Health & Medicine, Singapore (Commonwealth Union) – Singapore University of Technology and Design (SUTD) scientists have produced a fully knitted, circuit-embedded knee wearable capable of wireless sensing of joint movement in real-time. When contrasted with other knitted electronics, this model had lesser externally integrated objects and a sensor with higher sensitivity, giving it less possibility of being error-prone.
Researchers indicated that mobility restrictions are one of the 1st stages of human mobility disability and an early sign of reduced function. It may present as muscle weakness, loss of balance, and unsteady gait, together with pain in joints. Long-term and continued tracking of joint motion could possibly avoid or delay decline by paving the way for the early diagnosis, prognosis, as well as management of mobility-associated conditions.
This long-term as well as the continued tracking is made possible by the evaluation systems that can be non-wearable or wearable. The Non-wearable systems are dependable, but need a lab-based atmosphere along with trained individuals and are hence impractical for everyday applications. Whereas wearable systems are portable, more economical, and with greater simplicity to utilize. The issue has been that, typical wearable sensors are generally inflexible and bulky, according to researchers.
A recent addition to the wearable systems field are wearables produced with conductive fabric (CF), that have softness, lightweight, malleable, and are non-invasive. The sensors are comfortable and appropriate for tracking long-term. But, a majority of CF-based wearables end up error-prone if displaced from their intended area and depend on the outside components that are limiting the sensitivity as well as the working range of the sensors.
For the overcoming of these restrictions, the scientists formed a wearable that gives a high degree of functional and design freedom. Associate Professor Low Hong Yee together with her colleagues from SUTD joined hands with Dr Tan Ngiap Chuan of SingHealth Polyclinics and had their research paper published, ‘All knitted and integrated soft wearable of high stretchability and sensitivity for continuous monitoring of human joint motion’ that appeared in Advanced Healthcare Materials.
As indicated by Associate Professor Low, their main concerns as they designed the wearable were how accurate and reliable were the sensor data and for the sensor to depend on as lesser external objects as possible. They ended up with a highly stretchable, completely functioning sensing circuit produced from a single fabric. Due to the knee joint being significant for lower limb mobility, the wearable was created for the knee.
For the production of this single-fabric circuit, the scientists mechanically integrated an electrically conductive yarn that had a dielectric yarn of high elasticity for various stitch patterns. The dimensions were customized according to the leg of the individual. The functioning objects that consisted of sensors, interconnects, and resistors produced a stretchable circuit on the fully knitted wearable permitting real-time data to be collected.
But the drawing together of sensors, interconnects, as well as resistors in a single stretchable knit was hard as indicated by researchers. Associate Professor Low says “the synergy of yarns with different electrical and mechanical properties to achieve high signal sensitivity and high stretchability” was difficult, as the intended properties for each component had vast variations.
The sensors required the production of a large change in resistance for improved sensitivity, as interconnects along with resistors require fixed resistances of the maximum and minimum values, respectively. As such, the scientists optimized yarn composition and stitch type for every component prior to linking the functional circuit to a circuit board that was in a pocket of the wearable, that permits the wireless transmission of the real-time data.
Continuing on their findings, the researchers hope to learn the effect of sweat and humidity on sensor signals and go further with the research to bring in subjects from healthy as well as unhealthy populations in the years ahead.
