Student Georgia Institute of Technology Tenafly, New Jersey, United States
Introduction: The interlace between health and technology has been much more prevalent in recent years. Within those years, wearable bioelectronics for healthcare has been a prevailing pattern, specifically human motion monitoring. Studies in motion monitoring have explored the usage of strain sensors with a variety of materials such as metal and conductive polymers. However, there have been limitations as current conventional strain sensors are restricted to the working range when operating with the entire human body. In this study, a full-body motion suit uses resistive strain sensors made out of graphene to produce an accurate motion monitoring system, shown in Figure 1. This suit consists of eight wireless soft resistive strain sensors that are placed on various joints as the epidermal tissues surrounding the joints mechanically deform during motion. The resistive sensors measure the change in resistance and convert mechanical movements into electrical signals. With machine learning, a pioneering advancement in motion monitoring, the signals are collected into the strain database and converted into a real-time, full-body monitoring system. An additional IMU sensor is attached to the back, creating a reference point in a 3D space. These placements will allow the suit to detect the user’s intended movement based on the IMU information and deep-learned body-strained data of human joints. In this report, the fabrication of the resistive strain sensor will be detailed in-depth. The accuracy of the strain information will be collected and analyzed, proving the suit to be a reliable source of a motion monitoring system.
Materials and
Methods: To develop resistive strain sensors, two primary components are fabricated: the flexible circuit board and the resistive electrode. In the circuit, a Wheatstone Bridge is used to measure the resistance. A Nordic-Radio Frequency chip and Advanced Design System chip are incorporated to wirelessly transfer real-time resistance data from the sensor. A lithium polymer battery is then connected to provide a power supply and recharging port. A completed circuit is shown in Figure 2. Once the circuit board is fabricated, the resistive strain sensor is manufactured, as shown in Figure 3. The sensor is constructed from laser-induced graphene (LIG), which offers advantageous electrical conductivity and mechanical properties. LIG creates cost-effective and high-scalability graphene due to its simple laser irradiation on any precursor material. The electrode is printed on polyimide (PI) tape using the Alabama UV Laser. To solder the interconnects, copper is electroplated onto the ends of the resistive strain sensors. This interconnector, made out of PI and Cu, is serpentine-shaped, enabling the sensor to stretch without causing damage. Electroplating with copper E-plate solution, copper plate, a resistive sensor, and a power supplier, creates copper pads, onto which interconnects are then soldered. To protect the sensors, Polydimethylsiloxane (PDMS) is poured onto both sides of the electrode, spin-coated, and cured. To attach the sensor to the suit, a velcro mesh textile is incorporated into the ends of the sensor using silicone adhesive and fabric adhesive to securely attach it to the suit. This allows easy adjustment for subjects with different body sizes.
Results, Conclusions, and Discussions: Multiple tests were conducted to test the strain sensors' accuracy and precision, shown in Figure 4, using the Mark-10 digital force gauge for mechanical properties and the BK891 Precision for measuring electrical resistance. Figure 4a displays the response to strains ranging from 1% to 20% acting on the resistive sensors. Each strain was tested by stretching and releasing the sensors for 50 identical cycles. With constant resistance values within each strain, the sensor is shown to be precise up to 20% strain. Figure 4b shows that with 10% strain, the resistance spiked after about 80 ms and returned to its initial value within 225 ms after release. With a fast response and recovery rate, it is proven that the strain sensor can monitor strain information in real-time with high accuracy. Figure 4c tests the longevity of the sensor as it is stretched and released over 2000 cycles at 10% strain. The consistent change in resistance values is confirmed on the graph from the 1000th to the 1010th cycle. The full-body motion suit is expected to be long-lasting and provide precise data. The physical movement was examined with all resistive strain sensors attached to the suit. As shown in Figure 5, multichannel strain sensors were attached to the deltoids, knees, elbows, and gluteal. Observing the data collection for all body joints, there is a steady trend for every body joint as the change in resistance is constant over time. The motions are observed during the initial, transition, and final phases. Through these graphs, the final integration and application of the resistive strain sensors can be visualized. With consistent values and quick response and recovery rate, it is concluded that this device can track motion in real time without concern. With the multichannel LIG strain sensor, consisting of a flexible circuit and velcro-mesh path, this device can wirelessly strain data and recognize the client’s specific motion with a high level of accuracy and precision. The application has limitless potential and can be further developed for integration with smartphones or smartwatches, providing users with easier access to this information.
