delay decline in mobility by allowing for early diagnosis and management of these conditions. The study was funded by a healthcare grant under the SUTD growth plan (Grant Number SGPHCRS1905) for the Singapore University of Technology and Design.
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