Researchers have developed a fully knitted, circuit-embedded knee wearable for wireless sensing of joint motion in real time. Compared to other knitted electronics, this model has fewer externally integrated components and a more sensitive sensor, making it less error prone.
A relatively new player to the wearable systems field are wearables made from conductive fabric (CF), which are soft, lightweight, malleable, and noninvasive. These sensors are comfortable and suitable for longterm monitoring. However, most CF-based wearables become error-prone if displaced from their intended location and rely on external components that restrict the sensitivity and working range of the sensors.
To overcome these limitations, a research team created a wearable with a high degree of functional and design freedom. Associate professor Low Hong Yee and her colleagues from the Singapore University of Technology and Design (SUTD) collaborated with Dr. Tan Ngiap Chuan of SingHealth Polyclinics and published their research paper.1
Low says key considerations when designing the wearable were sensor data accuracy and reliability and for the sensor to rely on as few external components as possible. The result was a highly stretchable, fully functional sensing circuit made from a single fabric. Because the knee joint is important for lower limb mobility, the wearable was designed for the knee.
To develop this single-fabric circuit, the team mechanically coupled an electrically conductive yarn with a dielectric yarn of high elasticity in various stitch patterns. Dimensions were customized according to the subject’s leg. The functional components — sensors, interconnects, and resistors — formed a stretchable circuit on the fully knitted wearable that allowed real-time data to be obtained.
Sensors need to produce a large change in resistance for enhanced sensitivity, while interconnects and resistors need fixed resistances of the highest and lowest values, respectively. As such, the researchers optimized yarn composition and stitch type for each component before connecting the functional circuit to a circuit board contained in a pocket of the wearable, allowing for wireless transmission of real-time data.
The team assessed the knee wearable through extension-flexion, walking, jogging, and staircase activities. Subjects wore the wearable together with reflective markers that were detected by a motion capture system, allowing the comparison between sensor data and actual joint movement.
The sensor response time was less than 90 milliseconds for a step input. Additionally, the smallest change in joint angle that the sensors could detect was 0.12°. The sensor data showed strong correlation with joint movement data acquired from the motion capture system, demonstrating reliability of the sensor data.
Embedding a user-friendly sensor circuit into a soft and comfortable fabric may increase the public’s adoption of wearable technology, especially among athletes and the elderly. Data can be gathered in real-time and translated into indicators that can detect mobility decline. When signs of mobility decline are found, preventive care, prognosis, and management of the healthcare condition can be given.
Building on this work, the team intends to study the effect of sweat and humidity on sensor signals and to extend the research to include subjects from both healthy and unhealthy populations in the future. “We have started working on extending the wearable to special user groups and to monitor other body joints, such as the shoulder,” says Low. “We’re also looking at securing an incubation fund to explore the commercialization potential of the wearable.”
This work is supported by the Healthcare grant under SUTD Growth Plan at the Singapore University of Technology and Design (Grant Number SGPHCRS1905).
- Ujjaval Gupta, et al., “All knitted and integrated soft wearable of high stretchability and sensitivity for continuous monitoring of human joint motion,” Advanced Healthcare Materials (DOI: 10.1002/adhm.202202987), March 28, 2023.
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A video of the technology is available here .